Doubly Labelled Water Assessment of Elite Male-Squash Player’s Energy Balance During a Seven-Day Training Microcycle

Doubly Labelled Water Assessment of Elite Male-Squash Player’s Energy Balance During a Seven-Day Training Microcycle | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Case Report Doubly Labelled Water Assessment of Elite Male-Squash Player’s Energy Balance During a Seven-Day Training Microcycle Ollie Turner, Nigel Mitchell, Alan Ruddock, Alison Purvis, Catherine Hambly, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6779000/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract No previous research has quantified the energy balance of elite male squash players during a training microcycle. Consequently, the aim of this study was to concurrently quantify energy expenditure (EE), energy intake (EI) and energy availability (EA) among a cohort of elite male squash players to understand the energy balance of elite male squash players. Three elite male squash players were assessed during a 7-day training microcycle for TL (via heart rate monitoring, and sRPE), EE (via doubly labelled water technique), and EI (via weighed food method, Snap’N’Send photographic method, and 24-hour dietary recall). Mean daily EE was 4,210 ± 1,017 Kcals, with mean daily EI being 3,389 ± 981 Kcals, conveying a mean daily negative energy balance of 821 Kcals. Mean EA over the microcycle was 31.68 ± 17.91 Kcal⋅kg − 1 FFM⋅d − 1 indicating reduced EA. The study highlights that elite male squash players exhibit a high energy expenditure throughout a training microcycle and may follow poor nutrition strategies such as severe energy restriction, leading to low energy availability and sub optimal carbohydrate intake. These sub optimal nutritional practices may lead to reduced training performance and symptoms of relative energy deficiency in sport. Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Squash is a high intensity intermittent racket sport (Lees, 2003 ). At elite standard, squash requires a blend of technical, tactical, physical, and psychological capabilities (Jones et al., 2018 ). During simulated match play, elite male players are reported to elicit a mean energy expenditure of 1179 ± 148 Kcal⋅h − 1 , mean heart rate of 92 ± 3% heart rate maximum, mean blood lactate concentrations of 8.3 ± 3.4 mmol⋅L − 1 , and mean respiratory exchange ratio of 0.94 ± 0.04 (Girard et al., 2007 ). This highlights the high intensity nature of the sport and high energetic demands placed on players to maintain performance during match play. To sustain the high intensity demands of squash and simultaneously enhance technical capabilities, elite squash players engage in a variety of on and off-court training sessions (Gibson et al., 2019 ; James et al., 2021 ). These include group (i.e. conditioned games and routines), technical (i.e. 1–1 session with a coach), match play, ghosting (i.e. simulated squash-specific movements such as lunges into areas of the court), conditioning, and resistance sessions (Gibson et al., 2019 ; James et al., 2021 ). James et al., ( 2021 ) quantified the training load of elite Malaysian squash players across a variety of internal (i.e. psychophysiological) and external demands (i.e. musculoskeletal) (Neilsen et al., 2018; Impellizzeri et al., 2019 ). Players engaged in a mean total of 11 training sessions per week, equating to a mean training time of 258 minutes per week. James et al., ( 2021 ) reported that group sessions were the longest in duration (79 ± 12 min), eliciting the greatest session rating of perceived exertion (sRPE) (5793 ± 1477 a.u.) and high intensity movements (189 ± 88 > 3.5 m⋅s − 1 ) due to their longer duration in comparison to other sessions. Match play sessions were shown to have the greatest mean heart rate (81 ± 6% HR max ) and greatest time > 90% heart rate maximum (10 ± 10 min), while conditioning sessions were shown to have the greatest RPE (77 ± 16 a.u.) and player load (519 ± 153 a.u.). Given the apparent fluctuations of training load on a session-by-session basis, it is likely that energy expenditure is highly variable on a session-by-session basis. Consequently, the concept of ‘periodised’ nutrition has been developed (Jeukendrup, 2017 ) to ensure athletes are fuelling appropriately throughout variable training loads to optimise health (Mountjoy et al., 2023 ), achieve body composition goals (Stellingwerf et al., 2019), and augment training adaptations (Impey et al., 2018 ). It is also likely that elite male squash players have a high energy expenditure due to the high intensity demands of the sport (Girard et al., 2007 ). This may put players at risk of low energy availability (Mountjoy et al., 2023 ). Energy availability is a concept which is defined as the left-over dietary energy which can be utilised for optimal function of bodily systems after accounting for exercise energy expenditure, expressed relative to an individual’s fat free mass (Areta et al., 2021; Mountjoy et al., 2023 ). Chronic low energy availability, historically defined at a threshold of < 30 Kcal⋅kg − 1 FFM⋅d − 1 has been shown exhibit a variety of negative health outcomes in male athletes such as impaired reproductive function (Hooper et al., 2017 ), impaired bone health (Heikura et al., 2018 ;), impaired gastrointestinal function (Kuikman et al., 2021 ), impaired energy metabolism and regulation (Stenqvist et al., 2021 ), impaired haemological status (Hennigar et al., 2021 ), impaired glucose metabolism (Kojima et al., 2022 ), mental health issues (Torstveit et al., 2019 ), self-reported sleep disturbances (Pardue et al., 2017 ), impaired cardiovascular function (Langan-Evans et al., 2021 ), reduced skeletal muscle function (Pasiakos et al., 2010 ), impaired growth and development (Nindl et al., 2007 ) and reduced immunity (McGuire et al., 2023 ). These also have negative consequence on performance outcomes in male athletes such as decreased athlete availability (Drew et al., 2018 ), decreased training response (Woods et al., 2018 ), decreased recovery (Gillbanks et al., 2022 ), decreased motivation (Gillbanks et al., 2022 ), decreased muscle strength (Jurov et al., 2022 ), decreased endurance performance (Keay et al., 2018 ), and decreased power performance (Woods et al., 2018 ). Despite these potential negative consequences, there is currently no research quantifying either the energy expenditure, energy intake, or overall energy balance of elite male squash players. Therefore, it is difficult for sports nutrition practitioners to provide evidence-based recommendations to elite male squash players, due to a paucity of information regarding specific nutrition recommendations in the sport. This is unlike in other racket sports such as tennis (Ranchordas et al., 2013) and high intensity intermittent sports such as soccer (Collins et al., 2020), The doubly labelled water technique is the reference standard method of assessing energy expenditure in free-living individuals (Westerterp, 2017). The doubly labelled water technique has been used to provide estimates of energy expenditure in other sports such as tennis (Ellis et al., 2021 ; Ellis et al., 2023 a; Ellis et al., 2023 b), table tennis (Sagayama et al., 2017 ) and badminton (Watanabe et al., 2008), as well as other high intensity intermittent sports such as basketball (Silva et al., 2013 ), rugby league (Costello et al., 2018 ; Smith et al., 2018 ; Costello et al., 2019 ), rugby union (Morehen et al., 2016 ; Smith et al., 2018 ), and soccer (Ebine et al., 2002 ; Anderson et al., 2017 ; Anderson et al., 2019 ; Brinkmans et al., 2019 ; Hannon et al., 2021 ; Morehen et al., 2022 ; Dasa et al., 2023 ; Stables et al., 2023 ). Much of the literature has also quantified dietary intake alongside energy expenditure (Ebine et al., 2002 ; Silva et al., 2013 ; Morehen et al., 2016 ; Anderson et al., 2017 ; Sagayama et al., 2017 ; Anderson et al., 2019 ; Brinkmans et al., 2019 ; Hannon et al., 2021 ; Morehen et al., 2021; Dasa et al., 2023 ; Stables et al., 2023 ) to report any mismatches in recommendations and practice (Heikura et al., 2017 ). This data has enabled the creation of sport-specific nutritional guidelines to guide practitioners to appropriately advise athletes in other sports such as tennis (Ranchordas et al., 2013) and soccer (Collins et al., 2020). To estimate athletes’ total energy expenditure, a physical activity level (PAL) score can also be calculated (Westerterp, 2013 ). The PAL score is defined as any energy expended through bodily movements from skeletal muscle and is calculated as a magnitude of an individual’s resting metabolic rate (RMR) and their energy expenditure (Westerterp, 2013 ). The PAL score is a useful tool to quantify the physical demands of an individual or sport (i.e. no physical activity; sedentary and light activity; moderately active; vigorously active) and can be used to compare individual’s activity levels or between sports (Westerterp, 2013 ). No previous research has quantified the PAL score of elite male squash players and doing so would enable for comparison of physical activity levels in comparison to different sports, relative to an individual’s resting metabolic rate and energy expenditure. Research into the dietary habits of elite Spanish squash players via a food consumption frequency questionnaire (Ventura-Comes et al., 2019 ) conveyed that players practices are sub-optimal, under consuming carbohydrate rich foods such as bread, potatoes, pasta, and rice in comparison to non-specific carbohydrate guidelines (Burke et al., 2011 ). This may indicate that players do not consume enough carbohydrate to sustain their training load and may be at risk of low carbohydrate availability (Kojima et al., 2020 ; Mountjoy et al., 2023 ), which often occurs simultaneously with low energy availability (Logue et al., 2018 ). Turner et al., ( 2021 ) reported that although players had poor knowledge of contemporary macronutrient guidelines, they were still able to identify optimal pre, during and post exercise nutrition strategies. Consequently, it is relevant to consider whether non-specific carbohydrate and energy expenditure guidelines are suitable for elite squash players. Food frequency questionnaires have also been shown to display poor validity and reliability (Thompson & Subar, 2017 ) and therefore more valid and reliable methods to quantify dietary intake such as weighed food diaries, Snap ‘N’ Send and 24-h dietary recall (Bingham et al., 1994 ; Costello et al., 2017) need to be employed. Therefore, the aim of this study was to 1) quantify energy expenditure using the doubly labelled water technique, and 2) estimate energy intake through self-reported 7-day food dairy. This work is original because it is the first to report the energy balance of elite squash players throughout a microcycle, using the most rigorous methodological tool, doubly labelled water, and have a significant practical impact for the field by providing a basis from which to provide specific nutritional recommendations for elite squash players in context to their training load. Methods Participants Three elite or world class (McKay et al., 2022) male squash players took part in the study. Table 1 outlines the characteristics of each player. All players remained injury free throughout the course of the study and followed a decentralised training programme. Training was undertaken in a variety of facilities across the country. The research was approved by an institutional ethics committee (ER33101394). All participants provided informed consent before taking part and data were collected according to the principles of the 7th revision of the Declaration of Helsinki (World Medical Association, 2001 ). Table 1 Player’s characteristics Player (n) Player level (McKay et al., 2022) Age (y) Stature (m) Body Mass (kg) Sum of 8 skinfolds (mm) Resting Metabolic Rate (Kcals) Player goals 1 5 25 1.85 90.2 75.6 2141 Optimise body composition 2 5 22 1.85 81.8 51.4 1814 Fuel appropriately for training 3 4 23 1.80 75.6 51.7 - Fuel appropriately for training Mean ± SD 23 ± 2 183 ± 2.9 84.5 ± 7.2 59.6 ± 13.9 1978 ± 231 - Study Design Figure 1 displays a schematic overview of the study. The study was cross sectional in design. Data was collected during a 7-day microcycle within a pre-season training period. The week before the 7-day microcycle, each player’s RMR and body composition were calculated (see below). Player three’s RMR data was rendered void due to faulty equipment. Total energy expenditure was quantified using doubly labelled water technique (Westerterp, 2017). Total energy intake was measured via Snap’N’Send (Costello et al., 2017), weighed food method (Bingham et al., 1994 ), and 24-hour dietary recall (Bingham et al. 1994 ). Training load was quantified using heart rate monitoring and rating of perceived exertion during each training session. Players undertook their regular training regime as prescribed by their squash team. Anthropometrics, Body Composition & Resting Metabolic Rate Participants wore lightweight clothing for measurements of stature, body mass and sum of eight skinfold assessment, ensuring all jewellery was removed. Participant’s stature and body mass were quantified using a stadiometer and scales (SECA, Alpha 220, Hamburg, Germany), with this being measured to the nearest 0.1 cm and 0.1 kg respectively. Measurements were undertaken by an International Society for the Advancement of Kinanthropometry (ISAK) level one practitioner according to ISAK guidelines (Marfell-Jones et al., 2006 ). Two measurements were taken for each anthropometric measurement, with a third being taken if the first two measured had a variability greater than 2%. The mean value was recorded where two measures were taken, with the median being recorded where three measures were taken. Upon completion of all anthropometric measures, RMR was measured via open circuit indirect calorimetry (GEM Nutrition Ltd, UK), using the protocol outlined by Bone and Burke (Bone & Burke, 2018 ). The calorimeter was calibrated against known gas concentrations “zero” (0.0% O 2 and 0.0% CO 2 ) and “span” (20.0% O 2 and 1.0% CO 2 ) gases (BOC, Guildford, UK), prior to each assessment. After calibration and before data collection, participants relaxed for 10 minutes under a transparent ventilated hood in a supine position, in a dark, quiet, thermoneutral room. Subsequently, data was collected over a 20-minutes (2 x 10-minute duplicates), in which data from the second 10-minutes was used to quantify RMR. VO 2 and VCO 2 were quantified using the Haldane transformation (Haldane, 1918 ) and energy expenditure (Kcals⋅day − 1 ) using the Weir equation (Weir, 1949 ). Training Load Due to players undergoing training in different locations, each player reported their training via the mobile application WhatsApp (Facebook, California, USA) to quantify training load throughout the 7-day microcycle. Heart rate monitoring was used to quantify the cardiovascular demand of each session, with each player wearing a Polar H10 Heart Rate Sensor Band (Polar, Kempele, Finland) from the start of the warm-up to the completion of the warm-down of each session. The Heart rate sensor band transmitted data via bluetooth to the Polar Beat application (Polar, Kempele, Finland), storing the heart rate data, which was subsequently exported into a comma-separated value (CSV) file. Rating of perceived exertion (RPE) was quantified using the Foster modified CR10 scale (Foster et al., 2001 ) after each completed session. This was multiplied by the duration of each session to quantify session rating of perceived exertion (sRPE; Foster et al., 2001 ). The session duration was classified as the start of the warm-up to the completion of the warm-down. Players reported their RPE through the mobile application WhatsApp (Facebook, California, USA) when the principal investigator was not present. Players were educated on how to interpret the Foster modified CR10 scale prior to the 7-day microcycle so they could correctly interpret the scale, increasing the validity of the data collected. Energy Expenditure On the day before the 7-day microcycle, players were weighed to the nearest 0.1 kg (SECA, 875, Hamburg, Germany). Players then provided a baseline urine sample which was collected into a 35 ml cryogenic vial. Players then drank a single bolus dose of hydrogen (deuterium 2 H) and oxygen ( 18 O) stable isotopes in the form of water ( 2 H 2 18 O) through glass vials. The desired dose was 5% deuterium 2 H and 10% 18 O. This was calculated according to each player’s body mass, measured to the nearest decimal place, using the calculation: 18 O Dose= [0.65 (body mass, g) x DIE] / IE DIE = Desired initial enrichment = 618.923 x body mass (kg) −0305 IE = Initial enrichment = 10% = 100,000 ppm To ensure that all the bolus dose of doubly labelled water was consumed, each glass vial was refilled with additional water, with each player consuming. During the 7-day microcycle, each player deposited their second urine pass of the day into a 35 ml cryogenic vial, with this being stored and frozen at -80 o C for subsequent analysis. The time of players’ second urine pass of the day was recorded, as well as their body mass to the nearest 0.1 kg (SECA, 875, Hamburg, Germany). The first urine pass of the day was not used due to this being stored in the bladder overnight and therefore an inaccurate measure of energy expenditure (Westerterp, 2017). Urine samples were analysed to quantify total energy expenditure. Samples were compressed into capillary tubes before being vacuum distilled (Westerterp, 2017). The water from the subsequent distillate was used, being analysed in a liquid water analyser (Los Gatos Research; Berman et al., 2012 ). Samples were corrected to correct delta values to parts per million by analysing alongside three laboratory standards for each isotope and three international standards (Standard Light Arctic Precipitate, Standard Mean Ocean Water and Green Ice Sheet Precipitation). A two-pool model equation (Schoeller, 1988 ) was used to convert isotope enrichment to energy expenditure, assuming a food quotient of 0.85. Fat free mass (FFM) was quantified from total body water analysis ( 18 O dilution space), with this technique being shown to have a 6.03 ± 0.93% analytic error, within the acceptable range (Speakman et al., 2021) Energy Intake Energy intake was quantified through a self-reported 7-day food dairy via weighed food method, Snap’N’Send and 24-hour dietary recall (Bingham et al. 1994 ; Costello et al., 2017). These three methods combined have been shown to enhance the reliability of the assessment of energy intake (Thompson and Subar, 2017 ). Food diaries were completed via the mobile application WhatsApp (Facebook, California, USA), with players sending across details of any food or drink they consumed (i.e. name, mass and cooking methods), as well as an accompanying photo which was timestamped. Food diaries were cross-referenced with 24-hour dietary recall by the principal researcher after each day of completion. Each player attended an introductory workshop on how to complete the self-reported food diary as well as undergoing a three-day practice food diary prior to the two-week in season training period to highlight any issues or questions involving the self-reported food diary process. Upon completion of the 7-day microcycle, food diaries were analysed by a Sport and Exercise Nutrition Register (SENr) accredited nutritionist using the nutrition analysis software Nutritics (Nutritics Ltd, Ireland). To ensure consistency of analysis, the principal researcher analysed all 7 days of each players’ food diary. Energy intake was reported in kilocalories (Kcals) and kilocalories per kilogram of fat free mass (Kcal⋅kg⋅FFM − 1 ). Macronutrient intakes were analysed and reported in grams (g) and grams per kilogram of body mass (g⋅kg⋅bm − 1 ). Statistical Analysis All data are presented as mean ± standard deviation ( SD ). Training load data is reported for descriptive purposes. Physical activity level (PAL) was quantified through the following formula (FAO, et al., 2004; Westerterp, 2017): $$\:Physical\:Activity\:Level=\frac{Mean\:energy\:expenditure}{Resting\:metabolic\:rate}$$ Total energy expenditure in relation to fat free mass was calculated through the following formula: $$\:Kcalkg-1\:FFM=\frac{Total\:energy\:expenditure\:\left(Kcals\right)}{Fat\:free\:mass\:\left(kg\right)}$$ Energy availability was calculated through the following formula: $$\:Energy\:availability=\frac{Exercise\:energy\:expenditure-energy\:intake}{Kcalkg-1\:FFM}$$ Results Training Load Table 2 displays the mean training load data for feeding, ghosting, group, match play, conditioning, and strength sessions among the three players. Table 2 Mean training load data Type of Session Number of sessions ( n ) Duration (min) Mean Heart Rate (beats⋅min − 1 ) Maximum Heart Rate During the Session (beats⋅min − 1 ) Energy Expenditure (Kcals) RPE sRPE (a.u.) Feeding 2 65 ± 28 128 ± 17 158 ± 10 641 ± 74 4 ± 0 260 ± 113 Ghosting 2 100 ± 0 137 ± 10 192 ± 3 1137 ± 209 8 ± 1 800 ± 141 Group 11 99 ± 25 133 ± 9 178 ± 9 1036 ± 225 7 ± 2 672 ± 283 Match play 5 91 ± 30 140 ± 10 182 ± 10 1102 ± 249 7 ± 2 696 ± 293 Conditioning 2 89 ± 10 135 ± 2 184 ± 9 874 ± 21 6 ± 0 534 ± 59 Strength 6 88 ± 30 114 ± 19 172 ± 13 665 ± 272 7 ± 2 573 ± 210 Energy Balance Table 3 displays mean and individual energy expenditure and energy intake data. Table 3 Mean and individual energy expenditure and energy intake data Mean Player 1 Player 2 Player 3 Daily Energy Expenditure Kcals⋅d − 1 4210 ± 1017 4746 4847 3037 Kcal⋅kg⋅d − 1 49.82 ± 12.04 52.62 59.25 40.17 Kcal.kg − 1 .FFM 62.96 ± 10.72 68.34 69.92 50.61 MJ⋅d − 1 17.61 ± 4.26 19.86 20.28 12.71 kJ⋅kg⋅d − 1 208.45 ± 50.38 220.16 247.9 168.07 kJ⋅FFM⋅d − 1 263.42 ± 44.85 285.93 292.55 211.75 Physical Activity Level (PAL) 2.5 ± 0.4 2.2 2.7 - Daily Energy Intake Kcals⋅d − 1 3389 ± 981 2354 ± 588 4305 ± 1120 3507 ± 658 MJ⋅d − 1 14.18 ± 4.1 9.85 ± 2.46 18.01 ± 4.69 14.67 ± 2.75 Energy Availability Kcal⋅kg − 1 FFM⋅d − 1 32 ± 18 11 42 42 Carbohydrate g 318 ± 149 282 ± 61 557 ± 120 318 ± 118 g⋅kg⋅bm − 1 4.7 ± 2.1 2.9 ± 0.7 7 ± 1.5 4.2 ± 1.6 Protein g 177 ± 37 145 ± 56 168 ± 39 218 ± 52 g⋅kg⋅bm − 1 2.3 ± 0.6 1.7 ± 0.7 2.1 ± 0.5 2.9 ± 0.7 Fat g 128 ± 44 78 ± 29 156 ± 73 151 ± 27 g⋅kg⋅bm − 1 1.7 ± 0.6 0.9 ± 0.3 2.0 ± 0.9 2 ± 0.4 Fibre g 31 ± 6 26 ± 12 29 ± 8 37 ± 8 MJ = Megajoules; kJ = Kilojoules Player One Player one’s characteristics are reported in Table 1 , with the players training schedule and load being reported in Table 4 . Table 4 Training schedule and load for player one Microcycle Day Training Session ( n ) Type of Session Duration (min) Mean Heart Rate (beats⋅min − 1 ) Maximum Heart Rate During the Session (beats⋅min − 1 ) Energy Expenditure (Kcals) RPE sRPE (a.u.) 1 1 Match play 108 139 178 1403 7 756 Daily Total 108 1403 756 2 2 Group 115 125 176 1200 5 575 3 Group 83 141 173 1109 6 498 Daily Total 198 2309 1073 3 4 Strength 73 149 173 1053 9 657 5 Match play 82 151 178 1238 9 738 Daily Total 155 2291 1395 4 6 Group 94 138 182 1206 7 658 7 Match play 50 145 169 659 5 250 Daily Total 144 1865 908 5 8 Group 81 134 168 1001 6 486 9 Match play 60 144 173 800 6 360 Daily Total 141 1801 846 6 10 Group 64 143 173 884 6 384 Daily Total 64 884 384 7 11 Group 45 140 165 589 4 180 Daily Total 45 589 180 Mean ± STDEV - - 78 ± 22 141 + 7 174 ± 5 1013 ± 256 6 ± 2 504 ± 194 Mean daily energy expenditure for player one over the 7-day microcycle was 4746 Kcals, equating to a PAL of 2.2. When expressed in relation to FFM, energy expenditure was 68.34 Kcal⋅kg − 1 FFM. Mean daily energy intake over the 7-day microcycle being reported as 2354 ± 588 Kcals⋅d − 1 , resulting in a mean energy balance of -2,392 Kcals⋅d − 1 . Consequently, energy availability was 11 Kcal⋅kg − 1 FFM⋅d − 1 . Figures 2 A-C display the mean and daily macronutrient intake in grams (g), mean and daily macronutrient intake in g.kg.bm (g.kg.bm), and mean and daily energy intake (Kcals). Supplementary Table 1 reports player one’s daily energy, macronutrient, and fibre intake. Player Two Player two’s characteristics are reported in Table 1 , with the players training schedule and load being reported in Table 5 . Table 5 Training load of player two Microcycle Day Training Session ( n ) Type of Session Duration (min) Mean Heart Rate (beats⋅min − 1 ) Maximum Heart Rate During the Session (beats⋅min − 1 ) Energy Expenditure (Kcals) RPE sRPE (a.u.) 1 1 Strength 133 105 186 832 6 798 2 Group 125 146 192 1251 8 1000 Daily Total 258 2083 1798 2 3 Ghosting 100 144 194 1285 7 700 4 Conditioning 96 136 190 889 6 576 Daily Total 196 2174 1276 3 5 Strength 90 118 181 745 8 720 6 Group 80 125 176 772 4 320 Daily Total 170 1517 1040 4 7 Feeding 85 116 151 693 4 340 8 Group 122 138 194 1454 8 976 Daily Total 207 2147 1316 5 9 Strength 95 97 176 483 6 570 10 Match play 96 143 195 1231 8 768 Daily Total 191 1714 1338 Mean - - 102 ± 18 127 + 17 184 ± 14 964 ± 318 7 ± 2 677 ± 231 Mean daily energy expenditure for player one over the 7-day microcycle was 4,847 Kcals, equating to a PAL of 2.7. When expressed in relation to FFM, energy expenditure was 69.92 Kcal⋅kg − 1 FFM. Mean daily energy intake over the 7-day microcycle was reported as 4305 ± 1120 Kcals⋅d. This conveys a mean energy balance of -542 Kcals per day. Consequently, energy availability was 42 Kcal⋅kg − 1 FFM⋅d − 1 . Figures 3 A-C display the mean and daily macronutrient intake in grams (g), mean and daily macronutrient intake in g.kg.bm (g.kg.bm), and mean and daily energy intake (Kcals). Supplementary Table 2 reports player two’s daily energy, macronutrient, and fibre intake. Player Three Player three’s characteristics are reported in Table 1 , with the players training schedule and load being reported in Table 6 . Table 6 Training load of player three Microcycle Day Training Session ( n ) Type of Session Duration (min) Mean Heart Rate (beats⋅min − 1 ) Maximum Heart Rate During the Session (beats⋅min − 1 ) Energy Expenditure (Kcals) RPE sRPE (a.u.) 1 1 Strength 42 106 154 283 5 210 2 Group 121 124 182 1072 8 968 Daily Total 163 1355 1178 2 3 Ghosting 100 130 190 989 9 900 4 Conditioning 82 133 177 859 6 492 Daily Total 182 1848 1392 3 5 Match play 133 124 186 1176 8 1064 Daily Total 133 1176 1064 4 6 Group 134 122 177 968 8 1072 7 Group 81 126 165 783 5 405 Daily Total 215 1751 1477 5 8 Group 79 134 183 833 9 711 9 Strength 96 106 159 595 5 480 Daily Total 175 1428 1191 Mean ± STDEV - - 96 ± 30 123 + 10 175 ± 13 835 ± 267 7 ± 2 630 ± 372 Mean daily energy expenditure for player one over the 7-day microcycle was 3037 Kcals. When expressed in relation to FFM, energy expenditure was 50.61 Kcal⋅kg − 1 FFM. Mean daily energy intake over the 7-day microcycle was reported as 3507 ± 658 Kcals⋅day. This conveys a mean energy balance of + 470 Kcals per day. Consequently, energy availability was 42 Kcal⋅kg − 1 FFM⋅d − 1 . Unfortunately, the PAL could not be calculated due to faulty equipment when measuring resting metabolic rate. Over the 7-day microcycle, the player engaged in 11 training sessions, with Table 3 conveying the training load of these sessions. Figures 4 A-C display the mean and daily macronutrient intake in grams (g), mean and daily macronutrient intake in g.kg.bm (g.kg.bm), and mean and daily energy intake (Kcals). Supplementary Table 3 reports player three’s daily energy, macronutrient, and fibre intake. Discussion The main aims of this study were to 1) quantify energy expenditure using the doubly labelled water technique in elite male squash players during a seven day microcycle, and 2) estimate energy intake in elite male squash players through a self-reported seven day food dairy. The main findings of the study were (1) elite male squash players expended a mean daily energy expenditure of 4,210 ± 1,017 Kcals (2) players ingested a mean daily energy intake of 3,389 ± 981 Kcals (3) players exhibited a mean daily energy balance of -821 Kcals; (4) players had a mean energy availability of 32 ± 18 Kcal⋅kg − 1 FFM⋅d − 1 throughout the microcycle (5) the mean PAL score of elite squash players was 2.5 ± 0.4. This work is original in that it is the first study to quantify the energy balance of elite male squash players, using the reference standard and highly rigorous DLW technique. This work will make a significant impact in the field by providing a basis for specific nutritional practices. Quantifying the energy balance of elite male squash players highlights players current practices and whether they are optimal in relation to their training load, while providing data to create specific nutritional guidelines for squash players to inform future practice. This study implemented rigorous methodological procedures such as the doubly labelled water method which is the reference standard to assess energy expenditure (Westerterp, 2017). The study also utilised a combination of three methods to assess energy intake, a self-reported 7-day food dairy via weighed food method, Snap’N’Send and 24-hour dietary recall (Bingham et al. 1994 ; Costello et al., 2017), with these three methods combined have been shown to enhance the reliability of the assessment of energy intake (Thompson and Subar, 2017 ). In the first investigation of its kind, using the doubly labelled water method, we identified the mean energy expenditure among the three players over the 7-day microcycle was 4,210 ± 1,017 Kcals. The doubly labelled water method provides a robust assessment of energy expenditure through enriching an individual with heavy oxygen ( 18 O) and hydrogen ( 2 H) and measuring the difference in the washout kinetics of the isotopes (Westerterp, 2017). It is the only method of measuring energy expenditure without interference to the behaviour of individuals, and therefore seen as the reference standard for measuring energy expenditure in free living individuals (Westerterp, 2017). To contextualise the energy expenditure data reported in elite male squash players, it is relevant to compare to other racket sports and high intensity intermittent sports which have utilised the doubly labelled water method. Ellis et al., ( 2021 ) reported the energy expenditure of an elite male tennis player. Data collection was split into two separate periods, with period one being a training microcycle with one professional ATP international match, and period two being a competition microcycle consisting of five ATP international matches and a reduced training load. During period one, the tennis player expended less energy than reported in the present study, expending 3712 Kcals⋅d − 1 or 56.3 Kcal⋅kg − 1 FFM when expressed relative to FFM, less than elite male squash players (62.96 ± 10.72 Kcal⋅kg − 1 FFM). Consequently, elite male squash players are reported to expend 13.4% more than elite male tennis players during a training microcycle. During the competition period, the tennis player expended more than the present study, expending 5520 Kcals⋅d − 1 or 83.7 Kcal⋅kg − 1 FFM when expressed relative to FFM. This highlights the variance in energy expenditure on a microcycle basis and the influence of match play on the energy expenditures of tennis players. The present study quantified the training load and energy expenditure of elite male squash players during a training microcycle, and future research should aim to quantify the player load and energy expenditure of elite male squash players during a competition. This would ascertain whether the player load and energy expenditure are greater during competition periods, as experienced in elite male tennis and devise specific nutritional guidelines for elite male squash players during competition. The present study reports that energy expenditure in elite male squash players was greater than reported in elite male soccer players during an in-season microcycle (3566 ± 585 Kcals⋅d − 1 ; Anderson et al., 2017 ). Elite soccer players during an in-season microcycle are reported to have rest days and reduced training load to facilitate preparation and recovery for competitive matches (Malone et al., 2015 ), unlike elite squash players who will sustain consistent training loads until they reach a competition phase. Elite male squash players were shown to expend less energy than elite rugby league players during an in-season training and competition microcycle (5374 ± 645 Kcals⋅d − 1 ; Morehen et al., 2016 ). Elite rugby league players body masses are reported to be greater than elite squash players (rugby league = 94.7 ± 6.7 kg [Morehen et al., 2016 ]; squash = 84.5 ± 7.2 kg), with body mass being shown to be a determinant of energy expenditure (Westerterp, 2017b ). This is also supported in our results given the energy expenditure of player 1 at 90 kg was greater than player 3 at 75 kg. Collision based activity has also been shown to increase total daily energy expenditure through an increase in collision induced muscle damage (Costello et al., 2018 ), and this may increase the energy expenditure of rugby league players in comparison to squash players. The PAL of elite squash players was 2.5 ± 0.4. PAL. Values of 2.5 are reported as the ‘upper limit’ for ‘sustained lifestyle’ and in an unclassified range above the range (2.0-2.4) associated with ‘vigorous lifestyle’ (Westerterp, 2013 ). The PAL value observed is greater than elite male tennis players during a training microcycle (2.2; Ellis et al., 2021 ), elite soccer players during an in-season training and competition microcycle (1.75 ± 0.13; Brinkmans et al., 2019 ), but less than elite rugby league plays during an in-season training and competition microcycle (2.9; Morehen et al., 2016 ). Consequently, this study reports a valid and accurate assessment of energy expenditure among elite male squash players during a training microcycle, in combination with a PAL value which can be utilised to devise squash specific nutritional recommendations. Energy availability is a well-established concept to support individuals’ health and performance (Areta et al., 2021; Mountjoy et al., 2023 ). Due to the high energy expenditure and PAL value experienced by players in the present study, players need to ensure that they are consuming enough energy to fuel their training. Mean energy intake among the three players over the 7-day microcycle was 3,389 ± 981 Kcals, resulting in a mean daily energy balance of -821 Kcals. On an individual level, player one reported a mean daily energy balance of -2,392 Kcals⋅d − 1 and body mass reduction of 2.1 kg over the seven day microcycle; player two reported a mean daily energy balance of -542 Kcals⋅d − 1 and body mass increase of 0.8 kg over the seven day microcycle; and player three reported a mean daily energy balance of + 470 Kcals⋅d − 1 and body mass reduction of 0.5 kg over the seven day microcycle. Increases in body mass while in a negative energy balance such as in player two suggest there is likely to be an underreporting of energy intake, rather than undereating, a common phenomenon within nutritional science (Black et al., 1993 ). Indeed, research in elite male soccer (Anderson et al., 2017 ; Brinkmans et al., 2019 ) and rugby league players (Morehen et al., 2016 ) all reported lower energy intakes than energy expenditures despite body mass remaining stable throughout the duration of the microcycles. Mean energy availability among the three players over the microcycle was 31.68 ± 17.91 Kcal⋅kg − 1 FFM⋅d − 1 . When reported individually, players two and three had an energy availability of 42.35 Kcal⋅kg − 1 FFM⋅d − 1 and 41.69 Kcal⋅kg − 1 FFM⋅d − 1 respectively, indicating reduced energy availability according to the International Olympic Committee’s Consensus Statement of Relative Energy Deficiency in Sport (Mountjoy et al., 2023 ). Player one exhibited an energy balance of − 2,392 Kcals⋅d − 1 and energy availability of 11 Kcal⋅kg − 1 FFM⋅d − 1 , indicating low energy availability according to the International Olympic Committee’s Consensus Statement of Relative Energy Deficiency in Sport (Mountjoy et al., 2023 ). Low energy availability has many negative consequences on health and performance-based outcomes (Mountjoy et al., 2023 ). Therefore, it is crucial appropriate nutrition strategies are devised to support optimal, health, wellbeing and performance. This study reports valid and accurate data to help support elite male squash players to adopt appropriate nutrition strategies and mitigate against low energy availability (see practical application section). A potential limitation of the study was that exercise energy expenditure, and subsequently energy availability was calculated through heart rate monitoring rather than the gold standard indirect calorimetry. Heart rate monitoring was shown to yield a non-significant (1.2 ± 6.2%; p = > 0.05) mean underestimate of total energy expenditure in comparison to indirect calorimetry (Ceesay et al., 1989 ). Consequently, due to the nature of the study and inability to measure exercise energy expenditure through indirect calorimetry, heart rate monitoring was used to quantify expenditure. The Polar H10 band was selected, as this has been shown to have the greatest RR signal strength during high intensity activities and high correlation to an electrocardiography Holter monitor (Gilgen-Ammann et al., 2019 ). Squash is a high intensity intermittent sport (Girard et al., 2007 ), and, therefore, carbohydrates play a key role in energy metabolism (Van Loon et al., 2001 ). Previous research into the dietary habits of elite Spanish squash players has suggested that players under-consume carbohydrate rich foods such as bread, potatoes, pasta, and rice (Ventura-Comes et al., 2019 ). Mean carbohydrate intake was 4.7 ± 2.1 g⋅kg⋅bm − 1 among players, which highlights under-fuelling in comparison to non-specific sports nutrition carbohydrate guidelines (Burke et al., 2011 ). Burke et al., ( 2011 ) proposed a carbohydrate target intake of 6–10 g⋅kg⋅bm − 1 for individuals engaging in 1–3 hours of high intensity activity per day. Low carbohydrate availability often occurs simultaneously with low energy availability (Logue et al., 2018 ). Indeed, player one’s carbohydrate intake was a mean of 2.9 ± 0.7 g⋅kg⋅bm − 1 over the microcycle which is lower than non-specific guidelines (Burke et al., 2011 ). Carbohydrate intake appears to be individualised with player two consuming 7 ± 1.5 g⋅kg⋅bm − 1 and player three consuming 4.2 ± 1.6 g⋅kg⋅bm − 1 . Players’ nutritional choices are highly individualised and based on a variety of different physiological, cultural, psychological, social, and economic factors (Birkenhead & Slater, 2015 ). Nutrition knowledge is one of those factors which can influence the food choice of players (Birkenhead & Slater, 2015 ). To this extent, the data presented in this study aims to increase knowledge through increasing understanding of the energy expenditure of elite squash players throughout a microcycle, and as a result, the energy and carbohydrate requirements of elite squash players. Periodised nutrition is a well-established concept to ensure athletes fuel appropriately throughout variable training loads (Jeukendrup, 2017 ). Elite squash players appear to have variable training loads with player one’s daily training duration, daily exercise energy expenditure, and daily sRPE ranging from 45 to 198 minutes, 589 to 2,309 Kcals and 180 to 1,395 respectively; players two’s ranging from 170 to 258 (daily training duration), 1,517 to 2,174 (daily exercise energy expenditure), and 1,040 to 1,798 (daily sRPE); and players three’s ranging from 133 to 215 (daily training duration), 1,176 to 1,848 (daily exercise energy expenditure), and 1,064 to 1,477 (daily sRPE). A limitation of the doubly labelled water technique is its inability to provide day to day energy expenditure assessments, hence energy expenditure being expressed over a 7-day microcycle in this study. It is likely that energy expenditure varied on a day-to-day basis and while nutritional recommendations can be devised to account for the energy expenditure over a microcycle, day to day recommendations may be appropriate to optimise training adaptation (Impey et al., 2017), body composition (Stellingwerf, 2019) and physical performance (Jeukendrup, 2017 ). There was some evidence of energy periodisation within the present study with player one’s energy intake varying from 1932 Kcals (daily sRPE = 180) to 3306 Kcals (daily sRPE = 1,395); player two’s energy intake varying from 2834 Kcals (daily sRPE = 0) to 6,361 Kcals (daily sRPE = 1,798); and player three’s energy intake varying from 2,499 Kcals (daily sRPE = 0) to 4,421 Kcals (daily sRPE = 1,191). Practical Applications The present study demonstrates that elite male squash players exhibit a high energy expenditure throughout a training microcycle and follow inappropriate nutrition strategies such as sub optimal carbohydrate intake or in one case, severe energy restriction, leading to low energy availability. This may lead to a wide range of health and performance-based consequences (Mounjoy et al., 2023). One of the aims of the paper was to increase the understanding of the energy expenditure of elite male squash players throughout a microcycle, so that energy and carbohydrate guidelines can be devised. Consequently, for an 85 kg player (the mean of the three players body mass in this study) wanting to achieve energy balance, if protein intake was fixed at the suggested guidelines of 1.4 to 2 g⋅kg⋅bm − 1 (119g to 170g; 476 Kcals to 680 Kcals; Jäger et al., 2018) and fat intake was fixed at 30% of total energy intake (1.6 g⋅kg⋅bm − 1 ; 140g; 1263 Kcals; Kerksick et al., 2018 ), carbohydrate intake should be between 2,267 and 2,471 Kcals (depending on the individuals protein intake), equating to 567 to 618 g or 6.6 to 7.2 g⋅kg⋅bm − 1 of carbohydrate per day. The training load data suggests that elite male squash players have a varied training load, and therefore players should work with a registered sport dietitian or sports nutritionist to optimally periodise their energy and carbohydrate intake alongside their training load to maximise training adaptations and performance (Jeukendrup, 2017 ). Declarations A cknowledgements The authors at Sheffield Hallam University would like to thank Catherine Hambly and her team at the University of Aberdeen for collaborating on this study and advising on how to conduct the doubly labelled water technique as well as analysis of the samples. The authors would also like to thank England Squash and the elite male squash players who took part in the study, advancing scientific knowledge within the sport Author Contributions O. Turner, M. Ranchordas N. Mitchell, A. Ruddock, A. Purvis and designed the study. O. Turner recruited players, undertook some of the data analysis with C. Hambly & J. Speakman carrying out analysis of the urine samples to determine total daily energy expenditure, O. Turner drafted the manuscript and oversaw manuscript preparation. M. Ranchordas, N. Mitchell, A. Ruddock and A. Purvis assisted with revising the manuscript. All authors read and approved the final manuscript. Funding Funding was provided by Sheffield Hallam University and England Squash as part of O Turner’s PhD programme Institutional Review Board Statement The research was approved by Sheffield Hallam University’s ethics committee (ER33101394) Informed Consent Statement All players provided informed consent prior to participating in the research. Data Availability Statement Most of the data generated or analysed during this study are included in this published article [and its supplementary information files] such as training load, energy expenditure and energy intake data Disclosure of Interest The authors declare that they have no competing interests. References Anderson, L., Orme, P., Naughton, R. J., Close, G. L., Milsom, J., Rydings, D., . . . Morton, J. P. (2017). Energy intake and expenditure of professional soccer players of the E nglish premier league: Evidence of carbohydrate periodization. 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International Journal of Sport Nutrition and Exercise Metabolism, 27 (6), 550-559. doi:10.1123/ijsnem.2017-0064 Pasiakos, S. M., Vislocky, L. M., Carbone, J. W., Altieri, N., Konopelski, K., Freake, H. C., . . . Rodriguez, N. R. (2010). Acute energy deprivation affects skeletal muscle protein synthesis and associated intracellular signaling proteins in physically active adults. The Journal of Nutrition, 140 (4), 745-751. doi:10.3945/jn.109.118372 Ranchordas, M. K., Dawson, J. T., & Russell, M. (2017). Practical nutritional recovery strategies for elite soccer players when limited time separates repeated matches. Journal of the International Society of Sports Nutrition, 14 , 35. doi:10.1186/s12970-017-0193-8 Sagayama, H., Hamaguchi, G., Toguchi, M., Ichikawa, M., Yamada, Y., Ebine, N., . . . Tanaka, H. (2017). Energy requirement assessment in japanese table tennis players using the doubly labeled water method. International Journal of Sport Nutrition and Exercise Metabolism, 27 (5), 421-428. doi:10.1123/ijsnem.2017-0022 Schoeller, A., D. (1988). Measurement of energy expenditure in free-living humans by using doubly labelled water. The Journal of Nutrition, 118 , 1278-1289. Silva, A. M., Santos, D. A., Matias, C. N., Minderico, C. S., Schoeller, D. A., & Sardinha, L. B. (2013). Total energy expenditure assessment in elite junior basketball players: A validation study using doubly labeled water. Journal of Strength and Conditioning Research, 27 (7), 1920-1927. doi:10.1519/JSC.0b013e31827361eb Smith, D. R., King, R. F. G. J., Duckworth, L. C., Sutton, L., Preston, T., O’Hara, J. P., & Jones, B. (2018). Energy expenditure of rugby players during a 14-day in-season period, measured using doubly labelled water. European Journal of Applied Physiology, 118 (3), 647-656. doi:10.1007/s00421-018-3804-4 Stables, R. G., Kasper, A. M., Sparks, S. A., Morton, J. P., & Close, G. L. (2021). An assessment of the validity of the remote food photography method (termed snap-N-send) in experienced and inexperienced sport nutritionists. International Journal of Sport Nutrition and Exercise Metabolism, 31 (2), 125-134. doi:10.1123/IJSNEM.2020-0216 Stables, R. G., Hannon, M. P., Jacob, A. D., Topping, O., Costello, N. B., Boddy, L. M., . . . Morton, J. P. (2023). Daily energy requirements of male academy soccer players are greater than age-matched non-academy soccer players: A doubly labelled water investigation. Journal of Sports Sciences, 41 (12), 1218-1230. doi:10.1080/02640414.2023.2263707 Stenqvist, T. B., Melin, A. K., Garthe, I., Slater, G., Paulsen, G., Iraki, J., . . . Torstveit, M. K. (2021). Prevalence of surrogate markers of relative energy deficiency in male norwegian olympic-level athletes. International Journal of Sport Nutrition and Exercise Metabolism, 31 (6), 497-506. doi:10.1123/ijsnem.2020-0368 Stellingwerff, T., Morton, J. P., & Burke, L. M. (2019). A framework for periodized nutrition for athletics. International Journal of Sport Nutrition and Exercise Metabolism, 29 (2), 1-151. doi:10.1123/ijsnem.2018-0305 Thompson FE, Subar AF. Dietary assessment methodology. In: Coulston AM, editor. Nutrition in the prevention and treatment of disease. London: Academic; 2017. p. 5–48. https://doi.org/10.1016/B978-0-12-802928-2. 00001-1. Torstveit, M. K., Fahrenholtz, I. L., Lichtenstein, M. B., Stenqvist, T. B., & Melin, A. K. (2019). Exercise dependence, eating disorder symptoms and biomarkers of relative energy deficiency in sports (RED-S) among male endurance athletes. BMJ Open Sport & Exercise Medicine, 5 (1), e000439. doi:10.1136/bmjsem-2018-000439 Turner, O., Mitchell, N., Ruddock, A., Purvis, A., & Ranchordas, M. (2021). Elite squash players nutrition knowledge and influencing factors. Journal of the International Society of Sports Nutrition, 18 (1), 1-46. doi:10.1186/s12970-021-00443-3 van Loon, L. J., Greenhaff, P. L., Constantin-Teodosiu, D., Saris, W. H., & Wagenmakers, A. J. (2001). The effects of increasing exercise intensity on muscle fuel utilisation in humans. The Journal of Physiology, 536 (1), 295-304. doi:10.1111/j.1469-7793.2001.00295.x Ventura-Comes A, Martínez-Sanz JM, Sánchez-Oliver AJ, & Domínguez R (2019) Analysis of foods habits in squash players. J Phys Ed Sport 19:1300-1307. doi:10.7752/jpes.2019.s4189 Weir, J. B. (1949). New methods for calculating metabolic rate with special reference to protein metabolism. The Journal of Physiology, 109 (1-2), 1-9. doi:10.1113/jphysiol.1949.sp004363 Westerterp, K. R. (2013). Physical activity and physical activity induced energy expenditure in humans: Measurement, determinants, and effects. Frontiers in Physiology, 4 , 90. doi:10.3389/fphys.2013.00090 Westerterp, K. R. (2017 a ). Doubly labelled water assessment of energy expenditure: Principle, practice, and promise. European Journal of Applied Physiology, 117 (7), 1277-1285. doi:10.1007/s00421-017-3641-x Westerterp, K. R. (2017 b ). Control of energy expenditure in humans. European Journal of Clinical Nutrition, 71 (3), 340-344. doi:10.1038/ejcn.2016.237 Woods, A. L., Rice, A. J., Garvican-Lewis, L., Wallett, A. M., Lundy, B., Rogers, M. A., . . . Thompson, K. G. (2018). The effects of intensified training on resting metabolic rate (RMR), body composition and performance in trained cyclists. PloS One, 13 (2), e0191644. doi:10.1371/journal.pone.0191644 World Medical Association (2001). World Medical Association Declaration of Helsinki: Ethical principles for medical research involving human subjects. World Health Organisation. , 79 , 373–374. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6779000","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Case Report","associatedPublications":[],"authors":[{"id":466273801,"identity":"357b1d8c-e1ab-4244-a9d9-f44ddd400a2b","order_by":0,"name":"Ollie Turner","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYBACA/7GhgMSP2zq+UE8xgaIKIzGrkXi8MEDlj1pCZINRGthSEs+UMF2KMHgALFazBnOGBy4wXMgz/jaGQPGnzsOM/C3H2CTnIFHi2Vzj8HBGRZ3is1u5xgw8545zCBxJoFNcgM+hx04Y3BYgucZ4zaQFsa2wwwMNxjYJB/g1ZJjcPgP22HGzbNzgA4DapEnrCUt4YAE2+HEDdI5Bgy8QC0GIC34HGY54/CBA5I9acYSt9MKDvO2pfMYnklstsTnfXP+xuYPwKiU45+dvPHhzzZrObnjhw/e7MGjBQlwgKOGh0CsoAD2B8SqHAWjYBSMghEGAHgTWJfsiwQMAAAAAElFTkSuQmCC","orcid":"","institution":"Sheffield Hallam University","correspondingAuthor":true,"prefix":"","firstName":"Ollie","middleName":"","lastName":"Turner","suffix":""},{"id":466273802,"identity":"c3c9795b-5fd2-4471-a985-cb38ce3860c7","order_by":1,"name":"Nigel Mitchell","email":"","orcid":"","institution":"UK Sports Institute","correspondingAuthor":false,"prefix":"","firstName":"Nigel","middleName":"","lastName":"Mitchell","suffix":""},{"id":466273803,"identity":"99ee27c1-93d4-4b82-851e-b92206fd9895","order_by":2,"name":"Alan Ruddock","email":"","orcid":"","institution":"Sheffield Hallam University","correspondingAuthor":false,"prefix":"","firstName":"Alan","middleName":"","lastName":"Ruddock","suffix":""},{"id":466273804,"identity":"31b62938-d398-433b-b4fe-093646bf3fc5","order_by":3,"name":"Alison Purvis","email":"","orcid":"","institution":"Sheffield Hallam University","correspondingAuthor":false,"prefix":"","firstName":"Alison","middleName":"","lastName":"Purvis","suffix":""},{"id":466273805,"identity":"b9ff910b-cc68-42ba-ab1d-2248e13a68d7","order_by":4,"name":"Catherine Hambly","email":"","orcid":"","institution":"University of Aberdeen","correspondingAuthor":false,"prefix":"","firstName":"Catherine","middleName":"","lastName":"Hambly","suffix":""},{"id":466273806,"identity":"10656503-7630-45ef-8de7-3013b646e2e9","order_by":5,"name":"John Speakman","email":"","orcid":"","institution":"University of Aberdeen","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"","lastName":"Speakman","suffix":""},{"id":466273807,"identity":"e70bf64a-3c7c-4550-963f-e6674df10943","order_by":6,"name":"Mayur Ranchordas","email":"","orcid":"","institution":"Sheffield Hallam University","correspondingAuthor":false,"prefix":"","firstName":"Mayur","middleName":"","lastName":"Ranchordas","suffix":""}],"badges":[],"createdAt":"2025-05-29 19:08:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6779000/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6779000/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84212883,"identity":"68a079cd-c3c9-4494-8d39-4b244ac436b6","added_by":"auto","created_at":"2025-06-09 10:21:27","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":157745,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic overview of: A) player one; B) player two; C) player three\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6779000/v1/59eda9927c3b5133da4b9779.jpg"},{"id":84212877,"identity":"d1ca25f4-f06c-4bf4-915c-61ecae170bb2","added_by":"auto","created_at":"2025-06-09 10:21:27","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":64431,"visible":true,"origin":"","legend":"\u003cp\u003ePlayer one’s daily macronutrient intake reported in (A) grams and (B) grams per kilogram of body mass and (C) daily energy intake reported in Kcals\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6779000/v1/0afe2f9a53b0f86b89b42423.jpg"},{"id":84214346,"identity":"e414e019-b331-4afc-9499-23efbd8a8bde","added_by":"auto","created_at":"2025-06-09 10:29:27","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":66818,"visible":true,"origin":"","legend":"\u003cp\u003ePlayer two’s daily macronutrient intake reported in (A) grams and (B) grams per kilogram of body mass and (C) daily energy intake reported in Kcals\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6779000/v1/4440805a717719a8f8987855.jpg"},{"id":84214347,"identity":"ba01df73-df50-4c21-a33f-5371d15cfb05","added_by":"auto","created_at":"2025-06-09 10:29:27","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":68073,"visible":true,"origin":"","legend":"\u003cp\u003ePlayer three’s daily macronutrient intake reported in (A) grams and (B) grams per kilogram of body mass and (C) daily energy intake reported in Kcals\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6779000/v1/05f95c4e73755ba1123f7e82.jpg"},{"id":84215236,"identity":"82302e38-6cb6-49b1-b97d-2b77ba7086e0","added_by":"auto","created_at":"2025-06-09 10:37:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2057976,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6779000/v1/0dab1e7f-0005-4ecd-bc96-a807211096be.pdf"},{"id":84212876,"identity":"d81e9d28-eb14-4a88-9be4-9e24af97c73d","added_by":"auto","created_at":"2025-06-09 10:21:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":21029,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytables.docx","url":"https://assets-eu.researchsquare.com/files/rs-6779000/v1/bed49106fe846f160a2a5daf.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Doubly Labelled Water Assessment of Elite Male-Squash Player’s Energy Balance During a Seven-Day Training Microcycle","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSquash is a high intensity intermittent racket sport (Lees, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). At elite standard, squash requires a blend of technical, tactical, physical, and psychological capabilities (Jones et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). During simulated match play, elite male players are reported to elicit a mean energy expenditure of 1179\u0026thinsp;\u0026plusmn;\u0026thinsp;148 Kcal\u0026sdot;h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, mean heart rate of 92\u0026thinsp;\u0026plusmn;\u0026thinsp;3% heart rate maximum, mean blood lactate concentrations of 8.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4 mmol\u0026sdot;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and mean respiratory exchange ratio of 0.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04 (Girard et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). This highlights the high intensity nature of the sport and high energetic demands placed on players to maintain performance during match play.\u003c/p\u003e \u003cp\u003eTo sustain the high intensity demands of squash and simultaneously enhance technical capabilities, elite squash players engage in a variety of on and off-court training sessions (Gibson et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; James et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These include group (i.e. conditioned games and routines), technical (i.e. 1\u0026ndash;1 session with a coach), match play, ghosting (i.e. simulated squash-specific movements such as lunges into areas of the court), conditioning, and resistance sessions (Gibson et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; James et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). James et al., (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) quantified the training load of elite Malaysian squash players across a variety of internal (i.e. psychophysiological) and external demands (i.e. musculoskeletal) (Neilsen et al., 2018; Impellizzeri et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Players engaged in a mean total of 11 training sessions per week, equating to a mean training time of 258 minutes per week. James et al., (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported that group sessions were the longest in duration (79\u0026thinsp;\u0026plusmn;\u0026thinsp;12 min), eliciting the greatest session rating of perceived exertion (sRPE) (5793\u0026thinsp;\u0026plusmn;\u0026thinsp;1477 a.u.) and high intensity movements (189\u0026thinsp;\u0026plusmn;\u0026thinsp;88\u0026thinsp;\u0026gt;\u0026thinsp;3.5 m\u0026sdot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) due to their longer duration in comparison to other sessions. Match play sessions were shown to have the greatest mean heart rate (81\u0026thinsp;\u0026plusmn;\u0026thinsp;6% HR\u003csub\u003emax\u003c/sub\u003e) and greatest time\u0026thinsp;\u0026gt;\u0026thinsp;90% heart rate maximum (10\u0026thinsp;\u0026plusmn;\u0026thinsp;10 min), while conditioning sessions were shown to have the greatest RPE (77\u0026thinsp;\u0026plusmn;\u0026thinsp;16 a.u.) and player load (519\u0026thinsp;\u0026plusmn;\u0026thinsp;153 a.u.).\u003c/p\u003e \u003cp\u003eGiven the apparent fluctuations of training load on a session-by-session basis, it is likely that energy expenditure is highly variable on a session-by-session basis. Consequently, the concept of \u0026lsquo;periodised\u0026rsquo; nutrition has been developed (Jeukendrup, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) to ensure athletes are fuelling appropriately throughout variable training loads to optimise health (Mountjoy et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), achieve body composition goals (Stellingwerf et al., 2019), and augment training adaptations (Impey et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). It is also likely that elite male squash players have a high energy expenditure due to the high intensity demands of the sport (Girard et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). This may put players at risk of low energy availability (Mountjoy et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Energy availability is a concept which is defined as the left-over dietary energy which can be utilised for optimal function of bodily systems after accounting for exercise energy expenditure, expressed relative to an individual\u0026rsquo;s fat free mass (Areta et al., 2021; Mountjoy et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Chronic low energy availability, historically defined at a threshold of \u0026lt;\u0026thinsp;30 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e has been shown exhibit a variety of negative health outcomes in male athletes such as impaired reproductive function (Hooper et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), impaired bone health (Heikura et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e;), impaired gastrointestinal function (Kuikman et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), impaired energy metabolism and regulation (Stenqvist et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), impaired haemological status (Hennigar et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), impaired glucose metabolism (Kojima et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), mental health issues (Torstveit et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), self-reported sleep disturbances (Pardue et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), impaired cardiovascular function (Langan-Evans et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), reduced skeletal muscle function (Pasiakos et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), impaired growth and development (Nindl et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and reduced immunity (McGuire et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These also have negative consequence on performance outcomes in male athletes such as decreased athlete availability (Drew et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), decreased training response (Woods et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), decreased recovery (Gillbanks et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), decreased motivation (Gillbanks et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), decreased muscle strength (Jurov et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), decreased endurance performance (Keay et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and decreased power performance (Woods et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Despite these potential negative consequences, there is currently no research quantifying either the energy expenditure, energy intake, or overall energy balance of elite male squash players. Therefore, it is difficult for sports nutrition practitioners to provide evidence-based recommendations to elite male squash players, due to a paucity of information regarding specific nutrition recommendations in the sport. This is unlike in other racket sports such as tennis (Ranchordas et al., 2013) and high intensity intermittent sports such as soccer (Collins et al., 2020),\u003c/p\u003e \u003cp\u003eThe doubly labelled water technique is the reference standard method of assessing energy expenditure in free-living individuals (Westerterp, 2017). The doubly labelled water technique has been used to provide estimates of energy expenditure in other sports such as tennis (Ellis et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ellis et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003ea; Ellis et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003eb), table tennis (Sagayama et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and badminton (Watanabe et al., 2008), as well as other high intensity intermittent sports such as basketball (Silva et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), rugby league (Costello et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Smith et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Costello et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), rugby union (Morehen et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Smith et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and soccer (Ebine et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Anderson et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Anderson et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Brinkmans et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hannon et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Morehen et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Dasa et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Stables et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Much of the literature has also quantified dietary intake alongside energy expenditure (Ebine et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Silva et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Morehen et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Anderson et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Sagayama et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Anderson et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Brinkmans et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hannon et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Morehen et al., 2021; Dasa et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Stables et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) to report any mismatches in recommendations and practice (Heikura et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This data has enabled the creation of sport-specific nutritional guidelines to guide practitioners to appropriately advise athletes in other sports such as tennis (Ranchordas et al., 2013) and soccer (Collins et al., 2020).\u003c/p\u003e \u003cp\u003eTo estimate athletes\u0026rsquo; total energy expenditure, a physical activity level (PAL) score can also be calculated (Westerterp, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The PAL score is defined as any energy expended through bodily movements from skeletal muscle and is calculated as a magnitude of an individual\u0026rsquo;s resting metabolic rate (RMR) and their energy expenditure (Westerterp, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The PAL score is a useful tool to quantify the physical demands of an individual or sport (i.e. no physical activity; sedentary and light activity; moderately active; vigorously active) and can be used to compare individual\u0026rsquo;s activity levels or between sports (Westerterp, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). No previous research has quantified the PAL score of elite male squash players and doing so would enable for comparison of physical activity levels in comparison to different sports, relative to an individual\u0026rsquo;s resting metabolic rate and energy expenditure.\u003c/p\u003e \u003cp\u003eResearch into the dietary habits of elite Spanish squash players via a food consumption frequency questionnaire (Ventura-Comes et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) conveyed that players practices are sub-optimal, under consuming carbohydrate rich foods such as bread, potatoes, pasta, and rice in comparison to non-specific carbohydrate guidelines (Burke et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This may indicate that players do not consume enough carbohydrate to sustain their training load and may be at risk of low carbohydrate availability (Kojima et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mountjoy et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), which often occurs simultaneously with low energy availability (Logue et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Turner et al., (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported that although players had poor knowledge of contemporary macronutrient guidelines, they were still able to identify optimal pre, during and post exercise nutrition strategies. Consequently, it is relevant to consider whether non-specific carbohydrate and energy expenditure guidelines are suitable for elite squash players. Food frequency questionnaires have also been shown to display poor validity and reliability (Thompson \u0026amp; Subar, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and therefore more valid and reliable methods to quantify dietary intake such as weighed food diaries, Snap \u0026lsquo;N\u0026rsquo; Send and 24-h dietary recall (Bingham et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Costello et al., 2017) need to be employed.\u003c/p\u003e \u003cp\u003eTherefore, the aim of this study was to 1) quantify energy expenditure using the doubly labelled water technique, and 2) estimate energy intake through self-reported 7-day food dairy. This work is original because it is the first to report the energy balance of elite squash players throughout a microcycle, using the most rigorous methodological tool, doubly labelled water, and have a significant practical impact for the field by providing a basis from which to provide specific nutritional recommendations for elite squash players in context to their training load.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThree elite or world class (McKay et al., 2022) male squash players took part in the study. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e outlines the characteristics of each player. All players remained injury free throughout the course of the study and followed a decentralised training programme. Training was undertaken in a variety of facilities across the country. The research was approved by an institutional ethics committee (ER33101394). All participants provided informed consent before taking part and data were collected according to the principles of the 7th revision of the Declaration of Helsinki (World Medical Association, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePlayer\u0026rsquo;s characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlayer (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlayer level\u003c/p\u003e \u003cp\u003e(McKay et al., 2022)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAge (y)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStature (m)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBody Mass (kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSum of 8 skinfolds (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eResting Metabolic Rate (Kcals)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePlayer goals\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e75.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOptimise body composition\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eFuel appropriately for training\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e75.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eFuel appropriately for training\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e183\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e84.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e59.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1978\u0026thinsp;\u0026plusmn;\u0026thinsp;231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Design\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displays a schematic overview of the study. The study was cross sectional in design. Data was collected during a 7-day microcycle within a pre-season training period. The week before the 7-day microcycle, each player\u0026rsquo;s RMR and body composition were calculated (see below). Player three\u0026rsquo;s RMR data was rendered void due to faulty equipment. Total energy expenditure was quantified using doubly labelled water technique (Westerterp, 2017). Total energy intake was measured via Snap\u0026rsquo;N\u0026rsquo;Send (Costello et al., 2017), weighed food method (Bingham et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1994\u003c/span\u003e), and 24-hour dietary recall (Bingham et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Training load was quantified using heart rate monitoring and rating of perceived exertion during each training session. Players undertook their regular training regime as prescribed by their squash team.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eAnthropometrics, Body Composition \u0026 Resting Metabolic Rate\u003c/h3\u003e\n\u003cp\u003eParticipants wore lightweight clothing for measurements of stature, body mass and sum of eight skinfold assessment, ensuring all jewellery was removed. Participant\u0026rsquo;s stature and body mass were quantified using a stadiometer and scales (SECA, Alpha 220, Hamburg, Germany), with this being measured to the nearest 0.1 cm and 0.1 kg respectively. Measurements were undertaken by an International Society for the Advancement of Kinanthropometry (ISAK) level one practitioner according to ISAK guidelines (Marfell-Jones et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Two measurements were taken for each anthropometric measurement, with a third being taken if the first two measured had a variability greater than 2%. The mean value was recorded where two measures were taken, with the median being recorded where three measures were taken.\u003c/p\u003e \u003cp\u003eUpon completion of all anthropometric measures, RMR was measured via open circuit indirect calorimetry (GEM Nutrition Ltd, UK), using the protocol outlined by Bone and Burke (Bone \u0026amp; Burke, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The calorimeter was calibrated against known gas concentrations \u0026ldquo;zero\u0026rdquo; (0.0% O\u003csub\u003e2\u003c/sub\u003e and 0.0% CO\u003csub\u003e2\u003c/sub\u003e) and \u0026ldquo;span\u0026rdquo; (20.0% O\u003csub\u003e2\u003c/sub\u003e and 1.0% CO\u003csub\u003e2\u003c/sub\u003e) gases (BOC, Guildford, UK), prior to each assessment. After calibration and before data collection, participants relaxed for 10 minutes under a transparent ventilated hood in a supine position, in a dark, quiet, thermoneutral room. Subsequently, data was collected over a 20-minutes (2 x 10-minute duplicates), in which data from the second 10-minutes was used to quantify RMR. VO\u003csub\u003e2\u003c/sub\u003e and VCO\u003csub\u003e2\u003c/sub\u003e were quantified using the Haldane transformation (Haldane, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1918\u003c/span\u003e) and energy expenditure (Kcals\u0026sdot;day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) using the Weir equation (Weir, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e1949\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eTraining Load\u003c/h3\u003e\n\u003cp\u003eDue to players undergoing training in different locations, each player reported their training via the mobile application WhatsApp (Facebook, California, USA) to quantify training load throughout the 7-day microcycle. Heart rate monitoring was used to quantify the cardiovascular demand of each session, with each player wearing a Polar H10 Heart Rate Sensor Band (Polar, Kempele, Finland) from the start of the warm-up to the completion of the warm-down of each session. The Heart rate sensor band transmitted data via bluetooth to the Polar Beat application (Polar, Kempele, Finland), storing the heart rate data, which was subsequently exported into a comma-separated value (CSV) file. Rating of perceived exertion (RPE) was quantified using the Foster modified CR10 scale (Foster et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) after each completed session. This was multiplied by the duration of each session to quantify session rating of perceived exertion (sRPE; Foster et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The session duration was classified as the start of the warm-up to the completion of the warm-down. Players reported their RPE through the mobile application WhatsApp (Facebook, California, USA) when the principal investigator was not present. Players were educated on how to interpret the Foster modified CR10 scale prior to the 7-day microcycle so they could correctly interpret the scale, increasing the validity of the data collected.\u003c/p\u003e\n\u003ch3\u003eEnergy Expenditure\u003c/h3\u003e\n\u003cp\u003eOn the day before the 7-day microcycle, players were weighed to the nearest 0.1 kg (SECA, 875, Hamburg, Germany). Players then provided a baseline urine sample which was collected into a 35 ml cryogenic vial. Players then drank a single bolus dose of hydrogen (deuterium \u003csup\u003e2\u003c/sup\u003eH) and oxygen (\u003csup\u003e18\u003c/sup\u003eO) stable isotopes in the form of water (\u003csup\u003e2\u003c/sup\u003eH\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e18\u003c/sup\u003eO) through glass vials. The desired dose was 5% deuterium \u003csup\u003e2\u003c/sup\u003eH and 10% \u003csup\u003e18\u003c/sup\u003eO. This was calculated according to each player\u0026rsquo;s body mass, measured to the nearest decimal place, using the calculation:\u003c/p\u003e \u003cp\u003e \u003csup\u003e18\u003c/sup\u003eO Dose= [0.65 (body mass, g) x DIE] / IE\u003c/p\u003e \u003cp\u003eDIE\u0026thinsp;=\u0026thinsp;Desired initial enrichment\u0026thinsp;=\u0026thinsp;618.923 x body mass (kg)\u003csup\u003e\u0026minus;0305\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIE\u0026thinsp;=\u0026thinsp;Initial enrichment\u0026thinsp;=\u0026thinsp;10% = 100,000 ppm\u003c/p\u003e \u003cp\u003eTo ensure that all the bolus dose of doubly labelled water was consumed, each glass vial was refilled with additional water, with each player consuming.\u003c/p\u003e \u003cp\u003eDuring the 7-day microcycle, each player deposited their second urine pass of the day into a 35 ml cryogenic vial, with this being stored and frozen at -80\u003csup\u003eo\u003c/sup\u003eC for subsequent analysis. The time of players\u0026rsquo; second urine pass of the day was recorded, as well as their body mass to the nearest 0.1 kg (SECA, 875, Hamburg, Germany). The first urine pass of the day was not used due to this being stored in the bladder overnight and therefore an inaccurate measure of energy expenditure (Westerterp, 2017).\u003c/p\u003e \u003cp\u003eUrine samples were analysed to quantify total energy expenditure. Samples were compressed into capillary tubes before being vacuum distilled (Westerterp, 2017). The water from the subsequent distillate was used, being analysed in a liquid water analyser (Los Gatos Research; Berman et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Samples were corrected to correct delta values to parts per million by analysing alongside three laboratory standards for each isotope and three international standards (Standard Light Arctic Precipitate, Standard Mean Ocean Water and Green Ice Sheet Precipitation). A two-pool model equation (Schoeller, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1988\u003c/span\u003e) was used to convert isotope enrichment to energy expenditure, assuming a food quotient of 0.85.\u003c/p\u003e \u003cp\u003eFat free mass (FFM) was quantified from total body water analysis (\u003csup\u003e18\u003c/sup\u003eO dilution space), with this technique being shown to have a 6.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93% analytic error, within the acceptable range (Speakman et al., 2021)\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEnergy Intake\u003c/h2\u003e \u003cp\u003eEnergy intake was quantified through a self-reported 7-day food dairy via weighed food method, Snap\u0026rsquo;N\u0026rsquo;Send and 24-hour dietary recall (Bingham et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Costello et al., 2017). These three methods combined have been shown to enhance the reliability of the assessment of energy intake (Thompson and Subar, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Food diaries were completed via the mobile application WhatsApp (Facebook, California, USA), with players sending across details of any food or drink they consumed (i.e. name, mass and cooking methods), as well as an accompanying photo which was timestamped. Food diaries were cross-referenced with 24-hour dietary recall by the principal researcher after each day of completion. Each player attended an introductory workshop on how to complete the self-reported food diary as well as undergoing a three-day practice food diary prior to the two-week in season training period to highlight any issues or questions involving the self-reported food diary process.\u003c/p\u003e \u003cp\u003eUpon completion of the 7-day microcycle, food diaries were analysed by a Sport and Exercise Nutrition Register (SENr) accredited nutritionist using the nutrition analysis software Nutritics (Nutritics Ltd, Ireland). To ensure consistency of analysis, the principal researcher analysed all 7 days of each players\u0026rsquo; food diary. Energy intake was reported in kilocalories (Kcals) and kilocalories per kilogram of fat free mass (Kcal\u0026sdot;kg\u0026sdot;FFM\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Macronutrient intakes were analysed and reported in grams (g) and grams per kilogram of body mass (g\u0026sdot;kg\u0026sdot;bm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (\u003cem\u003eSD\u003c/em\u003e). Training load data is reported for descriptive purposes. Physical activity level (PAL) was quantified through the following formula (FAO, et al., 2004; Westerterp, 2017):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:Physical\\:Activity\\:Level=\\frac{Mean\\:energy\\:expenditure}{Resting\\:metabolic\\:rate}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eTotal energy expenditure in relation to fat free mass was calculated through the following formula:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:Kcalkg-1\\:FFM=\\frac{Total\\:energy\\:expenditure\\:\\left(Kcals\\right)}{Fat\\:free\\:mass\\:\\left(kg\\right)}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eEnergy availability was calculated through the following formula:\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:Energy\\:availability=\\frac{Exercise\\:energy\\:expenditure-energy\\:intake}{Kcalkg-1\\:FFM}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTraining Load\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e displays the mean training load data for feeding, ghosting, group, match play, conditioning, and strength sessions among the three players.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean training load data\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of Session\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of sessions (\u003cem\u003en\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDuration\u003c/p\u003e \u003cp\u003e(min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean Heart Rate (beats\u0026sdot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMaximum Heart Rate During the Session\u003c/p\u003e \u003cp\u003e(beats\u0026sdot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEnergy Expenditure (Kcals)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRPE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003esRPE\u003c/p\u003e \u003cp\u003e(a.u.)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e128\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e158\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e641\u0026thinsp;\u0026plusmn;\u0026thinsp;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e4\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e260\u0026thinsp;\u0026plusmn;\u0026thinsp;113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGhosting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e100\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e137\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e192\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e1137\u0026thinsp;\u0026plusmn;\u0026thinsp;209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e8\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e800\u0026thinsp;\u0026plusmn;\u0026thinsp;141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e99\u0026thinsp;\u0026plusmn;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e133\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e178\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e1036\u0026thinsp;\u0026plusmn;\u0026thinsp;225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e7\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e672\u0026thinsp;\u0026plusmn;\u0026thinsp;283\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMatch play\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e91\u0026thinsp;\u0026plusmn;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e140\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e182\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e1102\u0026thinsp;\u0026plusmn;\u0026thinsp;249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e7\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e696\u0026thinsp;\u0026plusmn;\u0026thinsp;293\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConditioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e89\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e135\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e184\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e874\u0026thinsp;\u0026plusmn;\u0026thinsp;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e534\u0026thinsp;\u0026plusmn;\u0026thinsp;59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e88\u0026thinsp;\u0026plusmn;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e114\u0026thinsp;\u0026plusmn;\u0026thinsp;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e172\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e665\u0026thinsp;\u0026plusmn;\u0026thinsp;272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e7\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e573\u0026thinsp;\u0026plusmn;\u0026thinsp;210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEnergy Balance\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e displays mean and individual energy expenditure and energy intake data.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean and individual energy expenditure and energy intake data\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePlayer 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePlayer 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePlayer 3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eDaily Energy Expenditure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKcals\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4210\u0026thinsp;\u0026plusmn;\u0026thinsp;1017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKcal\u0026sdot;kg\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e49.82\u0026thinsp;\u0026plusmn;\u0026thinsp;12.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKcal.kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.FFM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e62.96\u0026thinsp;\u0026plusmn;\u0026thinsp;10.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMJ\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e17.61\u0026thinsp;\u0026plusmn;\u0026thinsp;4.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ekJ\u0026sdot;kg\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e208.45\u0026thinsp;\u0026plusmn;\u0026thinsp;50.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e220.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e247.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e168.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ekJ\u0026sdot;FFM\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e263.42\u0026thinsp;\u0026plusmn;\u0026thinsp;44.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e285.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e292.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e211.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical Activity Level (PAL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eDaily Energy Intake\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKcals\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3389\u0026thinsp;\u0026plusmn;\u0026thinsp;981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2354\u0026thinsp;\u0026plusmn;\u0026thinsp;588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4305\u0026thinsp;\u0026plusmn;\u0026thinsp;1120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3507\u0026thinsp;\u0026plusmn;\u0026thinsp;658\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMJ\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e14.18\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.85\u0026thinsp;\u0026plusmn;\u0026thinsp;2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.01\u0026thinsp;\u0026plusmn;\u0026thinsp;4.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEnergy Availability\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCarbohydrate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e318\u0026thinsp;\u0026plusmn;\u0026thinsp;149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e282\u0026thinsp;\u0026plusmn;\u0026thinsp;61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e557\u0026thinsp;\u0026plusmn;\u0026thinsp;120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e318\u0026thinsp;\u0026plusmn;\u0026thinsp;118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eg\u0026sdot;kg\u0026sdot;bm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eProtein\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e177\u0026thinsp;\u0026plusmn;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e145\u0026thinsp;\u0026plusmn;\u0026thinsp;56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e168\u0026thinsp;\u0026plusmn;\u0026thinsp;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e218\u0026thinsp;\u0026plusmn;\u0026thinsp;52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eg\u0026sdot;kg\u0026sdot;bm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eFat\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e128\u0026thinsp;\u0026plusmn;\u0026thinsp;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78\u0026thinsp;\u0026plusmn;\u0026thinsp;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e156\u0026thinsp;\u0026plusmn;\u0026thinsp;73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e151\u0026thinsp;\u0026plusmn;\u0026thinsp;27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eg\u0026sdot;kg\u0026sdot;bm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFibre\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e31\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eMJ\u0026thinsp;=\u0026thinsp;Megajoules; kJ\u0026thinsp;=\u0026thinsp;Kilojoules\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePlayer One\u003c/h2\u003e \u003cp\u003ePlayer one\u0026rsquo;s characteristics are reported in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, with the players training schedule and load being reported in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTraining schedule and load for player one\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicrocycle Day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTraining Session\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eType of Session\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDuration\u003c/p\u003e \u003cp\u003e(min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean Heart Rate (beats\u0026sdot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMaximum Heart Rate During the Session\u003c/p\u003e \u003cp\u003e(beats\u0026sdot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEnergy Expenditure (Kcals)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRPE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003esRPE\u003c/p\u003e \u003cp\u003e(a.u.)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMatch play\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e756\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e108\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1403\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e756\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e575\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e498\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e198\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e2309\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1073\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStrength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e657\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMatch play\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e738\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e155\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e2291\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1395\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e658\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMatch play\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e144\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1865\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e908\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e486\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMatch play\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e141\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1801\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e846\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e384\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e64\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e884\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e384\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e45\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e589\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e180\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;STDEV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78\u0026thinsp;\u0026plusmn;\u0026thinsp;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e141\u0026thinsp;+\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e174\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1013\u0026thinsp;\u0026plusmn;\u0026thinsp;256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e504\u0026thinsp;\u0026plusmn;\u0026thinsp;194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMean daily energy expenditure for player one over the 7-day microcycle was 4746 Kcals, equating to a PAL of 2.2. When expressed in relation to FFM, energy expenditure was 68.34 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM. Mean daily energy intake over the 7-day microcycle being reported as 2354\u0026thinsp;\u0026plusmn;\u0026thinsp;588 Kcals\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, resulting in a mean energy balance of -2,392 Kcals\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Consequently, energy availability was 11 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Figures\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-C display the mean and daily macronutrient intake in grams (g), mean and daily macronutrient intake in g.kg.bm (g.kg.bm), and mean and daily energy intake (Kcals). Supplementary Table\u0026nbsp;1 reports player one\u0026rsquo;s daily energy, macronutrient, and fibre intake.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePlayer Two\u003c/h2\u003e \u003cp\u003ePlayer two\u0026rsquo;s characteristics are reported in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, with the players training schedule and load being reported in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTraining load of player two\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicrocycle Day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTraining Session\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eType of Session\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDuration\u003c/p\u003e \u003cp\u003e(min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean Heart Rate (beats\u0026sdot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMaximum Heart Rate During the Session\u003c/p\u003e \u003cp\u003e(beats\u0026sdot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEnergy Expenditure (Kcals)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRPE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003esRPE\u003c/p\u003e \u003cp\u003e(a.u.)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStrength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e798\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e258\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e2083\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1798\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGhosting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConditioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e576\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e196\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e2174\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1276\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStrength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e720\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e320\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1517\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1040\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFeeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e340\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e976\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e207\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e2147\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1316\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStrength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e570\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMatch play\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e768\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e191\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1714\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1338\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102\u0026thinsp;\u0026plusmn;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e127\u0026thinsp;+\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e184\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e964\u0026thinsp;\u0026plusmn;\u0026thinsp;318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e677\u0026thinsp;\u0026plusmn;\u0026thinsp;231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMean daily energy expenditure for player one over the 7-day microcycle was 4,847 Kcals, equating to a PAL of 2.7. When expressed in relation to FFM, energy expenditure was 69.92 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM. Mean daily energy intake over the 7-day microcycle was reported as 4305\u0026thinsp;\u0026plusmn;\u0026thinsp;1120 Kcals\u0026sdot;d. This conveys a mean energy balance of -542 Kcals per day. Consequently, energy availability was 42 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003eFFM\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Figures\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-C display the mean and daily macronutrient intake in grams (g), mean and daily macronutrient intake in g.kg.bm (g.kg.bm), and mean and daily energy intake (Kcals). Supplementary Table\u0026nbsp;2 reports player two\u0026rsquo;s daily energy, macronutrient, and fibre intake.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePlayer Three\u003c/h2\u003e \u003cp\u003ePlayer three\u0026rsquo;s characteristics are reported in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, with the players training schedule and load being reported in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTraining load of player three\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicrocycle Day\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTraining Session\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eType of Session\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDuration\u003c/p\u003e \u003cp\u003e(min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean Heart Rate (beats\u0026sdot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMaximum Heart Rate During the Session\u003c/p\u003e \u003cp\u003e(beats\u0026sdot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEnergy Expenditure (Kcals)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRPE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003esRPE\u003c/p\u003e \u003cp\u003e(a.u.)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStrength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e968\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e163\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1355\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1178\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGhosting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e900\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConditioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e492\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e182\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1848\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1392\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMatch play\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e133\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1176\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1064\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1072\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e405\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e215\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1751\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1477\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e711\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStrength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e595\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e480\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaily Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e175\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1428\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1191\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;STDEV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96\u0026thinsp;\u0026plusmn;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e123\u0026thinsp;+\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e175\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e835\u0026thinsp;\u0026plusmn;\u0026thinsp;267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e630\u0026thinsp;\u0026plusmn;\u0026thinsp;372\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMean daily energy expenditure for player one over the 7-day microcycle was 3037 Kcals. When expressed in relation to FFM, energy expenditure was 50.61 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM. Mean daily energy intake over the 7-day microcycle was reported as 3507\u0026thinsp;\u0026plusmn;\u0026thinsp;658 Kcals\u0026sdot;day. This conveys a mean energy balance of +\u0026thinsp;470 Kcals per day. Consequently, energy availability was 42 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Unfortunately, the PAL could not be calculated due to faulty equipment when measuring resting metabolic rate. Over the 7-day microcycle, the player engaged in 11 training sessions, with Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e conveying the training load of these sessions. Figures\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-C display the mean and daily macronutrient intake in grams (g), mean and daily macronutrient intake in g.kg.bm (g.kg.bm), and mean and daily energy intake (Kcals). Supplementary Table\u0026nbsp;3 reports player three\u0026rsquo;s daily energy, macronutrient, and fibre intake.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe main aims of this study were to 1) quantify energy expenditure using the doubly labelled water technique in elite male squash players during a seven day microcycle, and 2) estimate energy intake in elite male squash players through a self-reported seven day food dairy. The main findings of the study were (1) elite male squash players expended a mean daily energy expenditure of 4,210\u0026thinsp;\u0026plusmn;\u0026thinsp;1,017 Kcals (2) players ingested a mean daily energy intake of 3,389\u0026thinsp;\u0026plusmn;\u0026thinsp;981 Kcals (3) players exhibited a mean daily energy balance of -821 Kcals; (4) players had a mean energy availability of 32\u0026thinsp;\u0026plusmn;\u0026thinsp;18 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e throughout the microcycle (5) the mean PAL score of elite squash players was 2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4. This work is original in that it is the first study to quantify the energy balance of elite male squash players, using the reference standard and highly rigorous DLW technique. This work will make a significant impact in the field by providing a basis for specific nutritional practices. Quantifying the energy balance of elite male squash players highlights players current practices and whether they are optimal in relation to their training load, while providing data to create specific nutritional guidelines for squash players to inform future practice. This study implemented rigorous methodological procedures such as the doubly labelled water method which is the reference standard to assess energy expenditure (Westerterp, 2017). The study also utilised a combination of three methods to assess energy intake, a self-reported 7-day food dairy via weighed food method, Snap\u0026rsquo;N\u0026rsquo;Send and 24-hour dietary recall (Bingham et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Costello et al., 2017), with these three methods combined have been shown to enhance the reliability of the assessment of energy intake (Thompson and Subar, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the first investigation of its kind, using the doubly labelled water method, we identified the mean energy expenditure among the three players over the 7-day microcycle was 4,210\u0026thinsp;\u0026plusmn;\u0026thinsp;1,017 Kcals. The doubly labelled water method provides a robust assessment of energy expenditure through enriching an individual with heavy oxygen (\u003csup\u003e18\u003c/sup\u003eO) and hydrogen (\u003csup\u003e2\u003c/sup\u003eH) and measuring the difference in the washout kinetics of the isotopes (Westerterp, 2017). It is the only method of measuring energy expenditure without interference to the behaviour of individuals, and therefore seen as the reference standard for measuring energy expenditure in free living individuals (Westerterp, 2017). To contextualise the energy expenditure data reported in elite male squash players, it is relevant to compare to other racket sports and high intensity intermittent sports which have utilised the doubly labelled water method. Ellis et al., (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported the energy expenditure of an elite male tennis player. Data collection was split into two separate periods, with period one being a training microcycle with one professional ATP international match, and period two being a competition microcycle consisting of five ATP international matches and a reduced training load. During period one, the tennis player expended less energy than reported in the present study, expending 3712 Kcals\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e or 56.3 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM when expressed relative to FFM, less than elite male squash players (62.96\u0026thinsp;\u0026plusmn;\u0026thinsp;10.72 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM). Consequently, elite male squash players are reported to expend 13.4% more than elite male tennis players during a training microcycle. During the competition period, the tennis player expended more than the present study, expending 5520 Kcals\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e or 83.7 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM when expressed relative to FFM. This highlights the variance in energy expenditure on a microcycle basis and the influence of match play on the energy expenditures of tennis players. The present study quantified the training load and energy expenditure of elite male squash players during a training microcycle, and future research should aim to quantify the player load and energy expenditure of elite male squash players during a competition. This would ascertain whether the player load and energy expenditure are greater during competition periods, as experienced in elite male tennis and devise specific nutritional guidelines for elite male squash players during competition.\u003c/p\u003e \u003cp\u003eThe present study reports that energy expenditure in elite male squash players was greater than reported in elite male soccer players during an in-season microcycle (3566\u0026thinsp;\u0026plusmn;\u0026thinsp;585 Kcals\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; Anderson et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Elite soccer players during an in-season microcycle are reported to have rest days and reduced training load to facilitate preparation and recovery for competitive matches (Malone et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), unlike elite squash players who will sustain consistent training loads until they reach a competition phase. Elite male squash players were shown to expend less energy than elite rugby league players during an in-season training and competition microcycle (5374\u0026thinsp;\u0026plusmn;\u0026thinsp;645 Kcals\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; Morehen et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Elite rugby league players body masses are reported to be greater than elite squash players (rugby league\u0026thinsp;=\u0026thinsp;94.7\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7 kg [Morehen et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e]; squash\u0026thinsp;=\u0026thinsp;84.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2 kg), with body mass being shown to be a determinant of energy expenditure (Westerterp, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2017b\u003c/span\u003e). This is also supported in our results given the energy expenditure of player 1 at 90 kg was greater than player 3 at 75 kg. Collision based activity has also been shown to increase total daily energy expenditure through an increase in collision induced muscle damage (Costello et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and this may increase the energy expenditure of rugby league players in comparison to squash players.\u003c/p\u003e \u003cp\u003eThe PAL of elite squash players was 2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4. PAL. Values of 2.5 are reported as the \u0026lsquo;upper limit\u0026rsquo; for \u0026lsquo;sustained lifestyle\u0026rsquo; and in an unclassified range above the range (2.0-2.4) associated with \u0026lsquo;vigorous lifestyle\u0026rsquo; (Westerterp, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The PAL value observed is greater than elite male tennis players during a training microcycle (2.2; Ellis et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), elite soccer players during an in-season training and competition microcycle (1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13; Brinkmans et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), but less than elite rugby league plays during an in-season training and competition microcycle (2.9; Morehen et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Consequently, this study reports a valid and accurate assessment of energy expenditure among elite male squash players during a training microcycle, in combination with a PAL value which can be utilised to devise squash specific nutritional recommendations.\u003c/p\u003e \u003cp\u003eEnergy availability is a well-established concept to support individuals\u0026rsquo; health and performance (Areta et al., 2021; Mountjoy et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Due to the high energy expenditure and PAL value experienced by players in the present study, players need to ensure that they are consuming enough energy to fuel their training. Mean energy intake among the three players over the 7-day microcycle was 3,389\u0026thinsp;\u0026plusmn;\u0026thinsp;981 Kcals, resulting in a mean daily energy balance of -821 Kcals. On an individual level, player one reported a mean daily energy balance of -2,392 Kcals\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and body mass reduction of 2.1 kg over the seven day microcycle; player two reported a mean daily energy balance of -542 Kcals\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and body mass increase of 0.8 kg over the seven day microcycle; and player three reported a mean daily energy balance of +\u0026thinsp;470 Kcals\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and body mass reduction of 0.5 kg over the seven day microcycle. Increases in body mass while in a negative energy balance such as in player two suggest there is likely to be an underreporting of energy intake, rather than undereating, a common phenomenon within nutritional science (Black et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Indeed, research in elite male soccer (Anderson et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Brinkmans et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and rugby league players (Morehen et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) all reported lower energy intakes than energy expenditures despite body mass remaining stable throughout the duration of the microcycles. Mean energy availability among the three players over the microcycle was 31.68\u0026thinsp;\u0026plusmn;\u0026thinsp;17.91 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. When reported individually, players two and three had an energy availability of 42.35 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 41.69 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e respectively, indicating reduced energy availability according to the International Olympic Committee\u0026rsquo;s Consensus Statement of Relative Energy Deficiency in Sport (Mountjoy et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Player one exhibited an energy balance of \u0026minus;\u0026thinsp;2,392 Kcals\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and energy availability of 11 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, indicating low energy availability according to the International Olympic Committee\u0026rsquo;s Consensus Statement of Relative Energy Deficiency in Sport (Mountjoy et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Low energy availability has many negative consequences on health and performance-based outcomes (Mountjoy et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, it is crucial appropriate nutrition strategies are devised to support optimal, health, wellbeing and performance. This study reports valid and accurate data to help support elite male squash players to adopt appropriate nutrition strategies and mitigate against low energy availability (see practical application section). A potential limitation of the study was that exercise energy expenditure, and subsequently energy availability was calculated through heart rate monitoring rather than the gold standard indirect calorimetry. Heart rate monitoring was shown to yield a non-significant (1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.2%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;0.05) mean underestimate of total energy expenditure in comparison to indirect calorimetry (Ceesay et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1989\u003c/span\u003e). Consequently, due to the nature of the study and inability to measure exercise energy expenditure through indirect calorimetry, heart rate monitoring was used to quantify expenditure. The Polar H10 band was selected, as this has been shown to have the greatest RR signal strength during high intensity activities and high correlation to an electrocardiography Holter monitor (Gilgen-Ammann et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSquash is a high intensity intermittent sport (Girard et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), and, therefore, carbohydrates play a key role in energy metabolism (Van Loon et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Previous research into the dietary habits of elite Spanish squash players has suggested that players under-consume carbohydrate rich foods such as bread, potatoes, pasta, and rice (Ventura-Comes et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Mean carbohydrate intake was 4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1 g\u0026sdot;kg\u0026sdot;bm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e among players, which highlights under-fuelling in comparison to non-specific sports nutrition carbohydrate guidelines (Burke et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Burke et al., (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) proposed a carbohydrate target intake of 6\u0026ndash;10 g\u0026sdot;kg\u0026sdot;bm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for individuals engaging in 1\u0026ndash;3 hours of high intensity activity per day. Low carbohydrate availability often occurs simultaneously with low energy availability (Logue et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Indeed, player one\u0026rsquo;s carbohydrate intake was a mean of 2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 g\u0026sdot;kg\u0026sdot;bm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e over the microcycle which is lower than non-specific guidelines (Burke et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Carbohydrate intake appears to be individualised with player two consuming 7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 g\u0026sdot;kg\u0026sdot;bm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and player three consuming 4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 g\u0026sdot;kg\u0026sdot;bm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Players\u0026rsquo; nutritional choices are highly individualised and based on a variety of different physiological, cultural, psychological, social, and economic factors (Birkenhead \u0026amp; Slater, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Nutrition knowledge is one of those factors which can influence the food choice of players (Birkenhead \u0026amp; Slater, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). To this extent, the data presented in this study aims to increase knowledge through increasing understanding of the energy expenditure of elite squash players throughout a microcycle, and as a result, the energy and carbohydrate requirements of elite squash players.\u003c/p\u003e \u003cp\u003ePeriodised nutrition is a well-established concept to ensure athletes fuel appropriately throughout variable training loads (Jeukendrup, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Elite squash players appear to have variable training loads with player one\u0026rsquo;s daily training duration, daily exercise energy expenditure, and daily sRPE ranging from 45 to 198 minutes, 589 to 2,309 Kcals and 180 to 1,395 respectively; players two\u0026rsquo;s ranging from 170 to 258 (daily training duration), 1,517 to 2,174 (daily exercise energy expenditure), and 1,040 to 1,798 (daily sRPE); and players three\u0026rsquo;s ranging from 133 to 215 (daily training duration), 1,176 to 1,848 (daily exercise energy expenditure), and 1,064 to 1,477 (daily sRPE). A limitation of the doubly labelled water technique is its inability to provide day to day energy expenditure assessments, hence energy expenditure being expressed over a 7-day microcycle in this study. It is likely that energy expenditure varied on a day-to-day basis and while nutritional recommendations can be devised to account for the energy expenditure over a microcycle, day to day recommendations may be appropriate to optimise training adaptation (Impey et al., 2017), body composition (Stellingwerf, 2019) and physical performance (Jeukendrup, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). There was some evidence of energy periodisation within the present study with player one\u0026rsquo;s energy intake varying from 1932 Kcals (daily sRPE\u0026thinsp;=\u0026thinsp;180) to 3306 Kcals (daily sRPE\u0026thinsp;=\u0026thinsp;1,395); player two\u0026rsquo;s energy intake varying from 2834 Kcals (daily sRPE\u0026thinsp;=\u0026thinsp;0) to 6,361 Kcals (daily sRPE\u0026thinsp;=\u0026thinsp;1,798); and player three\u0026rsquo;s energy intake varying from 2,499 Kcals (daily sRPE\u0026thinsp;=\u0026thinsp;0) to 4,421 Kcals (daily sRPE\u0026thinsp;=\u0026thinsp;1,191).\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePractical Applications\u003c/h2\u003e \u003cp\u003eThe present study demonstrates that elite male squash players exhibit a high energy expenditure throughout a training microcycle and follow inappropriate nutrition strategies such as sub optimal carbohydrate intake or in one case, severe energy restriction, leading to low energy availability. This may lead to a wide range of health and performance-based consequences (Mounjoy et al., 2023). One of the aims of the paper was to increase the understanding of the energy expenditure of elite male squash players throughout a microcycle, so that energy and carbohydrate guidelines can be devised. Consequently, for an 85 kg player (the mean of the three players body mass in this study) wanting to achieve energy balance, if protein intake was fixed at the suggested guidelines of 1.4 to 2 g\u0026sdot;kg\u0026sdot;bm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (119g to 170g; 476 Kcals to 680 Kcals; J\u0026auml;ger et al., 2018) and fat intake was fixed at 30% of total energy intake (1.6 g\u0026sdot;kg\u0026sdot;bm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; 140g; 1263 Kcals; Kerksick et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), carbohydrate intake should be between 2,267 and 2,471 Kcals (depending on the individuals protein intake), equating to 567 to 618 g or 6.6 to 7.2 g\u0026sdot;kg\u0026sdot;bm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of carbohydrate per day. The training load data suggests that elite male squash players have a varied training load, and therefore players should work with a registered sport dietitian or sports nutritionist to optimally periodise their energy and carbohydrate intake alongside their training load to maximise training adaptations and performance (Jeukendrup, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003cstrong\u003ecknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors at Sheffield Hallam University would like to thank Catherine Hambly and her team at the University of Aberdeen for collaborating on this study and advising on how to conduct the doubly labelled water technique as well as analysis of the samples. The authors would also like to thank England Squash and the elite male squash players who took part in the study, advancing scientific knowledge within the sport\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eO. Turner, M. Ranchordas N. Mitchell, A. Ruddock, A. Purvis and designed the study. O. Turner recruited players, undertook some of the data analysis with C. Hambly \u0026amp; J. Speakman carrying out analysis of the urine samples to determine total daily energy expenditure, O. Turner drafted the manuscript and oversaw manuscript preparation. M. Ranchordas, N. Mitchell, A. Ruddock and A. Purvis assisted with revising the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding was provided by Sheffield Hallam University and England Squash as part of O Turner\u0026rsquo;s PhD programme\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was approved by Sheffield Hallam University\u0026rsquo;s ethics committee (ER33101394)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll players provided informed consent prior to participating in the research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMost of the data generated or analysed during this study are included in this published article [and its supplementary information files] such as training load, energy expenditure and energy intake data\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAnderson, L., Orme, P., Naughton, R. J., Close, G. L., Milsom, J., Rydings, D., . . . Morton, J. P. (2017). Energy intake and expenditure of professional soccer players of the \u003cins cite=\"mailto:Alison%20Purvis\" datetime=\"2024-07-01T08:25\"\u003eE\u003c/ins\u003e nglish premier league: Evidence of carbohydrate periodization.\u003cem\u003e International Journal of Sport Nutrition and Exercise Metabolism, 27\u003c/em\u003e(3), 228-238. doi:10.1123/ijsnem.2016-0259\u003c/li\u003e\n\u003cli\u003eAnderson, L., Close, G. L., Morgans, R., Hambly, C., Speakman, J. R., Drust, B., \u0026amp; Morton, J. P. (2019). Assessment of energy expenditure of a professional goalkeeper from the \u003cins cite=\"mailto:Alison%20Purvis\" datetime=\"2024-07-01T08:26\"\u003eE\u003c/ins\u003e nglish premier league using the doubly labeled water method.\u003cem\u003e International Journal of Sports Physiology and Performance, 14\u003c/em\u003e(5), 1-684. doi:10.1123/ijspp.2018-0520\u003c/li\u003e\n\u003cli\u003eBerman, E. S. F., Fortson, S. L., Snaith, S. P., Gupta, M., Baer, D. S., Chery, I., . . . Speakman, J. R. (2012). Direct analysis of \u0026delta;2H and \u0026delta;18O in natural and enriched human urine using laser-based, off-axis integrated cavity output spectroscopy.\u003cem\u003e Analytical Chemistry, 84\u003c/em\u003e(22), 9768. doi:10.1021/ac3016642\u003c/li\u003e\n\u003cli\u003eBingham, S. A., Gill, C., Welch, A., Day, K., Cassidy, A., Khaw, K. T., . . . Day, N. E. (1994). Comparison of dietary assessment methods in nutritional epidemiology: Weighed records v. 24 h recalls, food-frequency questionnaires and estimated-diet records.\u003cem\u003e \u003c/em\u003e\u003cem\u003eBritish Journal of Nutrition; Br J Nutr, 72\u003c/em\u003e(4), 619-643. doi:10.1079/BJN19940064\u003c/li\u003e\n\u003cli\u003eBirkenhead, K. L., \u0026amp; Slater, G. (2015). 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(1998). \u003cem\u003eBorg\u0026apos;s perceived exertion and pain scales\u003c/em\u003e. Champaign, IL: Human Kinetics; pp 39-43\u003c/li\u003e\n\u003cli\u003eBrinkmans, N. Y. J., Iedema, N., Plasqui, G., Wouters, L., Saris, W. H. M., van Loon, L. J. C., \u0026amp; van Dijk, J. (2019). Energy expenditure and dietary intake in professional football players in the \u003cins cite=\"mailto:Alison%20Purvis\" datetime=\"2024-06-30T15:44\"\u003eD\u003c/ins\u003e utch premier league: Implications for nutritional counselling.\u003cem\u003e Journal of Sports Sciences, 37\u003c/em\u003e(24), 2759-2767. doi:10.1080/02640414.2019.1576256\u003c/li\u003e\n\u003cli\u003eBurke, L. M., Hawley, J. A., Wong, S. H. S., \u0026amp; Jeukendrup, A. E. (2011). Carbohydrates for training and competition.\u003cem\u003e Journal of Sports Sciences, 29\u003c/em\u003e, S17-S27. doi:10.1080/02640414.2011.585473\u003c/li\u003e\n\u003cli\u003eCeesay, S. M., Prentice, A. M., Day, K. C., Murgatroyd, P. R., Goldberg, G. 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R. (2017\u003cem\u003ea\u003c/em\u003e). Doubly labelled water assessment of energy expenditure: Principle, practice, and promise.\u003cem\u003e European Journal of Applied Physiology, 117\u003c/em\u003e(7), 1277-1285. doi:10.1007/s00421-017-3641-x\u003c/li\u003e\n\u003cli\u003eWesterterp, K. R. (2017\u003cem\u003eb\u003c/em\u003e). Control of energy expenditure in humans.\u003cem\u003e European Journal of Clinical Nutrition, 71\u003c/em\u003e(3), 340-344. doi:10.1038/ejcn.2016.237\u003c/li\u003e\n\u003cli\u003eWoods, A. L., Rice, A. J., Garvican-Lewis, L., Wallett, A. M., Lundy, B., Rogers, M. A., . . . Thompson, K. G. (2018). The effects of intensified training on resting metabolic rate (RMR), body composition and performance in trained cyclists.\u003cem\u003e PloS One, 13\u003c/em\u003e(2), e0191644. doi:10.1371/journal.pone.0191644\u003c/li\u003e\n\u003cli\u003eWorld Medical Association (2001). World Medical Association Declaration of Helsinki: Ethical principles for medical research involving human subjects.\u003cem\u003e World Health Organisation.\u003c/em\u003e, \u003cem\u003e79\u003c/em\u003e, 373\u0026ndash;374. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"performance-nutrition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Performance Nutrition](https://performancenutrition.biomedcentral.com/)","snPcode":"44410","submissionUrl":"https://submission.springernature.com/new-submission/44410/3","title":"Performance Nutrition","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6779000/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6779000/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNo previous research has quantified the energy balance of elite male squash players during a training microcycle. Consequently, the aim of this study was to concurrently quantify energy expenditure (EE), energy intake (EI) and energy availability (EA) among a cohort of elite male squash players to understand the energy balance of elite male squash players. Three elite male squash players were assessed during a 7-day training microcycle for TL (via heart rate monitoring, and sRPE), EE (via doubly labelled water technique), and EI (via weighed food method, Snap\u0026rsquo;N\u0026rsquo;Send photographic method, and 24-hour dietary recall). Mean daily EE was 4,210\u0026thinsp;\u0026plusmn;\u0026thinsp;1,017 Kcals, with mean daily EI being 3,389\u0026thinsp;\u0026plusmn;\u0026thinsp;981 Kcals, conveying a mean daily negative energy balance of 821 Kcals. Mean EA over the microcycle was 31.68\u0026thinsp;\u0026plusmn;\u0026thinsp;17.91 Kcal\u0026sdot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e FFM\u0026sdot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e indicating reduced EA. The study highlights that elite male squash players exhibit a high energy expenditure throughout a training microcycle and may follow poor nutrition strategies such as severe energy restriction, leading to low energy availability and sub optimal carbohydrate intake. These sub optimal nutritional practices may lead to reduced training performance and symptoms of relative energy deficiency in sport.\u003c/p\u003e","manuscriptTitle":"Doubly Labelled Water Assessment of Elite Male-Squash Player’s Energy Balance During a Seven-Day Training Microcycle","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-09 10:21:22","doi":"10.21203/rs.3.rs-6779000/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-01T10:18:33+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-23T13:20:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"313927892590067290010796796239762492223","date":"2025-09-23T12:13:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-07T13:36:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-04T18:27:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-20T21:50:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"34844949307515662844322622649734027811","date":"2025-07-16T14:44:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"153857345576404027421791420115980304020","date":"2025-07-08T11:40:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-03T14:46:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-30T04:47:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-30T04:47:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Performance Nutrition","date":"2025-05-29T19:03:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"performance-nutrition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Performance Nutrition](https://performancenutrition.biomedcentral.com/)","snPcode":"44410","submissionUrl":"https://submission.springernature.com/new-submission/44410/3","title":"Performance Nutrition","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f6396894-ef79-4794-8a20-daa63eb3a688","owner":[],"postedDate":"June 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2025-10-01T10:23:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-09 10:21:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6779000","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6779000","identity":"rs-6779000","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}