A Study on the Variations in Peripheral Vision and Reaction Performance among Indian Male Football Players of Different Competitive Levels

A Study on the Variations in Peripheral Vision and Reaction Performance among Indian Male Football Players of Different Competitive Levels | 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 Research Article A Study on the Variations in Peripheral Vision and Reaction Performance among Indian Male Football Players of Different Competitive Levels Rakesh Rajak, Noor Kalam Sekh, Dr. Anirban Misra, Chiranjit Malakar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7964038/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Peripheral vision and reaction ability are critical determinants of performance in elite football, yet comparative assessments between competitive levels remain limited in Indian football contexts. Purpose To compare peripheral vision and reaction ability between national-level (I-League) and state-level male football players using FITLIGHT® technology. And quantify the magnitude of performance differences to inform training program design. Methods Fifty-two male football players (26 I-League, 26 state-level) aged 19–44 years participated in this comparative cross-sectional study. Peripheral vision was measured by counting total taps in 30 seconds, and reaction ability was assessed through foot reaction time (in milliseconds) using the FITLIGHT system. Independent samples t-tests were conducted with a significance level of p < 0.05, and Cohen's d effect sizes were calculated using G*Power software. Results Comparing the foot reaction time, the National-level players had significantly superior times than the state-level players (388.0 ± 9.78ms vs. 461.8 ± 8.73ms; t = 28.7, p < .001, d = 7.87) and total tap count (77.5 ± 1.96 vs. 65.1 ± 1.16; t = -27.7, p < .001, d = 7.51). Effect sizes indicated a very large difference for both variables. Conclusion National-level football players had dominant peripheral vision and reaction abilities compared to state-level male Football players. These findings show the importance of visuocognitive training technologies in talent identification and development programs across all competitive levels. Peripheral Vision Reaction Time FITLIGHT Cognitive-Motor Performance Football Elite Athletes Visual Training Figures Figure 1 Figure 2 1. INTRODUCTION Football demands visuocognitive and physical integration. Modern football has evolved dynamically, where players need to execute complex visual tasks while executing rapid decision-making under pressure and adapting to unpredictable situations (Theofilou et al., 2022 ). The ability to detect multiple stimuli simultaneously—including arriving ball, teammates' positions, and opponent movements, which separates the elite performers from others. Peripheral vision, the capacity to detect visual information outside the direct line of vision, enables players to maintain spatial awareness across the entire field of play without moving their head or making eye movements (Badau et al., 2023 ). It has three types: far-peripheral (60–110°), mid-peripheral (30–60°), and near-peripheral (18–30°) vision. To effectively scan their surroundings and anticipate game situations, football players must adapt to Enhance their performance. This visual capacity operates through the peripheral retina, which contains photoreceptor cells (rods and cones) specialized for detecting motion and maintaining awareness in lower light conditions. Reaction ability, the speed and accuracy of motor responses to stimuli, represents another performance determinant element in football. Elite players have much sensorimotor integration, enabling faster stimulus-response to execute movements in gameplay situations (Hassan et al., 2022 ). The emergence of technology-based training systems, particularly FITLIGHT®, has provided objective, standardized methods for assessing and training these visuocognitive enhancements through these types of tools. Despite countless studies on physical conditioning parameters, the visuocognitive domain remains relatively underexplored in Indian football. The enlightenment of Indian football by the Indian Super League (ISL) in 2014 and the developing operations of the I-League have created a distinct competitive gap by using various upgraded training instruments, coaching expertise, and performance technologies. Understanding performance differences between these levels exposes the need for talent identification strategies and training program development. 1.1 Purpose of the Study This study aimed to compare peripheral vision and reaction ability between I-League (national-level) and state-level male football players using FITLIGHT® technology. Quantify the magnitude of performance differences to inform training program design. 2.1 Hypothesis H O : There will be no significant effect on peripheral vision between national-level and state-level male football players H A : There will be a significant effect on peripheral vision between national-level and state-level male football players H O : There will be no significant effect on Reaction time between national-level and state-level male football players H A : There will be a significant effect on reaction time between national-level and state-level male football players. 2. METHODOLOGY 2.1 Study Design This study adopted a comparative cross-sectional study design. 2.2 Sample Size Determination To determine our sample size, we used G*Power 3.1.9.4 software with parameters based on prior research (Ballmann & Rogers, 2024 ): Effect size (f) = 0.80 Alpha error probability = 0.05 Power (1-β) = 0.80 Number of groups = 2 The analysis told us we needed a minimum of 52 participants (26 per group). 2.3 Participants Inclusion Criteria : Male football players aged 19–44 years National level I-League players State-level players who competed in the Santosh Trophy Minimum competitive football experience of 5 years No musculoskeletal injuries within 6 months before testing Exclusion Criteria : ISL-level players (to maintain clear competitive level distinction) Players below state-level competition We recruited fifty-two male football players who met these criteria from various clubs in Kolkata, West Bengal, India. They were divided into two equal groups: 26 I-League (national-level) and 26 state-level players. 2.4 Instrumentation Anthropometric Measurements : Height : Measured using a stadiometer (accuracy: ±0.1 cm) Weight : Measured with a calibrated digital weighing scale (accuracy: ±0.1 kg) BMI : Calculated as weight(kg)/height²(m²) Performance Assessment : We used the FITLIGHT® Trainer™ System (FITLIGHT Corp., Ontario, Canada)—a wireless LED-based reaction training system controlled via Dynamic Eye software. For our setup, we arranged eight FITLIGHT® pods in a circular pattern at a 1.5-meter radius from the central standing position, placing them on the floor at approximately 90 cm height. 2.5 Testing Procedures Pre-Test Standardization : We wanted to make sure everything was consistent, so: All testing happened between 10:00–12:00 AM to minimize circadian rhythm effects Testing occurred in May with temperatures ranging from 26–40°C at an average humidity Participants were strictly advised to avoid intense exercise 24 hours before testing Everyone completed a standardized 10-minute dynamic warm-up protocol Anthropometric Assessment : Age : Verified by using the ADHAR CARD Height : stadiometer with participants standing barefoot Weight : Weighing machine BMI : Calculated from height and weight measurements FITLIGHT® Assessment Protocol : Before the actual testing began, participants completed three practice trials (each lasting 10 seconds) to minimize learning effects. We then gave them a 5-minute rest before the formal testing began. Test 1 - Peripheral Vision Assessment : Duration : 30 seconds Task : Deactivate randomly blinking FITLIGHT® pods using foot contact as fast as possible Lights : Activated sequentially in unpredictable spatial patterns across the 360° arc Measurement : Total successful taps (count) Trials : Single 30-second trial Test 2 - Reaction Time Assessment : Trials : 5 repetitions Task : Deactivate a single illuminated light pod as rapidly as possible using foot contact Measurement : Foot reaction time (milliseconds) from light activation to physical contact Scoring : Average reaction time calculated from all 5 trials Rest : 5-minute interval between tests 2.6 Reliability and Validity Instrument Reliability The FITLIGHT® system has already been validated as a reliable tool for reaction time assessment in athletic populations (Badau & Badau, 2022 ; Steff et al., 2024 ). We calibrated all equipment according to the manufacturer's specifications before starting data collection. Tester Competency All measurements were conducted by the primary investigator with assistance from trained personnel under the supervision of a certified sports and exercise scientist (C. Malakar). We established inter-rater reliability through preliminary testing with randomly selected participants aged 23–26 years. Test-Retest Reliability Our pilot testing confirmed acceptable test-retest reliability for both FITLIGHT® protocols (r > 0.85) 2.7 Statistical Analysis We analyzed all data using JAMOVI software (version 2.5.6, https://www.jamovi.org ). Descriptive statistics (mean ± standard deviation) were calculated for the variables. The Shapiro-Wilk test helped us to assess whether our data distribution was normal. We used independent samples t-tests to compare national-level and state-level players for each dependent variable, and calculated Cohen's d effect sizes to understand the magnitude of differences. Statistical significance was set at α = 0.05 (two-tailed) 3. RESULTS 3.1 Participant Characteristics Anthropometric characteristics of participants are presented in Table 1 . National-level players were slightly older and taller with higher body weight compared to state-level players, though BMI values were comparable between groups. Table 1 Descriptive Statistics of Anthropometric Characteristics Variable Group N Mean Median SD Shapiro-Wilk W Shapiro-Wilk p Age (years) State 26 21.0 21.0 ± 1.46 0.926 0.061 National 26 22.1 22.0 ± 1.70 0.869 0.003* Height (cm) State 26 170.0 170.0 ± 2.94 0.920 0.044* National 26 175.0 175.0 ± 2.80 0.940 0.136 Weight (kg) State 26 64.3 65.0 ± 3.73 0.905 0.020* National 26 67.8 68.0 ± 3.61 0.933 0.092 BMI (kg/m²) State 26 22.4 22.5 ± 1.48 0.966 0.523 National 26 22.2 22.4 ± 1.30 0.981 0.884 Note. *p < .05 indicates deviation from the normal distribution 3.2 Performance Variables Descriptive statistics for peripheral vision and reaction ability are presented in Table 2 . National-level players demonstrated substantially faster reaction times and higher tap counts compared to state-level players. Table 2 Descriptive Statistics of Performance Variables Variable Group N Mean SD SE Foot Reaction Time (ms) State 26 461.8 ± 8.73 1.713 National 26 388.0 ± 9.78 1.917 Total Taps (30s) State 26 65.1 ± 1.16 0.228 National 26 77.5 ± 1.96 0.385 Table 3 Normality Assessment for Performance Variables (Combined Groups) Variable Shapiro-Wilk W p-value Foot Reaction Time 0.975 0.351 Total Taps (30s) 0.978 0.447 Note. Both variables demonstrated normal distribution (p > .05) 3.3 Group Comparisons Independent samples t-tests revealed statistically significant differences between groups for both performance variables (Table 4 ). Table 4 Independent Samples t-Test Results Variable t-value df p-value Mean Difference 95% CI Cohen's d Foot Reaction Time 28.7 50 < .001*** -73.8ms [-78.62, -68.98] 7.87 Total Taps (30s) -27.7 50 < .001*** 12.4 taps [11.50, 13.30] 7.51 Note. ***p < .001; Negative t-value for Total Taps indicates the National group performed more taps Key Findings : Foot Reaction Time : National-level players demonstrated significantly faster reaction times (388.0 ± 9.78ms) compared to state-level players (461.8 ± 8.73ms), representing a 19% performance advantage. The effect size (d = 7.87) indicates a very large practical difference. Total Taps : National-level players completed significantly more taps (77.5 ± 1.96) than state-level players (65.1 ± 1.16) within the 30-second assessment period, representing a 19% performance advantage. The effect size (d = 7.51) indicates a very large practical difference. Both null hypotheses were rejected (p < .001), supporting the alternative hypothesis that significant performance differences exist between these two levels. 4. DISCUSSION This study shows significant results that national-level (I-League) football players have higher peripheral vision and reaction ability compared to state-level players, with exceptionally large effect sizes observed for both variables. These findings get support with theoretical frameworks that strengthen the role of perceptual-cognitive expertise in sport performance differentiation (Williams & Ford, 2008 ). 4.1 Peripheral Vision Performance The potentiality and efficiency in peripheral vision and reaction ability of the I-League players show 19% prominence over the state-level football players, and from previous research (Theofilou et al., 2022 ), it is supported, where superior visual field awareness in national and regional athletes was shown. Training Environment I-League players typically engage in more sophisticated training programs where they develop their visuocognitive performance through technologies such as FITLIGHT®, BlazePod, and designated peripheral awareness drills. Competitive Exposure Higher-level competition demands continuous monitoring of multiple visual stimuli simultaneously. The faster game tempo, more complex tactical situations, and superior opponent quality in I-League matches necessitate enhanced peripheral awareness for effective performance. 4.2 Reaction Ability Performance Among the performance of foot reaction time, the I-League players potentially represent a notable significance of 73.8ms in football contexts, where split-second responses determine successful outcomes. This finding aligns with previous studies where faster reaction times have been observed in national and regional athletes across various sports (Hassan et al., 2022 ; Steff et al., 2024 ). Cognitive-Motor Integration Elite players develop more efficient neural pathways linking visual perception to motor execution through upgraded practices and drills in game-like situations. This enhanced sensorimotor coupling reduces processing time between stimulus detection and response. Spatial Adaptation The transition from conscious to automatic processing through thousands of practice repetitions reduces cognitive load and accelerates response execution (Silvestri et al., 2023 ). Physical Conditioning Higher-level training programs typically focus on neuromuscular power development, which facilitates faster movement execution following stimulus detection. Technology-Based Training Greater access to reaction training technologies (FITLIGHT®, specialized agility systems) provides I-League players with more frequent opportunities for targeted reaction development through varied, unpredictable stimulus analysis (Campanella et al., 2024 ). 4.3 Practical Implications These findings have significant implications for multiple development in Indian football: Player Development Programs : Integrate systematic visual-cognitive training from early developmental stages Incorporate FITLIGHT® or similar technology-based reaction training in regular practice sessions Design position-specific visual training protocols Coaching implementation : Increase awareness of visual-cognitive factors contributing to performance excellence Emphasize the importance of creating practice environments more challenging For talent Identification processes 4.5 Limitations Study Design Limitations : A cross-sectional design prevents causal inferences about training effects Cannot distinguish innate abilities Study Sample Characteristics : Convenience sampling from the Kolkata region limits generalizability Study Measurement Considerations : Laboratory-based assessment may not perfectly represent game-relevant capabilities Study Contextual Factors : Training history, tactical knowledge, and playing position data were not analyzed Nutritional status and recent training load were not controlled No assessment of transfer effects on actual match performance 4.6 Future Research Directions To build upon these findings, future research should: Longitudinal Investigations could be done Using instruments like EEG, fMRI to examine underlying neural mechanisms Utilize eye-tracking technology to assess visual scanning strategies Examine position-specific differences in visuocognitive demands and capabilities 5. CONCLUSION This study elaborates that national-level (I-League) football players got significantly superior peripheral vision and reaction ability compared to state-level players, with very large effect sizes indicating substantial practical differences. I-League players completed more peripheral vision taps and faster reaction times, reflecting the benefits of advanced training environments, greater competitive exposure, superior coaching, and enhanced technologies. These findings strengthen the critical importance of visuocognitive abilities in differentiating performance levels in football. The result of observed differences suggests that systematic integration of visuocognitive training technologies (FITLIGHT®, BlazePod) and peripheral awareness drills into grassroots and state-level development programs represents a high-priority intervention for detecting and developing performance gaps and optimizing talent development for Indian football. Coaches, administrators, and sport scientists should recognize that developing complete players requires balanced attention to physical, technical, tactical, and visuocognitive domains. Investing in training technologies and coaching education that focus on perceptual-cognitive skill development may yield substantial returns in player performance and competitive success. Declarations Ethical approval and informed consent This study was conducted in accordance with the ethical standards of the institutional research committee, and ethical approval was obtained from the institutional ethics committee of the Department of Physical Education, The University of Burdwan. All participants were informed about the nature and purpose of the study, and consent was collected from the participants before their participation. Conflict of interest The authors declared no conflicts of interest related to this research. Funding This research received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author contributions All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Rakesh Rajak, Noor Kalam Sekh, Dr. Anirban Misra, and Chiranjit Malakar. The first draft of the manuscript was written by Rakesh Rajak, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgments The authors thank all participating football players and coaching staff from various clubs in Kolkata, West Bengal, for their cooperation during the data collection process. We acknowledge the assistance of training personnel who supported the testing procedures. Data availability The data supporting the findings of this study are available from the corresponding author upon reasonable request. 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Res Q Exerc Sport 69(2):111–128. https://doi.org/10.1080/02701367.1998.10607677 Williams AM, Ford PR (2008) Expertise and expert performance in sport. Int Rev Sport Exerc Psychol 1(1):4–18. https://doi.org/10.1080/17509840701836867 Additional Declarations The authors declare potential competing interests as follows: Noor Kalam Sekh, 2Department of Physical Education and Sports Science, Visva-Bharati, Santiniketan, West Bengal, India Dr. Anirban Misra, Department of Physical Education, UCTC Behampore, Murshidabad, India Chiranjit Malakar, Independent Sports and Exercise Scientist, West Bengal, India The authors declared no conflicts of interest related to this research. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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2","display":"","copyAsset":false,"role":"figure","size":128992,"visible":true,"origin":"","legend":"\u003cp\u003eUnnumbered image in the Results section.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7964038/v1/fd406083f3c18ec9077c71f7.png"},{"id":94641094,"identity":"9e85ca72-32fe-4a37-83b7-3df59f6e07bb","added_by":"auto","created_at":"2025-10-29 07:51:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1286847,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7964038/v1/1b3f1b11-1e20-4c68-a6c8-1992fd119947.pdf"}],"financialInterests":"The authors declare potential competing interests as follows: Noor Kalam Sekh, 2Department of Physical Education and Sports Science, Visva-Bharati, Santiniketan, West Bengal, India\nDr. Anirban Misra, Department of Physical Education, UCTC Behampore, Murshidabad, India\nChiranjit Malakar, Independent Sports and Exercise Scientist, West Bengal, India\n\n- The authors declared no conflicts of interest related to this research.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eA Study on the Variations in Peripheral Vision and Reaction Performance among Indian Male Football Players of Different Competitive Levels\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eFootball demands visuocognitive and physical integration. Modern football has evolved dynamically, where players need to execute complex visual tasks while executing rapid decision-making under pressure and adapting to unpredictable situations (Theofilou et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). The ability to detect multiple stimuli simultaneously\u0026mdash;including arriving ball, teammates' positions, and opponent movements, which separates the elite performers from others.\u003c/p\u003e\n\u003cp\u003ePeripheral vision, the capacity to detect visual information outside the direct line of vision, enables players to maintain spatial awareness across the entire field of play without moving their head or making eye movements (Badau et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). It has three types: far-peripheral (60\u0026ndash;110\u0026deg;), mid-peripheral (30\u0026ndash;60\u0026deg;), and near-peripheral (18\u0026ndash;30\u0026deg;) vision. To effectively scan their surroundings and anticipate game situations, football players must adapt to\u003c/p\u003e\n\u003cp\u003eEnhance their performance. This visual capacity operates through the peripheral retina, which contains photoreceptor cells (rods and cones) specialized for detecting motion and maintaining awareness in lower light conditions.\u003c/p\u003e\n\u003cp\u003eReaction ability, the speed and accuracy of motor responses to stimuli, represents another performance determinant element in football. Elite players have much sensorimotor integration, enabling faster stimulus-response to execute movements in gameplay situations (Hassan et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). The emergence of technology-based training systems, particularly FITLIGHT\u0026reg;, has provided objective, standardized methods for assessing and training these visuocognitive enhancements through these types of tools.\u003c/p\u003e\n\u003cp\u003eDespite countless studies on physical conditioning parameters, the visuocognitive domain remains relatively underexplored in Indian football. The enlightenment of Indian football by the Indian Super League (ISL) in 2014 and the developing operations of the I-League have created a distinct competitive gap by using various upgraded training instruments, coaching expertise, and performance technologies. Understanding performance differences between these levels exposes the need for talent identification strategies and training program development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.1 Purpose of the Study\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003e\n\u003cp\u003eThis study aimed to compare peripheral vision and reaction ability between I-League (national-level) and state-level male football players using FITLIGHT\u0026reg; technology.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eQuantify the magnitude of performance differences to inform training program design.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\n\u003ch2\u003e2.1 Hypothesis\u003c/h2\u003e\n\u003cp\u003eH\u003csub\u003eO\u003c/sub\u003e: There will be no significant effect on peripheral vision between national-level and state-level male football players\u003c/p\u003e\n\u003cp\u003eH\u003csub\u003eA\u003c/sub\u003e: There will be a significant effect on peripheral vision between national-level and state-level male football players\u003c/p\u003e\n\u003cp\u003eH\u003csub\u003eO\u003c/sub\u003e: There will be no significant effect on Reaction time between national-level and state-level male football players\u003c/p\u003e\n\u003cp\u003eH\u003csub\u003eA\u003c/sub\u003e: There will be a significant effect on reaction time between national-level and state-level male football players.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"2. METHODOLOGY","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Design\u003c/h2\u003e\u003cp\u003eThis study adopted a comparative cross-sectional study design.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Sample Size Determination\u003c/h2\u003e\u003cp\u003eTo determine our sample size, we used G*Power 3.1.9.4 software with parameters based on prior research (Ballmann \u0026amp; Rogers, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e):\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eEffect size (f)\u0026thinsp;=\u0026thinsp;0.80\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eAlpha error probability\u0026thinsp;=\u0026thinsp;0.05\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePower (1-β)\u0026thinsp;=\u0026thinsp;0.80\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eNumber of groups\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThe analysis told us we needed a minimum of 52 participants (26 per group).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Participants\u003c/h2\u003e\u003cp\u003e\u003cb\u003eInclusion Criteria\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eMale football players aged 19\u0026ndash;44 years\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eNational level I-League players\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eState-level players who competed in the Santosh Trophy\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eMinimum competitive football experience of 5 years\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eNo musculoskeletal injuries within 6 months before testing\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eExclusion Criteria\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eISL-level players (to maintain clear competitive level distinction)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ePlayers below state-level competition\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eWe recruited fifty-two male football players who met these criteria from various clubs in Kolkata, West Bengal, India. They were divided into two equal groups: 26 I-League (national-level) and 26 state-level players.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Instrumentation\u003c/h2\u003e\u003cp\u003e\u003cb\u003eAnthropometric Measurements\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eHeight\u003c/b\u003e: Measured using a stadiometer (accuracy: \u0026plusmn;0.1 cm)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eWeight\u003c/b\u003e: Measured with a calibrated digital weighing scale (accuracy: \u0026plusmn;0.1 kg)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e: Calculated as weight(kg)/height\u0026sup2;(m\u0026sup2;)\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePerformance Assessment\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eWe used the \u003cb\u003eFITLIGHT\u0026reg; Trainer\u0026trade; System\u003c/b\u003e (FITLIGHT Corp., Ontario, Canada)\u0026mdash;a wireless LED-based reaction training system controlled via Dynamic Eye software.\u003c/p\u003e\u003cp\u003eFor our setup, we arranged eight FITLIGHT\u0026reg; pods in a circular pattern at a 1.5-meter radius from the central standing position, placing them on the floor at approximately 90 cm height.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Testing Procedures\u003c/h2\u003e\u003cp\u003e\u003cb\u003ePre-Test Standardization\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eWe wanted to make sure everything was consistent, so:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eAll testing happened between 10:00\u0026ndash;12:00 AM to minimize circadian rhythm effects\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTesting occurred in May with temperatures ranging from 26\u0026ndash;40\u0026deg;C at an average humidity\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eParticipants were strictly advised to avoid intense exercise 24 hours before testing\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eEveryone completed a standardized 10-minute dynamic warm-up protocol\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eAnthropometric Assessment\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e: Verified by using the ADHAR CARD\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eHeight\u003c/b\u003e: stadiometer with participants standing barefoot\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eWeight\u003c/b\u003e: Weighing machine\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e: Calculated from height and weight measurements\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFITLIGHT\u0026reg; Assessment Protocol\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eBefore the actual testing began, participants completed three practice trials (each lasting 10 seconds) to minimize learning effects. We then gave them a 5-minute rest before the formal testing began.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTest 1 - Peripheral Vision Assessment\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eDuration\u003c/b\u003e: 30 seconds\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eTask\u003c/b\u003e: Deactivate randomly blinking FITLIGHT\u0026reg; pods using foot contact as fast as possible\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eLights\u003c/b\u003e: Activated sequentially in unpredictable spatial patterns across the 360\u0026deg; arc\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eMeasurement\u003c/b\u003e: Total successful taps (count)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eTrials\u003c/b\u003e: Single 30-second trial\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eTest 2 - Reaction Time Assessment\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eTrials\u003c/b\u003e: 5 repetitions\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eTask\u003c/b\u003e: Deactivate a single illuminated light pod as rapidly as possible using foot contact\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eMeasurement\u003c/b\u003e: Foot reaction time (milliseconds) from light activation to physical contact\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eScoring\u003c/b\u003e: Average reaction time calculated from all 5 trials\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eRest\u003c/b\u003e: 5-minute interval between tests\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Reliability and Validity\u003c/h2\u003e\u003cp\u003e\u003cstrong\u003eInstrument Reliability\u003c/strong\u003e\u003cp\u003eThe FITLIGHT\u0026reg; system has already been validated as a reliable tool for reaction time assessment in athletic populations (Badau \u0026amp; Badau, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Steff et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). We calibrated all equipment according to the manufacturer's specifications before starting data collection.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTester Competency\u003c/strong\u003e\u003cp\u003eAll measurements were conducted by the primary investigator with assistance from trained personnel under the supervision of a certified sports and exercise scientist (C. Malakar). We established inter-rater reliability through preliminary testing with randomly selected participants aged 23\u0026ndash;26 years.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTest-Retest Reliability\u003c/strong\u003e\u003cp\u003eOur pilot testing confirmed acceptable test-retest reliability for both FITLIGHT\u0026reg; protocols (r\u0026thinsp;\u0026gt;\u0026thinsp;0.85)\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Statistical Analysis\u003c/h2\u003e\u003cp\u003eWe analyzed all data using JAMOVI software (version 2.5.6, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.jamovi.org\u003c/span\u003e\u003cspan address=\"https://www.jamovi.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Descriptive statistics (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation) were calculated for the variables. The Shapiro-Wilk test helped us to assess whether our data distribution was normal. We used independent samples t-tests to compare national-level and state-level players for each dependent variable, and calculated Cohen's d effect sizes to understand the magnitude of differences. Statistical significance was set at α\u0026thinsp;=\u0026thinsp;0.05 (two-tailed)\u003c/p\u003e\u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Participant Characteristics\u003c/h2\u003e\u003cp\u003eAnthropometric characteristics of participants are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. National-level players were slightly older and taller with higher body weight compared to state-level players, though BMI values were comparable between groups.\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\u003eDescriptive Statistics of Anthropometric 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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMedian\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eShapiro-Wilk W\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eShapiro-Wilk p\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\u003eAge (years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eState\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e21.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.926\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNational\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e22.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;1.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.869\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.003*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHeight (cm)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eState\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e170.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e170.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;2.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.920\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.044*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNational\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e175.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e175.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;2.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.940\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.136\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWeight (kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eState\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e64.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e65.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;3.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.905\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.020*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNational\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e67.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e68.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;3.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.933\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.092\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI (kg/m\u0026sup2;)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eState\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e22.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.966\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.523\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNational\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e22.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.981\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.884\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eNote.\u003c/em\u003e *p\u0026thinsp;\u0026lt;\u0026thinsp;.05 indicates deviation from the normal distribution\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\u003e3.2 Performance Variables\u003c/h2\u003e\u003cp\u003eDescriptive statistics for peripheral vision and reaction ability are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. National-level players demonstrated substantially faster reaction times and higher tap counts compared to state-level 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\u003eDescriptive Statistics of Performance Variables\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=\".\" 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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSE\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\u003eFoot Reaction Time (ms)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eState\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e461.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;8.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.713\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNational\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e388.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;9.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.917\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eTotal Taps (30s)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eState\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e65.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.228\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNational\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e77.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;1.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.385\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\u003e\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\u003eNormality Assessment for Performance Variables (Combined Groups)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\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=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eShapiro-Wilk W\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-value\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\u003eFoot Reaction Time\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.975\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.351\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal Taps (30s)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.978\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.447\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003eNote.\u003c/em\u003e Both variables demonstrated normal distribution (p\u0026thinsp;\u0026gt;\u0026thinsp;.05)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Group Comparisons\u003c/h2\u003e\u003cp\u003eIndependent samples t-tests revealed statistically significant differences between groups for both performance variables (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\u003eIndependent Samples t-Test Results\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\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=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003et-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMean Difference\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eCohen's d\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\u003eFoot Reaction Time\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-73.8ms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e[-78.62, -68.98]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e7.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal Taps (30s)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-27.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12.4 taps\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e[11.50, 13.30]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e7.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eNote.\u003c/em\u003e ***p\u0026thinsp;\u0026lt;\u0026thinsp;.001; Negative t-value for Total Taps indicates the National group performed more taps\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eKey Findings\u003c/strong\u003e:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eFoot Reaction Time\u003c/b\u003e: National-level players demonstrated significantly faster reaction times (388.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.78ms) compared to state-level players (461.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.73ms), representing a 19% performance advantage. The effect size (d\u0026thinsp;=\u0026thinsp;7.87) indicates a very large practical difference.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eTotal Taps\u003c/b\u003e: National-level players completed significantly more taps (77.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96) than state-level players (65.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.16) within the 30-second assessment period, representing a 19% performance advantage. The effect size (d\u0026thinsp;=\u0026thinsp;7.51) indicates a very large practical difference.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eBoth null hypotheses were rejected (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), supporting the alternative hypothesis that significant performance differences exist between these two levels.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThis study shows significant results that national-level (I-League) football players have higher peripheral vision and reaction ability compared to state-level players, with exceptionally large effect sizes observed for both variables. These findings get support with theoretical frameworks that strengthen the role of perceptual-cognitive expertise in sport performance differentiation (Williams \u0026amp; Ford, \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n\u003ch2\u003e4.1 Peripheral Vision Performance\u003c/h2\u003e\n\u003cp\u003eThe potentiality and efficiency in peripheral vision and reaction ability of the I-League players show 19% prominence over the state-level football players, and from previous research (Theofilou et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), it is supported, where superior visual field awareness in national and regional athletes was shown.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTraining Environment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI-League players typically engage in more sophisticated training programs where they develop their visuocognitive performance through technologies such as FITLIGHT\u0026reg;, BlazePod, and designated peripheral awareness drills.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompetitive Exposure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHigher-level competition demands continuous monitoring of multiple visual stimuli simultaneously. The faster game tempo, more complex tactical situations, and superior opponent quality in I-League matches necessitate enhanced peripheral awareness for effective performance.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n\u003ch2\u003e4.2 Reaction Ability Performance\u003c/h2\u003e\n\u003cp\u003eAmong the performance of foot reaction time, the I-League players potentially represent a notable significance of 73.8ms in football contexts, where split-second responses determine successful outcomes. This finding aligns with previous studies where faster reaction times have been observed in national and regional athletes across various sports (Hassan et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e; Steff et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCognitive-Motor Integration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eElite players develop more efficient neural pathways linking visual perception to motor execution through upgraded practices and drills in game-like situations. This enhanced sensorimotor coupling reduces processing time between stimulus detection and response.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSpatial Adaptation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe transition from conscious to automatic processing through thousands of practice repetitions reduces cognitive load and accelerates response execution (Silvestri et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhysical Conditioning\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHigher-level training programs typically focus on neuromuscular power development, which facilitates faster movement execution following stimulus detection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTechnology-Based Training\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGreater access to reaction training technologies (FITLIGHT\u0026reg;, specialized agility systems) provides I-League players with more frequent opportunities for targeted reaction development through varied, unpredictable stimulus analysis (Campanella et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n\u003ch2\u003e4.3 Practical Implications\u003c/h2\u003e\n\u003cp\u003eThese findings have significant implications for multiple development in Indian football:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlayer Development Programs\u003c/strong\u003e:\u003c/p\u003e\n\u003col style=\"list-style-type: upper-roman;\"\u003e\n\u003cli\u003e\n\u003cp\u003eIntegrate systematic visual-cognitive training from early developmental stages\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eIncorporate FITLIGHT\u0026reg; or similar technology-based reaction training in regular practice sessions\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eDesign position-specific visual training protocols\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eCoaching implementation\u003c/strong\u003e:\u003c/p\u003e\n\u003col style=\"list-style-type: upper-roman;\"\u003e\n\u003cli\u003e\n\u003cp\u003eIncrease awareness of visual-cognitive factors contributing to performance excellence\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eEmphasize the importance of creating practice environments more challenging\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eFor talent Identification processes\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n\u003ch2\u003e4.5 Limitations\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Design Limitations\u003c/strong\u003e:\u003c/p\u003e\n\u003col style=\"list-style-type: upper-roman;\"\u003e\n\u003cli\u003e\n\u003cp\u003eA cross-sectional design prevents causal inferences about training effects\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eCannot distinguish innate abilities\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Sample Characteristics\u003c/strong\u003e:\u003c/p\u003e\n\u003col style=\"list-style-type: upper-roman;\"\u003e\n\u003cli\u003e\n\u003cp\u003eConvenience sampling from the Kolkata region limits generalizability\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Measurement Considerations\u003c/strong\u003e:\u003c/p\u003e\n\u003col style=\"list-style-type: upper-roman;\"\u003e\n\u003cli\u003e\n\u003cp\u003eLaboratory-based assessment may not perfectly represent game-relevant capabilities\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Contextual Factors\u003c/strong\u003e:\u003c/p\u003e\n\u003col style=\"list-style-type: upper-roman;\"\u003e\n\u003cli\u003e\n\u003cp\u003eTraining history, tactical knowledge, and playing position data were not analyzed\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eNutritional status and recent training load were not controlled\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eNo assessment of transfer effects on actual match performance\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n\u003ch2\u003e4.6 Future Research Directions\u003c/h2\u003e\n\u003cp\u003eTo build upon these findings, future research should:\u003c/p\u003e\n\u003col style=\"list-style-type: upper-roman;\"\u003e\n\u003cli\u003e\n\u003cp\u003eLongitudinal Investigations could be done\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eUsing instruments like EEG, fMRI to examine underlying neural mechanisms\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eUtilize eye-tracking technology to assess visual scanning strategies\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eExamine position-specific differences in visuocognitive demands and capabilities\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003c/div\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eThis study elaborates that national-level (I-League) football players got significantly superior peripheral vision and reaction ability compared to state-level players, with very large effect sizes indicating substantial practical differences. I-League players completed more peripheral vision taps and faster reaction times, reflecting the benefits of advanced training environments, greater competitive exposure, superior coaching, and enhanced technologies.\u003c/p\u003e\u003cp\u003eThese findings strengthen the critical importance of visuocognitive abilities in differentiating performance levels in football. The result of observed differences suggests that systematic integration of visuocognitive training technologies (FITLIGHT\u0026reg;, BlazePod) and peripheral awareness drills into grassroots and state-level development programs represents a high-priority intervention for detecting and developing performance gaps and optimizing talent development for Indian football.\u003c/p\u003e\u003cp\u003eCoaches, administrators, and sport scientists should recognize that developing complete players requires balanced attention to physical, technical, tactical, and visuocognitive domains. Investing in training technologies and coaching education that focus on perceptual-cognitive skill development may yield substantial returns in player performance and competitive success.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eand informed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical standards of the institutional research committee, and ethical approval was obtained from the institutional ethics committee of the Department of Physical Education, The University of Burdwan. All participants were informed about the nature and purpose of the study, and consent was collected from the participants before their participation.\u003c/p\u003e\u003cp\u003e\u003ch2\u003eConflict of interest\u003c/h2\u003e\u003cp\u003eThe authors declared no conflicts of interest related to this research.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Rakesh Rajak, Noor Kalam Sekh, Dr. Anirban Misra, and Chiranjit Malakar. The first draft of the manuscript was written by Rakesh Rajak, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThe authors thank all participating football players and coaching staff from various clubs in Kolkata, West Bengal, for their cooperation during the data collection process. We acknowledge the assistance of training personnel who supported the testing procedures.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e\u003cp\u003eThe data supporting the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBadau D, Badau A (2022) Optimizing reaction time in relation to manual and foot laterality in children using the Fitlight technological systems. Sensors 22(22):8785. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/s22228785\u003c/span\u003e\u003cspan address=\"10.3390/s22228785\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBadau D, Badau A, Ene-Voiculescu C, Larion A, Ene-Voiculescu V, Mihaila I, Fleancu JL, Tudor V, Tifrea C, Cotovanu AS, Abramiuc A (2022) The impact of implementing an exergame program on the level of reaction time optimization in handball, volleyball, and basketball players. Int J Environ Res Public Health 19(9):5598. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph19095598\u003c/span\u003e\u003cspan address=\"10.3390/ijerph19095598\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBadau D, Stoica AM, Litoi MF, Badau A, Duta D, Hantau CG, Sabau AM, Oancea BM, Ciocan CV, Fleancu JL, Gozu B (2023) The impact of peripheral vision on manual reaction time using Fitlight technology for handball, basketball, and volleyball players. 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Int Rev Sport Exerc Psychol 1(1):4\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/17509840701836867\u003c/span\u003e\u003cspan address=\"10.1080/17509840701836867\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Burdwan","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Peripheral Vision, Reaction Time, FITLIGHT, Cognitive-Motor Performance, Football, Elite Athletes, Visual Training","lastPublishedDoi":"10.21203/rs.3.rs-7964038/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7964038/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003ePeripheral vision and reaction ability are critical determinants of performance in elite football, yet comparative assessments between competitive levels remain limited in Indian football contexts.\u003c/p\u003e\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eTo compare peripheral vision and reaction ability between national-level (I-League) and state-level male football players using FITLIGHT\u0026reg; technology. And quantify the magnitude of performance differences to inform training program design.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eFifty-two male football players (26 I-League, 26 state-level) aged 19\u0026ndash;44 years participated in this comparative cross-sectional study. Peripheral vision was measured by counting total taps in 30 seconds, and reaction ability was assessed through foot reaction time (in milliseconds) using the FITLIGHT system. Independent samples t-tests were conducted with a significance level of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and Cohen's d effect sizes were calculated using G*Power software.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eComparing the foot reaction time, the National-level players had significantly superior times than the state-level players (388.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.78ms vs. 461.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.73ms; t\u0026thinsp;=\u0026thinsp;28.7, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, d\u0026thinsp;=\u0026thinsp;7.87) and total tap count (77.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96 vs. 65.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.16; t = -27.7, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, d\u0026thinsp;=\u0026thinsp;7.51). Effect sizes indicated a very large difference for both variables.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eNational-level football players had dominant peripheral vision and reaction abilities compared to state-level male Football players. These findings show the importance of visuocognitive training technologies in talent identification and development programs across all competitive levels.\u003c/p\u003e","manuscriptTitle":"A Study on the Variations in Peripheral Vision and Reaction Performance among Indian Male Football Players of Different Competitive Levels","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-29 05:17:17","doi":"10.21203/rs.3.rs-7964038/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e2de8e5b-c89f-4a04-bec0-68a26a00b6b3","owner":[],"postedDate":"October 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-29T05:17:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-29 05:17:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7964038","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7964038","identity":"rs-7964038","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}