{"paper_id":"3d3043e9-f288-464e-b97a-d79c63dffbc6","body_text":"Performance after Anterior Cruciate Ligament Reconstruction in Major League Baseball Fielders | 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 Performance after Anterior Cruciate Ligament Reconstruction in Major League Baseball Fielders Po-Chun Chi, Min-Hao Sun, Yu-Che Lee, Cheng-Pang Yang, Joe Chih-Hao Chiu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9413563/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Objectives: To evaluate performance changes in Major League Baseball (MLB) fielders following anterior cruciate ligament reconstruction (ACLR) using advanced Statcast metrics related to baserunning, defense, and batting. Design: Retrospective, case-control study Methods: MLB fielders who underwent ACLR between 2015 and 2023 were identified through official MLB injury reports. Players with at least 100 plate appearances (PA) before and after surgery were included. A 1:2 matched control group was established based on position, batting stance, and pre-injury performance. Performance metrics were analyzed across baserunning (e.g., sprint speed, extra bases taken), defense (e.g., Ultimate Zone Rating, Defensive Runs Saved), and batting (e.g., On-base Plus Slugging, Weighted Runs Created Plus). Statistical analyses compared pre- and post-injury metrics within the study group and against controls. Results: Fourteen fielders met the inclusion criteria and were matched to 28 control players. Post-ACLR, the study group exhibited significant declines in sprint speed (-0.55 ft/sec, p = 0.04), extra bases taken (-0.34, p = 0.03), and Defensive Runs Saved (-3.93, p = 0.04). No significant differences were observed in batting metrics. The control group showed no comparable performance declines. Conclusion: ACLR negatively impacts baserunning and defensive performance in MLB fielders, particularly in speed-related and agility-dependent metrics. However, batting metrics remained stable, suggesting a limited association with offensive performance impairment. These findings highlight the need for rehabilitation strategies that focus on mobility and defensive agility post-ACLR. baseball anterior cruciate ligament reconstruction Major League Baseball athletic performance metrics Figures Figure 1 Figure 2 Introduction Injury to the anterior cruciate ligament (ACL) is a common sports-related injury that significantly impacts athletic performance, primarily by restricting knee mobility. 14 , 35 Additionally, it impacts vertical jump ability due to reduced knee stability and power generation, 37 limiting explosive force production. 21 Besides, since the ACL restricts varus and valgus stress and regulates rotational movements, 5 ACL injuries destabilize the knee, impairing its ability to handle sudden directional changes. This instability hinders agility by reducing control over lateral and twisting movements, both essential for rapid acceleration, deceleration, and pivoting. Currently, Anterior cruciate ligament reconstruction (ACLR) is the primary treatment for athletes who aiming to return to competition. 30 However, post-ACLR, athletes often struggle to regain pre-injury performance levels due to persistent quadriceps weakness, 11,36 altered movement patterns, 4,31,33 and reduced knee function, 22 with these issues often lasting up to two years despite rehabilitation. In baseball, lower extremity injuries, including ACL injuries, are less common than elbow and shoulder injuries. 9 , 20 However, they significantly impact game performance. 9 , 34 A study conducted by Stan Conte revealed that over an 11-year period in Major League Baseball (MLB), knee injuries contributed to 7.3% of all injured list days. 7 Furthermore, from 2011 to 2014, knee injuries had an incidence rate of 1.2 per 1,000 athlete-exposures, resulting in an average of 16.2 missed days per injury, accumulating over 30,000 total missed days. Approximately 12% of knee injuries required surgical intervention, and non-contact mechanisms, such as base-running, contributed to 44% of these injuries, with base-runners being the most frequently injured group. 8 Beyond performance limitations, knee injuries pose a significant financial burden. From 1998 to 2015, the annual cost of placing MLB players on the injured list averaged $ 423 million, totaling over $ 7.6 billion. While specific cost breakdowns for knee injuries were not provided, given that knee injuries comprised 9.8% of injured list placements, their economic impact is also substantial. 6 A study on ACL injuries in MLB revealed that they were more prevalent in infielders (32%) and outfielders (32%) than in pitchers (29%), particularly during fielding (68%) and base-running (29%). 10 Additionally, Fabricant et al. reported that 88% of MLB players returned to at least 30 games post-ACLR, though they experienced a 21.2% decline in games played. The study also found that the extent of batting decline was influenced by whether the injury affected the rear or lead batting leg, whereas stolen base success rates remained unaffected. 15 While previous studies have examined return-to-play rates and traditional performance metrics post-ACLR, 15 there is limited research utilizing advanced statistical analyses to assess its impact on performance. This study aims to address this gap by analyzing advanced performance metrics in MLB fielders before and after ACLR, comparing them with uninjured players of similar anthropometric characteristics and fielding positions. We hypothesize that fielders undergoing ACLR will demonstrate significant declines in performance metrics, concerning baserunning, fielding, and batting, compared to uninjured controls. Methods Study Cohort This study was reported in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines to improve transparency and reproducibility. We performed a retrospective case-control study on MLB fielders who underwent ACLR between January 1, 2015, and December 31, 2023. The inclusion of this date range was based on the availability of Statcast data. 26 Utilizing the MLB's official injured list and website (MLB.com), 25 we compiled a comprehensive dataset of MLB fielders who had ACLR during this period. We also conducted a rigorous cross-referencing process using multiple publicly available and reputable sources. These included Baseball-Reference, 1 Fangraphs, 2 and official team announcements. Each identified case of ACL reconstruction was verified through at least two independent sources to ensure the accuracy of injury status and surgery timing. This approach is consistent with prior peer-reviewed studies examining professional athlete injuries using public data. 13 , 23 We clearly defined eligibility criteria a priori: fielders with > 100 plate appearances (PA) in the season prior to ACLR (\"index year\") and those with > 100 PA after successful return to MLB post-ACLR (\"post-reconstruction year\", PRY). Players undergoing revision surgeries were excluded. Control Group A matched 1:2 control group was established, consisting of MLB fielders without a history of ACLR. Control players were selected from the same MLB season (calendar year) in which the corresponding case sustained the ACL injury (incident density sampling). Matching criteria included identical defensive position, batting side, an age difference within three years, and the closest Fangraph Wins Above Replacement (fWAR) value in the same index year. By ensuring that controls were active MLB players in the same season as their matched case, this design inherently controlled for seasonal variations, league-wide trends, and rule or equipment changes that could influence performance metrics. Additionally, the players were also required to have a minimum of 100 PA in the selected season to qualify as matched controls. Once the most suitable candidate was identified, a discreet review of the player’s public injury records was conducted to confirm the absence of ACLR history. The rationale for 1:2 matching was to improve statistical efficiency and balance key covariates across groups. This pair-matched group was incorporated to evaluate potential year-to-year changes in base-running, batting, and defensive parameters, accounting for statistical or measurement variations. Data curation Anthropometric characteristics were collected, including age at surgery, body mass index (BMI), height, weight, batting sides, and defensive positions. The defensive positions were defined as the positions that the players played the most during the specific season. Injury-related data, such as the date of ACLR and the date of return to competition at the MLB level, were also recorded. Basic and advanced performance data were sourced from the Statcast system. For the study group, data were collected for two distinct periods: the index year and the post-reconstruction year (PRY), which was defined as the season in which the player returned to MLB with at least 100 PA. Corresponding data for the control group covering the same periods as their study group counterparts was also collected. Data sources were publicly available, and data collection procedures were standardized. No imputation was applied. Annual performance metrics for both the study group and the control group were recorded. The metrics could be divided into three categories: baserunning, defensive, and batting. As for baserunning metrics, the variables tracked included Ultimate Base Running (UBR), Extra Bases Taken (XBR), Weighted Stolen Bases (wSB), Base Running Score (BSR), sprint speed, and the time from home plate to first base (HP-to-1B). UBR quantifies a player’s ability to advance on the basepaths outside of stolen bases, measuring decision-making and aggressiveness in taking extra bases on balls in play. XBR reflects the percentage of times a runner advances more than one base on a single or more than two bases on a double, showcasing their ability to capitalize on opportunities. The wSB evaluates a player’s stolen base contributions relative to league averages, accounting for both success rate and volume to assess overall value. BSR, a composite metric, integrates UBR, wSB, and other baserunning components to provide a comprehensive measure of a player’s overall effectiveness. These metrics collectively evaluate a player's efficiency and effectiveness on the bases, capturing their ability to take extra bases, steal bases, and their overall speed and agility. In terms of defensive metrics, Ultimate Zone Rating (UZR) and Defensive Runs Saved (DRS) were used to measure each player's defensive contributions. UZR quantifies a player's fielding ability in terms of runs saved or cost in their specific fielding zone, while DRS provides a more comprehensive look at the number of runs a player saved or cost their team due to their defensive play across all fielding opportunities. For batting performance, the study analyzed a range of metrics including On-base Plus Slugging (OPS), which combines on-base percentage (OBP) and slugging percentage (SLG) to measure a player's offensive contribution, assessing their ability to get on base and hit for power. Weighted Runs Created Plus (wRC+) adjusts a player's offensive value to account for park effects and the current offensive environment, with 100 being league average, values above 100 as above-average, and below 100 as below-average. Maximum Exit Velocity (Max-EV) and Average Exit Velocity (Avg-EV) measure the speed of the baseball off the bat, indicative of hitting power. Barrel Percentage (Barrel%) and Barrels per Plate Appearance (Brls/PA) highlight a player’s ability to make optimal contact with the ball, leading to more productive outcomes such as extra-base hits. All definitions and metric computations were consistent with Fangraphs glossary and Statcast documentation. These metrics provide a thorough analysis of player performance, offering insights into their speed, defensive capabilities, and hitting prowess, which are essential for evaluating their overall impact on the game. If any key performance metric was missing, the player was then excluded from the study group. These variables were initially analyzed between the study group and the control group. Subsequently, the yearly changes from the index year to PRY in these variables were further examined between the two groups. Statistical Analysis Residual distributions were evaluated for normality using the Kolmogorov-Smirnov test to determine the appropriateness of parametric versus nonparametric tests. The Mann-Whitney U test and Wilcoxon signed-rank test were applied for nonparametric data, while independent and paired t-tests were used for parametric data to evaluate the between-group differences. Pearson's correlation coefficient was employed to analyze relationships between variables in a continuous fashion. A P value less than 0.05 was considered to indicate statistical significance. A post hoc power analysis was conducted to evaluate the statistical power of the observed significant findings. For each variable, effect sizes were estimated by dividing the reported mean difference by the pooled standard deviation, yielding Cohen’s d . A two-tailed two-sample t -test framework was used for power estimation with a significance level of 0.05. All statistical analyses were conducted using SPSS Statistics for Mac, version 25.0.0 (IBM Corp., Armonk, NY, USA). Results Player Characteristics Of the 27 MLB players who underwent ACLR from 2015 to 2023, 3 were excluded due to their roles as pitchers. Additionally, 8 players were excluded for not meeting our inclusion criteria of a successful return to competition (RTC). Two players excluded due to a lack of comprehensive performance data. Eventually, 14 fielders were identified for the analysis. After finalizing this process, the control group was established in a 1:2 matched fashion. Following a discreet screening process, no players were excluded from the control group after their initial selection. A flow diagram of the study cohort is presented in Figure 1. Player characteristics are presented in Table 1. As for anthropometric data, there was no significant difference between the study group and the control group. Table 1 Player Characteristics Variables Study group (n = 14) Control group (n = 28) P value PA, n 346.6 ± 200.0 231.6 ± 173.2 0.07 Index age, years old 27.3 ± 2.9 27.2 ± 3.0 0.94 Height, cm 183.9 ± 5.5 183.0 ± 5.3 0.6 Weight, kg 92.8 ± 9.1 91.4 ± 8.7 0.62 Body mass index, kg/m 2 27.4 ± 1.9 27.3 ± 1.9 0.82 RH:LH, n 8:6 16:12 0.98 Surgery year, n 2015 2 2016 1 2017 2 2018 1 2019 2 2020 0 2021 2 2022 4 Abbreviation: PA, plate appearance; RH, right side hitter; LH, left side hitter. Base Running The yearly base running performance data are presented in Table 2A, while the yearly changes are detailed in Table 2B. No significant differences were observed in any parameter during the index year or PRY. However, yearly changes revealed significant differences in both XBR and sprint speed between the study and control groups. Specifically, the study group demonstrated a significant decrease in XBR compared to the control group (-0.34 ± 0.84 vs. 0.53 ± 1.29; P = 0.03) and a significant reduction in sprint speed (-0.55 ± 0.45 vs. -0.27 ± 0.48; P = 0.04). Table 2 Player Baserunning Data Variables Study group (n = 28) Control group (n = 14) P value Index year UBR 0.53 ± 1.17 0.12 ± 1.92 0.47 XBR 0.27 ± 1.11 -0.28 ± 1.4 0.24 wSB -0.17 ± 0.36 -0.20 ± 0.70 0.87 BSR 0.26 ± 1.39 -0.23 ± 1.91 0.4 Sprint speed, feet per second 27.53 ± 1.77 27.22 ± 1.10 0.49 HP-to-1B, second 4.33 ± 0.29 4.42 ± 0.17 0.23 Post-reconstruction year UBR -0.02 ± 1.66 0.36 ± 1.20 0.40 XBR -0.11 ± 1.43 0.29 ± 0.68 0.22 wSB 0.11 ± 0.56 -0.19 ± 0.91 0.27 BSR -0.04 ± 1.61 0.08 ± 1.01 0.77 Sprint speed, feet per second 27.05 ± 1.71 26.95 ± 1.23 0.83 HP-to-1B, second 4.45 ± 0.23 4.45 ± 0.19 0.97 Yearly changes UBR -0.55 ± 1.54 0.24 ± 1.88 0.18 *XBR -0.34 ± 0.84 0.53 ± 1.29 0.03 wSB 0.28 ± 0.54 0.01 ± 0.71 0.22 BSR -0.3 ± 0.96 0.31 ± 1.47 0.17 *Sprint speed, feet per second -0.55 ± 0.45 -0.27 ± 0.48 0.04 HP-to-1B, second 0.14 ± 1.83 0.03 ± 0.07 0.76 Abbreviation: UBR, ultimate base running; XBR, extra base running; wSB, weighted stolen base runs; BSR, base running runs; HP-to-1B, the average time needed to run from home plate to first base. Defensive Metrics Table 3 summarizes the yearly performance and yearly changes in defensive metrics. The study group exhibited significantly poorer performance in DRS following ACLR, as indicated by both the overall yearly performance (PRY: -2.79 ± 3.53 vs. -0.04 ± 3.45; P = 0.02) and the yearly change (ΔDRS: -3.93 ± 4.76 vs. -1.36 ± 6.37; P = 0.04). In contrast, no significant differences were observed in UZR metrics across all measured parameters. Table 3 Defensive Metrics Variable Study group (n = 28) Control group (n = 14) P value Index year UZR 1.05 ± 3.28 0.84 ± 4.61 0.88 DRS 1.14 ± 3.28 1.32 ± 6.81 0.93 Post-reconstruction year UZR -1.14 ± 2.25 0.24 ± 2.69 0.12 *DRS -2.79 ± 3.53 -0.04 ± 3.45 0.02 Yearly changes UZR -2.04 ± 4.11 -0.56 ± 3.62 0.24 *DRS -3.93 ± 4.76 -1.36 ± 6.37 0.04 Abbreviation: UZR, ultimate zone rating; DRS, defensive runs saved Batting Performance Batting performance was assessed using advanced data, such as wRC+, WAR, Barrel% and so on. The data were summarized in Tables 4A and 4B. As for yearly performance and changes of the batting performance, there was no significant difference in all the aspects considering batting performance between study group and control group. Table 4 Player Batting Performance Data Variable Study group (n = 28) Control group (n = 14) P value Index year OPS 0.77 ± 0.13 0.71 ± 0.13 0.13 wRC+ 108.36 ± 33.72 90.46 ± 32.82 0.11 fWAR 1.14 ± 1.31 0.91 ± 0.92 0.51 bWAR 1.14 ± 1.29 1.11 ± 1.41 0.92 MAX_EV 110.25 ± 3.47 109.51 ± 3.81 0.54 Avg_EV 88.84 ± 3.05 87.68 ± 2.53 0.20 Barrel% 6.67 ± 5.37 6.17 ± 3.62 0.72 Brls/PA 4.31 ± 3.18 4.09 ± 2.35 0.80 Post-reconstruction year OPS 0.7 ± 0.12 0.67 ± 0.13 0.40 wRC+ 90.52 ± 33.79 86.68 ± 27.52 0.70 fWAR 0.67 ± 1.21 0.69 ± 1.17 0.97 bWAR 0.54 ± 1.21 0.61 ± 1.23 0.87 MAX_EV 109.86 ± 4.02 109.39 ± 3.81 0.71 Avg_EV 89.01 ± 1.52 87.21 ± 2.76 0.08 Barrel% 7.78 ± 4.05 5.54 ± 3.91 0.09 Brls/PA 5.14 ± 2.47 3.77 ± 2.38 0.09 Yearly changes OPS -0.04 ± 0.16 -0.06 ± 0.12 0.54 wRC+ -3.79 ± 34.13 -17.86 ± 31.27 0.2 fWAR -0.23 ± 1.34 -0.47 ± 1.37 0.59 bWAR -0.49 ± 1.62 -0.6 ± 1.42 0.82 MAX_EV -0.12 ± 2.85 -0.39 ± 2.89 0.78 Avg_EV -0.44 ± 2.29 0.17 ± 2.39 0.43 Barrel% -0.64 ± 3.11 1.11 ± 3.17 0.1 Brls/PA -0.32 ± 1.87 0.83 ± 1.82 0.07 Abbreviation: OPS, on-base plus slugging; wRC+, weighted runs created plus; fWAR, Fangraphs wins above replacement; bWAR, Baseball-Reference wins above replacement; MAX_EV, maximum exit velocity; Avg_EV, average exit velocity; Barrel%, percentage of batted balls classified as \"barrels\"; Brls/PA, barrels per plate appearance. Power Analysis To assess the robustness of our statistically significant findings, a post hoc power analysis was conducted for sprint speed, XBR, and DRS. Using Cohen’s d as the effect size and assuming two-tailed independent samples t -tests at a significance level of 0.05 with 14 participants per group, the following results were obtained: For sprint speed, the observed mean difference was 0.55 ft/sec with a standard deviation of 0.45, yielding a large standardized difference (Cohen’s d = 1.22). The calculated statistical power was 0.98, indicating a high probability of detecting a true difference. For XBR, the mean difference was 0.87 with a standard deviation of 0.84, yielding a moderate standardized difference ( d = 0.40). The corresponding power was 0.36, suggesting a relatively low likelihood of reliably detecting the observed difference with the given sample size. For DRS, the mean difference was 3.93 runs with a standard deviation of 4.76, resulting in a standardized difference of d = 0.83. This corresponded to a power of 0.73, indicating a moderate-to-high probability of detecting this difference. (Figure 2) Discussion Among the 27 MLB fielders identified with ACL reconstruction, only 19 (70%) achieved a meaningful return to play, defined in our study as recording at least 100 plate appearances in the post-reconstruction season. This relatively strict threshold ensures that only players with sufficient playing time are analyzed, thereby increasing the reliability of performance comparisons. Notably, nearly 30% failed to meet this benchmark, underscoring the challenge of returning to consistent participation at the MLB level following ACLR. Among those who returned, we assessed post-ACLR performance in baserunning, defense, and batting using advanced metrics. The analysis revealed significant declines in sprint speed, XBR, and defensive runs saved DRS, suggesting an association with reduced baserunning efficiency and defensive effectiveness. In contrast, batting metrics showed no significant differences, suggesting that offensive performance remained stable despite mobility and defensive limitations. The decline in baserunning performance observed in this study aligns with findings from previous research, emphasizing the significant impact of ACLR on agility and mobility. In our analysis, MLB fielders who underwent ACLR exhibited a notable decrease in sprint speed and XBR compared to the control group. Sprint speed reflects a player's maximum running velocity, providing a direct assessment of explosive speed critical for successful baserunning. Similarly, XBR quantifies a player's ability to take extra bases on hits, integrating speed, decision-making, and agility into a comprehensive measure of baserunning efficiency. This is consistent with the study by Erickson et al., 12 which highlighted a general reduction in baserunning performance among professional baseball players following ACL reconstruction, as reflected by fewer stolen base attempts and slower base-to-base times. Such declines underscore the critical role of lower limb stability and strength in executing quick, dynamic movements required for baserunning. These findings are further supported by Dugas et al., who reported that ACL injuries in baseball players predominantly affect activities such as fielding and baserunning, where sudden accelerations and directional changes are frequent. 10 This highlights the unique demands of baserunning in baseball, requiring rapid bursts of speed and precise maneuvering, both of which are compromised by ACL injuries. The observed deficits in our study corroborate these findings, suggesting that ACL injuries not only reduce physical performance but also impair the execution of sport-specific skills essential for competitive play. To better understand these deficits, it is necessary to examine the underlying mechanisms by which ACL injuries impair lower limb stability and strength. Damage to the ligament reduces its ability to stabilize the knee joint during rapid movements, resulting in increased joint laxity and a higher risk of instability during dynamic activities. 28 Additionally, ACL injuries often lead to atrophy in the quadriceps and hamstring muscles due to disuse and postoperative recovery periods, further impairing the muscle strength required for explosive force generation. 18 Proprioceptive deficits caused by disrupted neuromuscular signaling also contribute to decreased coordination and balance, which are essential for maintaining control during sudden accelerations and directional changes. 3 Together, these mechanisms provide a comprehensive explanation for the observed baserunning performance deficits in MLB players post-ACLR. As for the defensive performance, this study also identified significant declines in DRS among MLB fielders following ACLR, while UZR remained stable. DRS is a metric that quantifies a player's ability to save runs for their team through exceptional defensive plays, incorporating factors such as range, arm strength, and playmaking ability. 29 In contrast, UZR evaluates a player's defensive effectiveness within their designated fielding zone, focusing more on positioning and routine play execution. 27 From a statistical standpoint, DRS applies stricter criteria in evaluating defensive performance, whereas UZR offers a more lenient approach. Previous studies on ACL injuries have largely emphasized overall performance metrics or return-to-sport rates, with relatively little attention given to their association with defensive performance. Our results address this gap by offering novel insights into the defensive challenges faced by MLB fielders’ post-reconstruction. The decline in DRS suggests that ACL injuries impact the dynamic aspects of defense, such as chasing down balls or making quick adjustments, which require agility and lower limb stability. Research indicates that ACL injuries impair neuromuscular control and proprioception, 3 leading to decreased knee stability and compromised athletic performance. For instance, a study by Gokeler et al. found that athletes with ACLR exhibited deficits in dynamic stability during high-demand tasks, which are critical for effective defensive play. 19 Additionally, Paterno et al. reported that altered movement patterns post-ACL injury increase the risk of re-injury, further impacting an athlete's ability to perform dynamic defensive maneuvers. 32 Conversely, the stability of UZR likely reflects the preservation of fundamental defensive skills, such as positioning and routine decision-making, which rely less on explosive movements. In summary, our findings indicate that a decline in defensive performance among fielders following ACLR does exist, but the extent of the decline is minimal. As a result, significant differences are only observed in DRS, which employs a more stringent scoring method. These findings underscore the importance of tailored rehabilitation programs focusing on dynamic defensive abilities to mitigate the impact of ACL injuries on fielding performance. This study revealed no significant differences in batting performance metrics between MLB fielders who underwent ACLR and the control group. Metrics such as OPS, wRC+, and Max-EV remained comparable in the PRY. These findings align with prior research indicating that ACLR has a limited impact on static and skill-based offensive activities. For example, Fabricant et al. observed that ACLR had minimal impact on the ability of professional baseball players to return to their pre-injury offensive performance levels. 15 They emphasized that batting performance relies more on skill and precision than the lower limb explosiveness required for baserunning or fielding. Similarly, Mai et al. 24 reported that performance outcomes after ACLR vary by sports, with baseball showing minimal declines in skill-based activities like batting. They also highlighted that baseball's reliance on static and precision-driven skills, rather than dynamic lower limb explosiveness, likely contributes to this resilience. The biomechanics study of the baseball swing by Fortenbaugh et al. differs from our findings, as he emphasized that ground reaction forces generated by the lower limbs play a crucial role in driving the kinetic chain for successful batting performance. The authors identified the transfer of energy from the lower body to the bat through precise coordination and timing as essential for generating optimal bat speed and ball exit velocity. 16 However, although ACL injuries may affect lower limb stability, the stability of batting performance observed in this study was not impacted by the injury. This implies that batting success relies more on upper body coordination and precise timing, with less dependence on the dynamic lower limb strength affected by ACL injuries. Building on this, further research into knee mechanics during baseball swings highlights distinct roles for the front and back knees. The front knee’s mechanics resemble exercises in early-stage ACL rehabilitation, potentially enabling earlier return to hitting and helping maintain offensive consistency. In contrast, the back knee’s higher rotary demands suggest a delayed initiation in rehabilitation, which may affect dynamic aspects of hitting, such as generating power and bat speed. Interestingly, slight trends toward improved Barrel% and Barrels/PA observed in our study, though not statistically significant, suggest upper body coordination and precise timing may compensate for deficits in lower limb contributions. These insights reinforce the notion that while the kinetic chain remains vital for successful batting, its reliance on lower limb strength and stability is less critical than previously assumed, particularly for ACL-injured players. Tailored rehabilitation programs addressing the specific demands of the front and back knees can further optimize recovery and ensure a balance between stability, power generation, and timing for effective batting performance. 17 Limitation There were some limitations to the current study. First, this study is the relatively small sample size, with 14 ACL-injured players and 28 matched controls. This may be attributed to several reasons. First, the prevalence of ACL reconstruction in MLB fielders is relatively low compared to other surgeries, such as ulnar collateral ligament reconstruction in pitchers. Second, our strict inclusion criteria contributed to the limited sample size, as we only included players who successfully returned to competition and accumulated a sufficient number of plate appearances (PA) postoperatively. While this ensured clean data, it may have excluded players who failed to return—possibly due to lasting functional deficits. These cases highlight another potential consequence of ACL injury worth future study. Lastly, our study window was restricted to 2015–2023 due to the availability of Statcast data, which was first introduced in 2015. Although matching on key covariates—such as defensive position, batting side, age, and fWAR within the same season—helped reduce inter-individual variability and enhance statistical efficiency, the power to detect small-to-moderate effects may still have been limited. Based on preliminary power calculations using observed effect sizes, certain outcomes (e.g., sprint speed) reached acceptable statistical power, while others (e.g., XBR) did not. This suggests that while large differences could be reliably detected, the study may have been underpowered to identify subtler performance changes. Future studies with larger cohorts and extended sampling periods are warranted to validate these findings and improve generalizability. Another limitation of the study was that we obtained information solely from publicly available resources, as we lacked access to operative reports or medical records. Consequently, we could not acquire surgery-related details such as graft types, reconstruction methods, post-operative complications, and rehabilitation programs. This limitation made it impossible to determine surgery-related factors affecting post-ACLR performance. Third, this study included only MLB-level players. This selection was due to the completeness of advanced performance metrics, which are only publicly accessible in the MLB-level database. However, this restriction limited the study cohort, meaning our results may not be broadly applicable to other levels, including Minor League Baseball players. Lastly, in this study, we aimed to utilize advanced performance metrics in baserunning, batting, and fielding to provide the most objective evaluation of players' performance. However, determining the best indicators for evaluating performance in each category remains challenging. With advancements in in-field tracking technologies, computational algorithms, and data analysis, more refined performance metrics will hopefully become available in the near future, enabling more accurate assessments. Conclusion This study examined the impact of ACLR on MLB fielders’ performance, focusing on baserunning, defense, and batting. The results showed that players experienced a decline in baserunning speed and defensive effectiveness while their batting performance remained largely unchanged. This indicated that ACLR appears to affect movement-based aspects of the game more than skill-based ones. These findings highlight the importance of rehabilitation programs that focus on restoring speed, agility, and defensive mobility. Further research with larger sample sizes and longer follow-ups is needed to better understand the long-term associations between ACL reconstruction and baseball performance and to refine recovery strategies. Practical Implications MLB fielders who undergo ACL reconstruction may experience notable declines in baserunning and defensive performance, particularly in speed- and agility-dependent tasks, even after successful return to play. Batting performance tends to remain stable post-ACLR, suggesting that offensive skills may be less affected than mobility-based defensive contributions. Postoperative rehabilitation should emphasize mobility, agility, and lower extremity stability, with a focus on sprinting, directional changes, and field coverage. Team decision-makers should consider the potential long-term impact on baserunning and fielding—not just batting—when evaluating the post-ACLR readiness and contract value of field players. These findings provide data-driven insight to guide individualized return-to-play protocols and long-term management strategies in professional baseball. Declarations Human Ethics and Consent to Participate: Not applicable. This study analysed publicly available, de-identified data from MLB.com and publicly accessible baseball analytics platforms (Statcast/Baseball Savant, FanGraphs, and Baseball-Reference). No human participants were recruited, no direct contact or intervention occurred, and no identifiable private information was collected; therefore, ethics approval and informed consent to participate were not applicable . Ethics Approval declaration: Not applicable. This study analysed publicly available, de-identified data and did not involve direct contact with human participants or identifiable private information; therefore, review by the Institutional Review Board of Linkou Chang Gung Memorial Hospital was not required. Funding Declaration: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author Contribution Po-Chun Chi and Min-Hao Sun contributed equally to this work and share first authorship.Po-Chun Chi, Min-Hao Sun and Yu-Che Lee collected the data and performed the analyses.Po-Chun Chi drafted the manuscript.Min-Hao Sun, Joe Chih-Hao Chiu, Yi-Lu, and Cheng-Pang Yang critically revised the manuscript for important intellectual content.Yi-Lu supervised the study.All authors reviewed and approved the final manuscript. Acknowledgement The authors would like to express their gratitude to the Department of Orthopedic Surgery at Chang Gung Memorial Hospital for their support throughout the course of this study. We also thank Dr. Joe Chih-Hao Chiu for valuable insights into the methodology and Dr. Cheng-Pang Yang, for assistance with data handling and statistical analysis. The authors also acknowledge the contributions of Dr. Yi-Sheng Chan and Dr Yi Lu, who assisted with manuscript proofreading and language editing. Data Availability The study analysed publicly available data from the following sources:1. Dataset title: MLB Statcast (player running, hitting, and sprint speed metrics; seasons 2015–2023)Repository name: Baseball Savant (Statcast), Major League Baseball Advanced MediaPersistent identifier: https://baseballsavant.mlb.com/2. Dataset title: FanGraphs Advanced Metrics (including UBR, XBR, wSB, BSR, wRC+, fWAR; seasons 2015–2023)Repository name: FanGraphsPersistent identifier: https://www.fangraphs.com/3. Dataset title: Baseball-Reference Player Statistics (player-level seasonal statistics and demographics used for cross-referencing)Repository name: Baseball-ReferencePersistent identifier: https://www.baseball-reference.com/4. Dataset title: MLB Injury/Transaction Information (injured list reports and related injury/surgery timing used for case identification and verification)Repository name: MLB.comPersistent identifier: https://www.mlb.com/No new clinical or patient-level datasets were generated for this study. The curated dataset compiled from the above public sources (including the list of included players and extracted season-level metrics used for analysis) can be made available from the corresponding author upon reasonable request. References Baseball-Reference. https://wwwbaseball-referencecom/ . Fangraphs. https://wwwfangraphscom/ . Arumugam A, Björklund M, Mikko S, Häger CK. Effects of neuromuscular training on knee proprioception in individuals with anterior cruciate ligament injury: a systematic review and GRADE evidence synthesis. BMJ Open. 2021;11(5):e049226. Castanharo R, da Luz BS, Bitar AC, et al. Males still have limb asymmetries in multijoint movement tasks more than 2 years following anterior cruciate ligament reconstruction. J Orthop Sci. 2011;16(5):531-535. Chhabra A, Starman JS, Ferretti M, et al. Anatomic, radiographic, biomechanical, and kinematic evaluation of the anterior cruciate ligament and its two functional bundles. J Bone Joint Surg Am. 2006;88 Suppl 4:2-10. Conte S, Camp CL, Dines JS. Injury Trends in Major League Baseball Over 18 Seasons: 1998-2015. Am J Orthop (Belle Mead NJ). 2016;45(3):116-123. Conte S, Requa RK, Garrick JG. Disability days in major league baseball. Am J Sports Med. 2001;29(4):431-436. Dahm DL, Curriero FC, Camp CL, et al. Epidemiology and Impact of Knee Injuries in Major and Minor League Baseball Players. Am J Orthop (Belle Mead NJ). 2016;45(3):E54-62. Dick R, Sauers EL, Agel J, et al. Descriptive epidemiology of collegiate men's baseball injuries: National Collegiate Athletic Association Injury Surveillance System, 1988-1989 through 2003-2004. J Athl Train. 2007;42(2):183-193. Dugas JR, Bedford BB, Andrachuk JS, et al. Anterior Cruciate Ligament Injuries in Baseball Players. Arthroscopy. 2016;32(11):2278-2284. Eitzen I, Holm I, Risberg MA. Preoperative quadriceps strength is a significant predictor of knee function two years after anterior cruciate ligament reconstruction. Br J Sports Med. 2009;43(5):371-376. Erickson BJ, Chalmers PN, D'Angelo J, et al. Performance and Return to Sport After Anterior Cruciate Ligament Reconstruction in Professional Baseball Players. Orthop J Sports Med. 2019;7(10):2325967119878431. Erickson BJ, Harris JD, Cvetanovich GL, et al. Performance and Return to Sport After Anterior Cruciate Ligament Reconstruction in Male Major League Soccer Players. Orthop J Sports Med. 2013;1(2):2325967113497189. Evans J, Mabrouk A, Nielson JL. Anterior Cruciate Ligament Knee Injury. In: StatPearls. Treasure Island (FL): StatPearls Publishing Copyright © 2024, StatPearls Publishing LLC.; 2024. Fabricant PD, Chin CS, Conte S, et al. Return to play after anterior cruciate ligament reconstruction in major league baseball athletes. Arthroscopy. 2015;31(5):896-900. Fortenbaugh DM. The Biomechanics of the Baseball Swing. In: Asfour S, Abdelrahman K, Latta L, Onar-Thomas A, Fleisig G, eds. A dissertation at the University of Miami. . 2011. Giordano K, Chaput M, Anz A, et al. Knee Kinetics in Baseball Hitting and Return to Play after ACL Reconstruction. Int J Sports Med. 2021;42(9):847-852. Girdwood M, Culvenor AG, Rio EK, et al. Tale of quadriceps and hamstring muscle strength after ACL reconstruction: a systematic review with longitudinal and multivariate meta-analysis. Br J Sports Med. 2024. Gokeler A, Benjaminse A, Hewett TE, et al. Proprioceptive deficits after ACL injury: are they clinically relevant? Br J Sports Med. 2012;46(3):180-192. Ingram JG, Fields SK, Yard EE, Comstock RD. Epidemiology of knee injuries among boys and girls in US high school athletics. Am J Sports Med. 2008;36(6):1116-1122. Legnani C, Del Re M, Viganò M, et al. Relationships between Jumping Performance and Psychological Readiness to Return to Sport 6 Months Following Anterior Cruciate Ligament Reconstruction: A Cross-Sectional Study. J Clin Med. 2023;12(2). Logerstedt D, Lynch A, Axe MJ, Snyder-Mackler L. Symmetry restoration and functional recovery before and after anterior cruciate ligament reconstruction. Knee Surg Sports Traumatol Arthrosc. 2013;21(4):859-868. Lu Y, Chen P, Sheu H, et al. Fastball Quality After Ulnar Collateral Ligament Reconstruction in Major League Baseball Pitchers. Am J Sports Med. 2024;52(10):2611-2619. Mai HT, Chun DS, Schneider AD, et al. Performance-Based Outcomes After Anterior Cruciate Ligament Reconstruction in Professional Athletes Differ Between Sports. Am J Sports Med. 2017;45(10):2226-2232. Major League Baseball. MLB.com. Major League Baseball. Statcast. June 9,2021. Mangine GT, Hoffman JR, Vazquez J, et al. Predictors of fielding performance in professional baseball players. Int J Sports Physiol Perform. 2013;8(5):510-516. Migliorini F, Vecchio G, Eschweiler J, et al. Reduced knee laxity and failure rate following anterior cruciate ligament reconstruction compared with repair for acute tears: a meta-analysis. J Orthop Traumatol. 2023;24(1):8. Mizels J, Erickson B, Chalmers P. Current State of Data and Analytics Research in Baseball. Curr Rev Musculoskelet Med. 2022;15(4):283-290. Myklebust G, Bahr R. Return to play guidelines after anterior cruciate ligament surgery. Br J Sports Med. 2005;39(3):127-131. Paterno MV, Ford KR, Myer GD, Heyl R, Hewett TE. Limb asymmetries in landing and jumping 2 years following anterior cruciate ligament reconstruction. Clin J Sport Med. 2007;17(4):258-262. Paterno MV, Rauh MJ, Schmitt LC, Ford KR, Hewett TE. Incidence of contralateral and ipsilateral anterior cruciate ligament (ACL) injury after primary ACL reconstruction and return to sport. Clin J Sport Med. 2012;22(2):116-121. Paterno MV, Schmitt LC, Ford KR, et al. Biomechanical measures during landing and postural stability predict second anterior cruciate ligament injury after anterior cruciate ligament reconstruction and return to sport. Am J Sports Med. 2010;38(10):1968-1978. Powell JW, Barber-Foss KD. Injury patterns in selected high school sports: a review of the 1995-1997 seasons. J Athl Train. 1999;34(3):277-284. Renström PA. Eight clinical conundrums relating to anterior cruciate ligament (ACL) injury in sport: recent evidence and a personal reflection. Br J Sports Med. 2013;47(6):367-372. Schmitt LC, Paterno MV, Hewett TE. The impact of quadriceps femoris strength asymmetry on functional performance at return to sport following anterior cruciate ligament reconstruction. J Orthop Sports Phys Ther. 2012;42(9):750-759. Ventura A, Iori S, Legnani C, et al. Single-bundle versus double-bundle anterior cruciate ligament reconstruction: assessment with vertical jump test. Arthroscopy. 2013;29(7):1201-1210. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 18 May, 2026 Reviewers agreed at journal 28 Apr, 2026 Reviewers invited by journal 28 Apr, 2026 Editor assigned by journal 18 Apr, 2026 Submission checks completed at journal 18 Apr, 2026 First submitted to journal 14 Apr, 2026 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-9413563\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":634024522,\"identity\":\"d0e73944-52e5-4db8-943f-1a8e052e13f6\",\"order_by\":0,\"name\":\"Po-Chun Chi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Linkou Chang Gung Memorial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Po-Chun\",\"middleName\":\"\",\"lastName\":\"Chi\",\"suffix\":\"\"},{\"id\":634024523,\"identity\":\"12b44b4f-0cf8-4154-9f8f-6246699266c5\",\"order_by\":1,\"name\":\"Min-Hao Sun\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Linkou Chang Gung Memorial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Min-Hao\",\"middleName\":\"\",\"lastName\":\"Sun\",\"suffix\":\"\"},{\"id\":634024524,\"identity\":\"8d1bec98-1d1e-4886-90b6-de963d44b4e5\",\"order_by\":2,\"name\":\"Yu-Che Lee\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Kaohsiung Chang Gung Memorial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Yu-Che\",\"middleName\":\"\",\"lastName\":\"Lee\",\"suffix\":\"\"},{\"id\":634024525,\"identity\":\"752b719c-621e-4ec3-9a8a-1b4b51d98064\",\"order_by\":3,\"name\":\"Cheng-Pang Yang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Linkou Chang Gung Memorial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Cheng-Pang\",\"middleName\":\"\",\"lastName\":\"Yang\",\"suffix\":\"\"},{\"id\":634024526,\"identity\":\"0226f153-ac26-4400-8a87-053e1bdb0b64\",\"order_by\":4,\"name\":\"Joe Chih-Hao Chiu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Linkou Chang Gung Memorial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Joe\",\"middleName\":\"Chih-Hao\",\"lastName\":\"Chiu\",\"suffix\":\"\"},{\"id\":634024528,\"identity\":\"5b8056a0-593e-4be0-8c29-8db4d1b2bb42\",\"order_by\":5,\"name\":\"Yi Lu\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYFAC5gaGChDNDmQwGDDIgdgHHuDVwtjAcAaslRGsxRisJYF4LQwMiWASnxZ+6cY2iQMV96L5mxkbH/MU1KXPDzv8EGiLnZxuA3YtknMOArWcKc6dcZix2ZjH4HDuxttpBkAtycZmB7BrMbiR2Cb9sS0ht+EwY5s0j8GB3I2zE0BaDiRuw6NF4iBQy3yIlrp0w9npH4jTsgGihTlBXjoHvy2SMxKbLQ6cScjdCPSL4RyDw4YbpHMKDiQY4PYLv0TywRsHKhJy5x1vPvjgzZ86efnZ6Zs/fKiwk8OlBQhYJFCdClZpgFM5CDB/QOHKN+BVPQpGwSgYBSMQAACKN2czybtxHAAAAABJRU5ErkJggg==\",\"orcid\":\"\",\"institution\":\"Linkou Chang Gung Memorial Hospital\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Yi\",\"middleName\":\"\",\"lastName\":\"Lu\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2026-04-14 09:40:12\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-9413563/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-9413563/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":108950333,\"identity\":\"f4e80eba-6775-4906-b5cd-c2bae10567c7\",\"added_by\":\"auto\",\"created_at\":\"2026-05-11 07:05:10\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":101071,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eFlow diagram of the study group (left) and control group (right). MLB, Major League Baseball; ACLR, anterior cruciate ligament reconstruction; fWAR, fangraph Wins Above Replacement\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9413563/v1/d94c996b7c4178d155c938c8.png\"},{\"id\":108977809,\"identity\":\"60ce149b-2819-4e92-a3c4-d7a71dd9c2d4\",\"added_by\":\"auto\",\"created_at\":\"2026-05-11 11:33:00\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":35036,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eStatistical power as a function of effect size (Cohen’s d) for a sample size of n = 14 per group. Abbreviation: DRS, defensive runs saved; XBR, extra base running.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9413563/v1/d73fcb72a087e68607c50e0f.png\"},{\"id\":108979915,\"identity\":\"9f925287-9acb-4126-9400-6b547cafa526\",\"added_by\":\"auto\",\"created_at\":\"2026-05-11 12:02:15\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":587156,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9413563/v1/488094b2-c203-42da-a9f0-ecb9293cb722.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Performance after Anterior Cruciate Ligament Reconstruction in Major League Baseball Fielders\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eInjury to the anterior cruciate ligament (ACL) is a common sports-related injury that significantly impacts athletic performance, primarily by restricting knee mobility.\\u003csup\\u003e\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e\\u003c/sup\\u003e Additionally, it impacts vertical jump ability due to reduced knee stability and power generation,\\u003csup\\u003e37\\u003c/sup\\u003e limiting explosive force production.\\u003csup\\u003e\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e\\u003c/sup\\u003e Besides, since the ACL restricts varus and valgus stress and regulates rotational movements,\\u003csup\\u003e5\\u003c/sup\\u003e ACL injuries destabilize the knee, impairing its ability to handle sudden directional changes. This instability hinders agility by reducing control over lateral and twisting movements, both essential for rapid acceleration, deceleration, and pivoting.\\u003c/p\\u003e \\u003cp\\u003eCurrently, Anterior cruciate ligament reconstruction (ACLR) is the primary treatment for athletes who aiming to return to competition.\\u003csup\\u003e\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e\\u003c/sup\\u003e However, post-ACLR, athletes often struggle to regain pre-injury performance levels due to persistent quadriceps weakness,\\u003csup\\u003e11,36\\u003c/sup\\u003e altered movement patterns,\\u003csup\\u003e4,31,33\\u003c/sup\\u003e and reduced knee function,\\u003csup\\u003e22\\u003c/sup\\u003e with these issues often lasting up to two years despite rehabilitation.\\u003c/p\\u003e \\u003cp\\u003eIn baseball, lower extremity injuries, including ACL injuries, are less common than elbow and shoulder injuries.\\u003csup\\u003e\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e\\u003c/sup\\u003e However, they significantly impact game performance.\\u003csup\\u003e\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e\\u003c/sup\\u003e A study conducted by Stan Conte revealed that over an 11-year period in Major League Baseball (MLB), knee injuries contributed to 7.3% of all injured list days.\\u003csup\\u003e\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u003c/sup\\u003e Furthermore, from 2011 to 2014, knee injuries had an incidence rate of 1.2 per 1,000 athlete-exposures, resulting in an average of 16.2 missed days per injury, accumulating over 30,000 total missed days. Approximately 12% of knee injuries required surgical intervention, and non-contact mechanisms, such as base-running, contributed to 44% of these injuries, with base-runners being the most frequently injured group.\\u003csup\\u003e\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e \\u003cp\\u003eBeyond performance limitations, knee injuries pose a significant financial burden. From 1998 to 2015, the annual cost of placing MLB players on the injured list averaged \\u003cspan\\u003e$\\u003c/span\\u003e423\\u0026nbsp;million, totaling over \\u003cspan\\u003e$\\u003c/span\\u003e7.6\\u0026nbsp;billion. While specific cost breakdowns for knee injuries were not provided, given that knee injuries comprised 9.8% of injured list placements, their economic impact is also substantial.\\u003csup\\u003e\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e \\u003cp\\u003eA study on ACL injuries in MLB revealed that they were more prevalent in infielders (32%) and outfielders (32%) than in pitchers (29%), particularly during fielding (68%) and base-running (29%).\\u003csup\\u003e10\\u003c/sup\\u003e Additionally, Fabricant et al. reported that 88% of MLB players returned to at least 30 games post-ACLR, though they experienced a 21.2% decline in games played. The study also found that the extent of batting decline was influenced by whether the injury affected the rear or lead batting leg, whereas stolen base success rates remained unaffected.\\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u003c/sup\\u003e\\u003c/p\\u003e \\u003cp\\u003eWhile previous studies have examined return-to-play rates and traditional performance metrics post-ACLR,\\u003csup\\u003e15\\u003c/sup\\u003e there is limited research utilizing advanced statistical analyses to assess its impact on performance. This study aims to address this gap by analyzing advanced performance metrics in MLB fielders before and after ACLR, comparing them with uninjured players of similar anthropometric characteristics and fielding positions. We hypothesize that fielders undergoing ACLR will demonstrate significant declines in performance metrics, concerning baserunning, fielding, and batting, compared to uninjured controls.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStudy Cohort\\u003c/h2\\u003e \\u003cp\\u003e This study was reported in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines to improve transparency and reproducibility. We performed a retrospective case-control study on MLB fielders who underwent ACLR between January 1, 2015, and December 31, 2023. The inclusion of this date range was based on the availability of Statcast data.\\u003csup\\u003e\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e\\u003c/sup\\u003e Utilizing the MLB's official injured list and website (MLB.com),\\u003csup\\u003e25\\u003c/sup\\u003e we compiled a comprehensive dataset of MLB fielders who had ACLR during this period. We also conducted a rigorous cross-referencing process using multiple publicly available and reputable sources. These included Baseball-Reference,\\u003csup\\u003e1\\u003c/sup\\u003e Fangraphs,\\u003csup\\u003e2\\u003c/sup\\u003e and official team announcements. Each identified case of ACL reconstruction was verified through at least two independent sources to ensure the accuracy of injury status and surgery timing. This approach is consistent with prior peer-reviewed studies examining professional athlete injuries using public data.\\u003csup\\u003e\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e\\u003c/sup\\u003e We clearly defined eligibility criteria a priori: fielders with \\u0026gt;\\u0026thinsp;100 plate appearances (PA) in the season prior to ACLR (\\\"index year\\\") and those with \\u0026gt;\\u0026thinsp;100 PA after successful return to MLB post-ACLR (\\\"post-reconstruction year\\\", PRY). Players undergoing revision surgeries were excluded.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eControl Group\\u003c/h3\\u003e\\n\\u003cp\\u003eA matched 1:2 control group was established, consisting of MLB fielders without a history of ACLR. Control players were selected from the same MLB season (calendar year) in which the corresponding case sustained the ACL injury (incident density sampling). Matching criteria included identical defensive position, batting side, an age difference within three years, and the closest Fangraph Wins Above Replacement (fWAR) value in the same index year. By ensuring that controls were active MLB players in the same season as their matched case, this design inherently controlled for seasonal variations, league-wide trends, and rule or equipment changes that could influence performance metrics.\\u003c/p\\u003e \\u003cp\\u003eAdditionally, the players were also required to have a minimum of 100 PA in the selected season to qualify as matched controls. Once the most suitable candidate was identified, a discreet review of the player\\u0026rsquo;s public injury records was conducted to confirm the absence of ACLR history. The rationale for 1:2 matching was to improve statistical efficiency and balance key covariates across groups. This pair-matched group was incorporated to evaluate potential year-to-year changes in base-running, batting, and defensive parameters, accounting for statistical or measurement variations.\\u003c/p\\u003e\\n\\u003ch3\\u003eData curation\\u003c/h3\\u003e\\n\\u003cp\\u003eAnthropometric characteristics were collected, including age at surgery, body mass index (BMI), height, weight, batting sides, and defensive positions. The defensive positions were defined as the positions that the players played the most during the specific season. Injury-related data, such as the date of ACLR and the date of return to competition at the MLB level, were also recorded.\\u003c/p\\u003e \\u003cp\\u003eBasic and advanced performance data were sourced from the Statcast system. For the study group, data were collected for two distinct periods: the index year and the post-reconstruction year (PRY), which was defined as the season in which the player returned to MLB with at least 100 PA. Corresponding data for the control group covering the same periods as their study group counterparts was also collected. Data sources were publicly available, and data collection procedures were standardized. No imputation was applied. Annual performance metrics for both the study group and the control group were recorded. The metrics could be divided into three categories: baserunning, defensive, and batting.\\u003c/p\\u003e \\u003cp\\u003eAs for baserunning metrics, the variables tracked included Ultimate Base Running (UBR), Extra Bases Taken (XBR), Weighted Stolen Bases (wSB), Base Running Score (BSR), sprint speed, and the time from home plate to first base (HP-to-1B). UBR quantifies a player\\u0026rsquo;s ability to advance on the basepaths outside of stolen bases, measuring decision-making and aggressiveness in taking extra bases on balls in play. XBR reflects the percentage of times a runner advances more than one base on a single or more than two bases on a double, showcasing their ability to capitalize on opportunities. The wSB evaluates a player\\u0026rsquo;s stolen base contributions relative to league averages, accounting for both success rate and volume to assess overall value. BSR, a composite metric, integrates UBR, wSB, and other baserunning components to provide a comprehensive measure of a player\\u0026rsquo;s overall effectiveness. These metrics collectively evaluate a player's efficiency and effectiveness on the bases, capturing their ability to take extra bases, steal bases, and their overall speed and agility.\\u003c/p\\u003e \\u003cp\\u003eIn terms of defensive metrics, Ultimate Zone Rating (UZR) and Defensive Runs Saved (DRS) were used to measure each player's defensive contributions. UZR quantifies a player's fielding ability in terms of runs saved or cost in their specific fielding zone, while DRS provides a more comprehensive look at the number of runs a player saved or cost their team due to their defensive play across all fielding opportunities.\\u003c/p\\u003e \\u003cp\\u003eFor batting performance, the study analyzed a range of metrics including On-base Plus Slugging (OPS), which combines on-base percentage (OBP) and slugging percentage (SLG) to measure a player's offensive contribution, assessing their ability to get on base and hit for power. Weighted Runs Created Plus (wRC+) adjusts a player's offensive value to account for park effects and the current offensive environment, with 100 being league average, values above 100 as above-average, and below 100 as below-average. Maximum Exit Velocity (Max-EV) and Average Exit Velocity (Avg-EV) measure the speed of the baseball off the bat, indicative of hitting power. Barrel Percentage (Barrel%) and Barrels per Plate Appearance (Brls/PA) highlight a player\\u0026rsquo;s ability to make optimal contact with the ball, leading to more productive outcomes such as extra-base hits.\\u003c/p\\u003e \\u003cp\\u003eAll definitions and metric computations were consistent with Fangraphs glossary and Statcast documentation. These metrics provide a thorough analysis of player performance, offering insights into their speed, defensive capabilities, and hitting prowess, which are essential for evaluating their overall impact on the game. If any key performance metric was missing, the player was then excluded from the study group.\\u003c/p\\u003e \\u003cp\\u003eThese variables were initially analyzed between the study group and the control group. Subsequently, the yearly changes from the index year to PRY in these variables were further examined between the two groups.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStatistical Analysis\\u003c/h2\\u003e \\u003cp\\u003eResidual distributions were evaluated for normality using the Kolmogorov-Smirnov test to determine the appropriateness of parametric versus nonparametric tests. The Mann-Whitney U test and Wilcoxon signed-rank test were applied for nonparametric data, while independent and paired t-tests were used for parametric data to evaluate the between-group differences. Pearson's correlation coefficient was employed to analyze relationships between variables in a continuous fashion. A P value less than 0.05 was considered to indicate statistical significance. A post hoc power analysis was conducted to evaluate the statistical power of the observed significant findings. For each variable, effect sizes were estimated by dividing the reported mean difference by the pooled standard deviation, yielding Cohen\\u0026rsquo;s \\u003cem\\u003ed\\u003c/em\\u003e. A two-tailed two-sample \\u003cem\\u003et\\u003c/em\\u003e-test framework was used for power estimation with a significance level of 0.05. All statistical analyses were conducted using SPSS Statistics for Mac, version 25.0.0 (IBM Corp., Armonk, NY, USA).\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003ePlayer Characteristics\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eOf the 27 MLB players who underwent ACLR from 2015 to 2023, 3 were excluded due to their roles as pitchers. Additionally, 8 players were excluded for not meeting our inclusion criteria of a successful return to competition (RTC). Two players excluded due to a lack of comprehensive performance data. Eventually, 14 fielders were identified for the analysis. After finalizing this process, the control group was established in a 1:2 matched fashion. Following a discreet screening process, no players were excluded from the control group after their initial selection. A flow diagram of the study cohort is presented in Figure 1.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003ePlayer characteristics are presented in Table 1. As for anthropometric data, there was no significant difference between the study group and the control group.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eTable 1 Player Characteristics\\u003c/p\\u003e\\n\\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eVariables\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003eStudy group\\u003c/p\\u003e\\n \\u003cp\\u003e(n = 14)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003eControl group\\u003c/p\\u003e\\n \\u003cp\\u003e(n = 28)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003eP value\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003ePA, n\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e346.6 \\u0026plusmn; 200.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e231.6 \\u0026plusmn; 173.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e0.07\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003eIndex age, years old\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e27.3 \\u0026plusmn; 2.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e27.2 \\u0026plusmn; 3.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e0.94\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003eHeight, cm\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e183.9 \\u0026plusmn; 5.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e183.0 \\u0026plusmn; 5.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e0.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003eWeight, kg\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e92.8 \\u0026plusmn; 9.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e91.4 \\u0026plusmn; 8.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e0.62\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003eBody mass index, kg/m\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e27.4 \\u0026plusmn; 1.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e27.3 \\u0026plusmn; 1.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e0.82\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003eRH:LH, n\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e8:6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e16:12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e0.98\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003eSurgery year, n\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003e2015\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003e2016\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003e2017\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003e2018\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003e2019\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003e2020\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003e2021\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41.1111%;\\\"\\u003e\\n \\u003cp\\u003e2022\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.6296%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eAbbreviation: PA, plate appearance; RH, right side hitter; LH, left side hitter.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eBase Running\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe yearly base running performance data are presented in Table 2A, while the yearly changes are detailed in Table 2B. No significant differences were observed in any parameter during the index year or PRY. However, yearly changes revealed significant differences in both XBR and sprint speed between the study and control groups. Specifically, the study group demonstrated a significant decrease in XBR compared to the control group (-0.34 \\u0026plusmn; 0.84 vs. 0.53 \\u0026plusmn; 1.29; P = 0.03) and a significant reduction in sprint speed (-0.55 \\u0026plusmn; 0.45 vs. -0.27 \\u0026plusmn; 0.48; P = 0.04).\\u003c/p\\u003e\\n\\u003cp\\u003eTable 2 Player Baserunning Data\\u003c/p\\u003e\\n\\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"553\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eVariables\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003eStudy group\\u003c/p\\u003e\\n \\u003cp\\u003e(n = 28)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003eControl group\\u003c/p\\u003e\\n \\u003cp\\u003e(n = 14)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003eP value\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003eIndex year\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003eUBR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e0.53 \\u0026plusmn; 1.17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e0.12 \\u0026plusmn; 1.92\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.47\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003eXBR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e0.27 \\u0026plusmn; 1.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e-0.28 \\u0026plusmn; 1.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.24\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003ewSB\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e-0.17 \\u0026plusmn; 0.36\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e-0.20 \\u0026plusmn; 0.70\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.87\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003eBSR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e0.26 \\u0026plusmn; 1.39\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e-0.23 \\u0026plusmn; 1.91\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003eSprint speed, feet per second\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e27.53 \\u0026plusmn; 1.77\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e27.22 \\u0026plusmn; 1.10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.49\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003eHP-to-1B, second\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e4.33 \\u0026plusmn; 0.29\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e4.42 \\u0026plusmn; 0.17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003ePost-reconstruction year\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003eUBR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e-0.02 \\u0026plusmn; 1.66\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e0.36 \\u0026plusmn; 1.20\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.40\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003eXBR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e-0.11 \\u0026plusmn; 1.43\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e0.29 \\u0026plusmn; 0.68\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.22\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003ewSB\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e0.11 \\u0026plusmn; 0.56\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e-0.19 \\u0026plusmn; 0.91\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.27\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003eBSR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e-0.04 \\u0026plusmn; 1.61\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e0.08 \\u0026plusmn; 1.01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.77\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003eSprint speed, feet per second\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e27.05 \\u0026plusmn; 1.71\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e26.95 \\u0026plusmn; 1.23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.83\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003eHP-to-1B, second\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e4.45 \\u0026plusmn; 0.23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e4.45 \\u0026plusmn; 0.19\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.97\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eYearly changes\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003eUBR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e-0.55 \\u0026plusmn; 1.54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e0.24 \\u0026plusmn; 1.88\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.18\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e*XBR\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e-0.34\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026plusmn; 0.84\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.53\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026plusmn; 1.29\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.03\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003ewSB\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e0.28 \\u0026plusmn; 0.54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e0.01 \\u0026plusmn; 0.71\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.22\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003eBSR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e-0.3 \\u0026plusmn; 0.96\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e0.31 \\u0026plusmn; 1.47\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e*Sprint speed, feet per second\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e-0.55\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026plusmn; 0.45\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e-0.27\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026plusmn; 0.48\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.04\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 26.9439%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.1465%;\\\"\\u003e\\n \\u003cp\\u003eHP-to-1B, second\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 18.9873%;\\\"\\u003e\\n \\u003cp\\u003e0.14 \\u0026plusmn; 1.83\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.349%;\\\"\\u003e\\n \\u003cp\\u003e0.03 \\u0026plusmn; 0.07\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 11.5732%;\\\"\\u003e\\n \\u003cp\\u003e0.76\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eAbbreviation: UBR, ultimate base running; XBR, extra base running; wSB, weighted stolen base runs; BSR, base running runs; HP-to-1B, the average time needed to run from home plate to first base.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDefensive Metrics\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eTable 3 summarizes the yearly performance and yearly changes in defensive metrics. The study group exhibited significantly poorer performance in DRS following ACLR, as indicated by both the overall yearly performance (PRY: -2.79 \\u0026plusmn; 3.53 vs. -0.04 \\u0026plusmn; 3.45; P = 0.02) and the yearly change (\\u0026Delta;DRS: -3.93 \\u0026plusmn; 4.76 vs. -1.36 \\u0026plusmn; 6.37; P = 0.04). In contrast, no significant differences were observed in UZR metrics across all measured parameters.\\u003c/p\\u003e\\n\\u003cp\\u003eTable 3 Defensive Metrics\\u003c/p\\u003e\\n\\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"548\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.3784%;\\\"\\u003e\\n \\u003cp\\u003eVariable\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003eStudy group\\u003c/p\\u003e\\n \\u003cp\\u003e(n = 28)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003eControl group\\u003c/p\\u003e\\n \\u003cp\\u003e(n = 14)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12.6143%;\\\"\\u003e\\n \\u003cp\\u003eP value\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.3784%;\\\"\\u003e\\n \\u003cp\\u003eIndex year\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12.6143%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.3784%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003eUZR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e1.05 \\u0026plusmn; 3.28\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e0.84 \\u0026plusmn; 4.61\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12.6143%;\\\"\\u003e\\n \\u003cp\\u003e0.88\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.3784%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003eDRS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e1.14 \\u0026plusmn; 3.28\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e1.32 \\u0026plusmn; 6.81\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12.6143%;\\\"\\u003e\\n \\u003cp\\u003e0.93\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.3784%;\\\"\\u003e\\n \\u003cp\\u003ePost-reconstruction year\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12.6143%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.3784%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003eUZR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e-1.14 \\u0026plusmn; 2.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e0.24 \\u0026plusmn; 2.69\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12.6143%;\\\"\\u003e\\n \\u003cp\\u003e0.12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.3784%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e*DRS\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e-2.79\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026plusmn; 3.53\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e-0.04\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026plusmn; 3.45\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12.6143%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.02\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.3784%;\\\"\\u003e\\n \\u003cp\\u003eYearly changes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12.6143%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.3784%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003eUZR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e-2.04 \\u0026plusmn; 4.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e-0.56 \\u0026plusmn; 3.62\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12.6143%;\\\"\\u003e\\n \\u003cp\\u003e0.24\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.3784%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e*DRS\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e-3.93\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026plusmn; 4.76\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 22.6691%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e-1.36\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026plusmn; 6.37\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 12.6143%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.04\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eAbbreviation: UZR, ultimate zone rating; DRS, defensive runs saved\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eBatting Performance\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eBatting performance was assessed using advanced data, such as wRC+, WAR, Barrel% and so on. The data were summarized in Tables 4A and 4B. As for yearly performance and changes of the batting performance, there was no significant difference in all the aspects considering batting performance between study group and control group.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eTable 4 Player Batting Performance Data\\u003c/p\\u003e\\n\\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"553\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003eVariable\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003eStudy group\\u003c/p\\u003e\\n \\u003cp\\u003e(n = 28)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003eControl group\\u003c/p\\u003e\\n \\u003cp\\u003e(n = 14)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003eP value\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003eIndex year\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eOPS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e0.77 \\u0026plusmn; 0.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e0.71 \\u0026plusmn; 0.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003ewRC+\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e108.36 \\u0026plusmn; 33.72\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e90.46 \\u0026plusmn; 32.82\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003efWAR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e1.14 \\u0026plusmn; 1.31\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e0.91 \\u0026plusmn; 0.92\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.51\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003ebWAR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e1.14 \\u0026plusmn; 1.29\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e1.11 \\u0026plusmn; 1.41\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.92\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eMAX_EV\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e110.25 \\u0026plusmn; 3.47\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e109.51 \\u0026plusmn; 3.81\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eAvg_EV\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e88.84 \\u0026plusmn; 3.05\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e87.68 \\u0026plusmn; 2.53\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.20\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eBarrel%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e6.67 \\u0026plusmn; 5.37\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e6.17 \\u0026plusmn; 3.62\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.72\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eBrls/PA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e4.31 \\u0026plusmn; 3.18\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e4.09 \\u0026plusmn; 2.35\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.80\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003ePost-reconstruction year\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eOPS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e0.7 \\u0026plusmn; 0.12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e0.67 \\u0026plusmn; 0.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.40\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003ewRC+\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e90.52 \\u0026plusmn; 33.79\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e86.68 \\u0026plusmn; 27.52\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.70\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003efWAR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e0.67 \\u0026plusmn; 1.21\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e0.69 \\u0026plusmn; 1.17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.97\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003ebWAR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e0.54 \\u0026plusmn; 1.21\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e0.61 \\u0026plusmn; 1.23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.87\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eMAX_EV\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e109.86 \\u0026plusmn; 4.02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e109.39 \\u0026plusmn; 3.81\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.71\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eAvg_EV\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e89.01 \\u0026plusmn; 1.52\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e87.21 \\u0026plusmn; 2.76\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.08\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eBarrel%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e7.78 \\u0026plusmn; 4.05\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e5.54 \\u0026plusmn; 3.91\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.09\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eBrls/PA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e5.14 \\u0026plusmn; 2.47\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e3.77 \\u0026plusmn; 2.38\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.09\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eYearly changes\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eOPS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e-0.04 \\u0026plusmn; 0.16\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e-0.06 \\u0026plusmn; 0.12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003ewRC+\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e-3.79 \\u0026plusmn; 34.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e-17.86 \\u0026plusmn; 31.27\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003efWAR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e-0.23 \\u0026plusmn; 1.34\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e-0.47 \\u0026plusmn; 1.37\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.59\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003ebWAR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e-0.49 \\u0026plusmn; 1.62\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e-0.6 \\u0026plusmn; 1.42\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.82\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eMAX_EV\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e-0.12 \\u0026plusmn; 2.85\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e-0.39 \\u0026plusmn; 2.89\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.78\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eAvg_EV\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e-0.44 \\u0026plusmn; 2.29\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e0.17 \\u0026plusmn; 2.39\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.43\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eBarrel%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e-0.64 \\u0026plusmn; 3.11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e1.11 \\u0026plusmn; 3.17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 23.7319%;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 19.2029%;\\\"\\u003e\\n \\u003cp\\u003eBrls/PA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e-0.32 \\u0026plusmn; 1.87\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 21.9203%;\\\"\\u003e\\n \\u003cp\\u003e0.83 \\u0026plusmn; 1.82\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 13.2246%;\\\"\\u003e\\n \\u003cp\\u003e0.07\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eAbbreviation: OPS, on-base plus slugging; wRC+, weighted runs created plus; fWAR, Fangraphs wins above replacement; bWAR, Baseball-Reference wins above replacement; MAX_EV, maximum exit velocity; Avg_EV, average exit velocity; Barrel%, percentage of batted balls classified as \\u0026quot;barrels\\u0026quot;; Brls/PA, barrels per plate appearance.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ePower Analysis\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eTo assess the robustness of our statistically significant findings, a post hoc power analysis was conducted for sprint speed, XBR, and DRS. Using Cohen\\u0026rsquo;s \\u003cem\\u003ed\\u003c/em\\u003e as the effect size and assuming two-tailed independent samples \\u003cem\\u003et\\u003c/em\\u003e-tests at a significance level of 0.05 with 14 participants per group, the following results were obtained:\\u003c/p\\u003e\\n\\u003cp\\u003eFor sprint speed, the observed mean difference was 0.55 ft/sec with a standard deviation of 0.45, yielding a large standardized difference (Cohen\\u0026rsquo;s \\u003cem\\u003ed\\u003c/em\\u003e = 1.22). The calculated statistical power was 0.98, indicating a high probability of detecting a true difference.\\u0026nbsp;For XBR, the mean difference was 0.87 with a standard deviation of 0.84, yielding a moderate standardized difference (\\u003cem\\u003ed\\u003c/em\\u003e = 0.40). The corresponding power was 0.36, suggesting a relatively low likelihood of reliably detecting the observed difference with the given sample size. For DRS, the mean difference was 3.93 runs with a standard deviation of 4.76, resulting in a standardized difference of \\u003cem\\u003ed\\u003c/em\\u003e = 0.83. This corresponded to a power of 0.73, indicating a moderate-to-high probability of detecting this difference. (Figure 2)\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eAmong the 27 MLB fielders identified with ACL reconstruction, only 19 (70%) achieved a meaningful return to play, defined in our study as recording at least 100 plate appearances in the post-reconstruction season. This relatively strict threshold ensures that only players with sufficient playing time are analyzed, thereby increasing the reliability of performance comparisons. Notably, nearly 30% failed to meet this benchmark, underscoring the challenge of returning to consistent participation at the MLB level following ACLR.\\u003c/p\\u003e\\n\\u003cp\\u003eAmong those who returned, we assessed post-ACLR performance in baserunning, defense, and batting using advanced metrics. The analysis revealed significant declines in sprint speed, XBR, and defensive runs saved DRS,\\u0026nbsp;suggesting an association with reduced baserunning efficiency and defensive effectiveness. In contrast, batting metrics showed no significant differences, suggesting that offensive performance remained stable despite mobility and defensive limitations.\\u003c/p\\u003e\\n\\u003cp\\u003eThe decline in baserunning performance observed in this study aligns with findings from previous research, emphasizing the significant impact of ACLR on agility and mobility. In our analysis, MLB fielders who underwent ACLR exhibited a notable decrease in sprint speed and XBR compared to the control group. Sprint speed reflects a player\\u0026apos;s maximum running velocity, providing a direct assessment of explosive speed critical for successful baserunning. Similarly, XBR quantifies a player\\u0026apos;s ability to take extra bases on hits, integrating speed, decision-making, and agility into a comprehensive measure of baserunning efficiency. This is consistent with the study by Erickson et al.,\\u003csup\\u003e12\\u003c/sup\\u003e which highlighted a general reduction in baserunning\\u0026nbsp;performance among professional baseball players following ACL reconstruction, as reflected by fewer stolen base attempts and slower base-to-base times. Such declines underscore the critical role of lower limb stability and strength in executing quick, dynamic movements required for baserunning.\\u003c/p\\u003e\\n\\u003cp\\u003eThese findings are further supported by Dugas et al., who reported that ACL injuries in baseball players predominantly affect activities such as fielding and baserunning, where sudden accelerations and directional changes are frequent.\\u003csup\\u003e10\\u003c/sup\\u003e This highlights the unique demands of baserunning in baseball, requiring rapid bursts of speed and precise maneuvering, both of which are compromised by ACL injuries. The observed deficits in our study corroborate these findings, suggesting that ACL injuries not only reduce physical performance but also impair the execution of sport-specific skills essential for competitive play.\\u003c/p\\u003e\\n\\u003cp\\u003eTo better understand these deficits, it is necessary to examine the underlying mechanisms by which ACL injuries impair lower limb stability and strength. Damage to the ligament reduces its ability to stabilize the knee joint during rapid movements, resulting in increased joint laxity and a higher risk of instability during dynamic activities.\\u003csup\\u003e28\\u003c/sup\\u003e Additionally, ACL injuries often lead to atrophy in the quadriceps and hamstring muscles due to disuse and postoperative recovery periods, further impairing the muscle strength required for explosive force generation.\\u003csup\\u003e18\\u003c/sup\\u003e Proprioceptive deficits caused by disrupted neuromuscular signaling also contribute to decreased coordination and balance, which are essential for maintaining control during sudden accelerations and directional changes.\\u003csup\\u003e3\\u003c/sup\\u003e Together, these mechanisms provide a comprehensive explanation for the observed baserunning performance deficits in MLB players post-ACLR.\\u003c/p\\u003e\\n\\u003cp\\u003eAs for the defensive performance, this study also identified significant declines in DRS among MLB fielders following ACLR, while UZR remained stable. DRS is a metric that quantifies a player\\u0026apos;s ability to save runs for their team through exceptional defensive plays, incorporating factors such as range, arm strength, and playmaking ability.\\u003csup\\u003e29\\u003c/sup\\u003e In contrast, UZR evaluates a player\\u0026apos;s defensive effectiveness within their designated fielding zone, focusing more on positioning and routine play execution.\\u003csup\\u003e27\\u003c/sup\\u003e From a statistical standpoint, DRS applies stricter criteria in evaluating defensive performance, whereas UZR offers a more lenient approach.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003ePrevious studies on ACL injuries have largely emphasized overall performance metrics or return-to-sport rates,\\u0026nbsp;with relatively little attention given to their association with defensive performance. Our results address this gap by offering novel insights into the defensive challenges faced by MLB fielders\\u0026rsquo; post-reconstruction. The decline in DRS suggests that ACL injuries impact the dynamic aspects of defense, such as chasing down balls or making quick adjustments, which require agility and lower limb stability. Research indicates that ACL injuries impair neuromuscular control and proprioception,\\u003csup\\u003e3\\u003c/sup\\u003e leading to decreased knee stability and compromised athletic performance. For instance, a study by Gokeler et al. found that athletes with ACLR exhibited deficits in dynamic stability during high-demand tasks, which are critical for effective defensive play.\\u003csup\\u003e19\\u003c/sup\\u003e Additionally, Paterno et al. reported that altered movement patterns post-ACL injury increase the risk of re-injury, further impacting an athlete\\u0026apos;s ability to perform dynamic defensive maneuvers.\\u003csup\\u003e32\\u003c/sup\\u003e Conversely, the stability of UZR likely reflects the preservation of fundamental defensive skills, such as positioning and routine decision-making, which rely less on explosive movements. In summary, our findings indicate that a decline in defensive performance among fielders following ACLR does exist, but the extent of the decline is minimal. As a result, significant differences are only observed in DRS, which employs a more stringent scoring method. These findings underscore the importance of tailored rehabilitation programs focusing on dynamic defensive abilities to mitigate the impact of ACL injuries on fielding performance.\\u003c/p\\u003e\\n\\u003cp\\u003eThis study revealed no significant differences in batting performance metrics between MLB fielders who underwent ACLR and the control group. Metrics such as OPS, wRC+, and Max-EV remained comparable in the PRY. These findings align with prior research indicating that ACLR has a limited impact on static and skill-based offensive activities. For example, Fabricant et al. observed that ACLR had minimal impact on the ability of professional baseball players to return to their pre-injury offensive performance levels.\\u003csup\\u003e15\\u003c/sup\\u003e They emphasized that batting performance relies more on skill and precision than the lower limb explosiveness required for baserunning or fielding. Similarly, Mai et al. \\u003csup\\u003e24\\u003c/sup\\u003e reported that performance outcomes after ACLR vary by sports, with baseball showing minimal declines in skill-based activities like batting. They also highlighted that baseball\\u0026apos;s reliance on static and precision-driven skills, rather than dynamic lower limb explosiveness, likely contributes to this resilience.\\u003c/p\\u003e\\n\\u003cp\\u003eThe biomechanics study of the baseball swing by Fortenbaugh et al. differs from our findings, as he emphasized that ground reaction forces generated by the lower limbs play a crucial role in driving the kinetic chain for successful batting performance. The authors identified the transfer of energy from the lower body to the bat through precise coordination and timing as essential for generating optimal bat speed and ball exit velocity.\\u003csup\\u003e16\\u003c/sup\\u003e However, although ACL injuries may affect lower limb stability, the stability of batting performance observed in this study was not impacted by the injury. This implies that batting success relies more on upper body coordination and precise timing, with less dependence on the dynamic lower limb strength affected by ACL injuries.\\u003c/p\\u003e\\n\\u003cp\\u003eBuilding on this, further research into knee mechanics during baseball swings highlights distinct roles for the front and back knees. The front knee\\u0026rsquo;s mechanics resemble exercises in early-stage ACL rehabilitation, potentially enabling earlier return to hitting and helping maintain offensive consistency. In contrast, the back knee\\u0026rsquo;s higher rotary demands suggest a delayed initiation in rehabilitation, which may affect dynamic aspects of hitting, such as generating power and bat speed. Interestingly, slight trends toward improved Barrel% and Barrels/PA observed in our study, though not statistically significant, suggest upper body coordination and precise timing may compensate for deficits in lower limb contributions. These insights reinforce the notion that while the kinetic chain remains vital for successful batting, its reliance on lower limb strength and stability is less critical than previously assumed, particularly for ACL-injured players. Tailored rehabilitation programs addressing the specific demands of the front and back knees can further optimize recovery and ensure a balance between stability, power generation, and timing for effective batting performance.\\u003csup\\u003e17\\u003c/sup\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eLimitation\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThere were some limitations to the current study. First, this study is the relatively small sample size, with 14 ACL-injured players and 28 matched controls. This may be attributed to several reasons. First, the prevalence of ACL reconstruction in MLB fielders is relatively low compared to other surgeries, such as ulnar collateral ligament reconstruction in pitchers. Second, our strict inclusion criteria contributed to the limited sample size, as we only included players who successfully returned to competition and accumulated a sufficient number of plate appearances (PA) postoperatively. While this ensured clean data, it may have excluded players who failed to return\\u0026mdash;possibly due to lasting functional deficits. These cases highlight another potential consequence of ACL injury worth future study.\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003eLastly, our study window was restricted to 2015\\u0026ndash;2023 due to the availability of Statcast data, which was first introduced in 2015.\\u003c/p\\u003e\\n\\u003cp\\u003eAlthough matching on key covariates\\u0026mdash;such as defensive position, batting side, age, and fWAR within the same season\\u0026mdash;helped reduce inter-individual variability and enhance statistical efficiency, the power to detect small-to-moderate effects may still have been limited. Based on preliminary power calculations using observed effect sizes, certain outcomes (e.g., sprint speed) reached acceptable statistical power, while others (e.g., XBR) did not. This suggests that while large differences could be reliably detected, the study may have been underpowered to identify subtler performance changes. Future studies with larger cohorts and extended sampling periods are warranted to validate these findings and improve generalizability.\\u003c/p\\u003e\\n\\u003cp\\u003eAnother limitation of the study was that we obtained information solely from publicly available resources, as we lacked access to operative reports or medical records. Consequently, we could not acquire surgery-related details such as graft types, reconstruction methods, post-operative complications, and rehabilitation programs. This limitation made it impossible to determine surgery-related factors affecting post-ACLR performance.\\u003c/p\\u003e\\n\\u003cp\\u003eThird, this study included only MLB-level players. This selection was due to the completeness of advanced performance metrics, which are only publicly accessible in the MLB-level database. However, this restriction limited the study cohort, meaning our results may not be broadly applicable to other levels, including Minor League Baseball players.\\u003c/p\\u003e\\n\\u003cp\\u003eLastly, in this study, we aimed to utilize advanced performance metrics in baserunning, batting, and fielding to provide the most objective evaluation of players\\u0026apos; performance. However, determining the best indicators for evaluating performance in each category remains challenging. With advancements in in-field tracking technologies, computational algorithms, and data analysis, more refined performance metrics will hopefully become available in the near future, enabling more accurate assessments.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eThis study examined the impact of ACLR on MLB fielders\\u0026rsquo; performance, focusing on baserunning, defense, and batting. The results showed that players experienced a decline in baserunning speed and defensive effectiveness while their batting performance remained largely unchanged. This indicated that ACLR appears to affect movement-based aspects of the game more than skill-based ones. These findings highlight the importance of rehabilitation programs that focus on restoring speed, agility, and defensive mobility. Further research with larger sample sizes and longer follow-ups is needed to better understand\\u0026nbsp;the \\u003cstrong\\u003elong-term associations\\u003c/strong\\u003e between ACL reconstruction and baseball performance and to refine recovery strategies.\\u003c/p\\u003e\\u003cp\\u003e\\u003cstrong\\u003ePractical Implications\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003col\\u003e\\n \\u003cli\\u003eMLB fielders who undergo ACL reconstruction may experience notable declines in baserunning and defensive performance, particularly in speed- and agility-dependent tasks, even after successful return to play.\\u003c/li\\u003e\\n \\u003cli\\u003eBatting performance tends to remain stable post-ACLR, suggesting that offensive skills may be less affected than mobility-based defensive contributions.\\u003c/li\\u003e\\n \\u003cli\\u003ePostoperative rehabilitation should emphasize mobility, agility, and lower extremity stability, with a focus on sprinting, directional changes, and field coverage.\\u003c/li\\u003e\\n \\u003cli\\u003eTeam decision-makers should consider the potential long-term impact on baserunning and fielding\\u0026mdash;not just batting\\u0026mdash;when evaluating the post-ACLR readiness and contract value of field players.\\u003c/li\\u003e\\n \\u003cli\\u003eThese findings provide data-driven insight to guide individualized return-to-play protocols and long-term management strategies in professional baseball.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eHuman Ethics and Consent to Participate:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable. This study analysed publicly available, de-identified data from MLB.com and publicly accessible baseball analytics platforms (Statcast/Baseball Savant, FanGraphs, and Baseball-Reference). No human participants were recruited, no direct contact or intervention occurred, and no identifiable private information was collected; therefore, ethics approval and informed consent to participate were \\u003cstrong\\u003enot applicable\\u003c/strong\\u003e\\u003cstrong\\u003e.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics Approval declaration:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable. This study analysed publicly available, de-identified data and did not involve direct contact with human participants or identifiable private information; therefore, review by the \\u003cstrong\\u003eInstitutional Review Board of Linkou Chang Gung Memorial Hospital\\u003c/strong\\u003e was not required.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding Declaration:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\\u003c/p\\u003e\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003ePo-Chun Chi and Min-Hao Sun contributed equally to this work and share first authorship.Po-Chun Chi, Min-Hao Sun and Yu-Che Lee collected the data and performed the analyses.Po-Chun Chi drafted the manuscript.Min-Hao Sun, Joe Chih-Hao Chiu, Yi-Lu, and Cheng-Pang Yang critically revised the manuscript for important intellectual content.Yi-Lu supervised the study.All authors reviewed and approved the final manuscript.\\u003c/p\\u003e\\u003ch2\\u003eAcknowledgement\\u003c/h2\\u003e\\u003cp\\u003eThe authors would like to express their gratitude to the Department of Orthopedic Surgery at Chang Gung Memorial Hospital for their support throughout the course of this study. We also thank Dr. Joe Chih-Hao Chiu for valuable insights into the methodology and Dr. Cheng-Pang Yang, for assistance with data handling and statistical analysis. The authors also acknowledge the contributions of Dr. Yi-Sheng Chan and Dr Yi Lu, who assisted with manuscript proofreading and language editing.\\u003c/p\\u003e\\u003ch2\\u003eData Availability\\u003c/h2\\u003e\\u003cp\\u003eThe study analysed publicly available data from the following sources:1. Dataset title: MLB Statcast (player running, hitting, and sprint speed metrics; seasons 2015\\u0026ndash;2023)Repository name: Baseball Savant (Statcast), Major League Baseball Advanced MediaPersistent identifier: https://baseballsavant.mlb.com/2. Dataset title: FanGraphs Advanced Metrics (including UBR, XBR, wSB, BSR, wRC+, fWAR; seasons 2015\\u0026ndash;2023)Repository name: FanGraphsPersistent identifier: https://www.fangraphs.com/3. Dataset title: Baseball-Reference Player Statistics (player-level seasonal statistics and demographics used for cross-referencing)Repository name: Baseball-ReferencePersistent identifier: https://www.baseball-reference.com/4. Dataset title: MLB Injury/Transaction Information (injured list reports and related injury/surgery timing used for case identification and verification)Repository name: MLB.comPersistent identifier: https://www.mlb.com/No new clinical or patient-level datasets were generated for this study. The curated dataset compiled from the above public sources (including the list of included players and extracted season-level metrics used for analysis) can be made available from the corresponding author upon reasonable request.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eBaseball-Reference. \\u003cem\\u003ehttps://wwwbaseball-referencecom/\\u003c/em\\u003e\\u003cem\\u003e.\\u003c/em\\u003e\\u003c/li\\u003e\\n\\u003cli\\u003eFangraphs. \\u003cem\\u003ehttps://wwwfangraphscom/\\u003c/em\\u003e\\u003cem\\u003e.\\u003c/em\\u003e\\u003c/li\\u003e\\n\\u003cli\\u003eArumugam A, Bj\\u0026ouml;rklund M, Mikko S, H\\u0026auml;ger CK. Effects of neuromuscular training on knee proprioception in individuals with anterior cruciate ligament injury: a systematic review and GRADE evidence synthesis. \\u003cem\\u003eBMJ Open. \\u003c/em\\u003e2021;11(5):e049226.\\u003c/li\\u003e\\n\\u003cli\\u003eCastanharo R, da Luz BS, Bitar AC, et al. Males still have limb asymmetries in multijoint movement tasks more than 2 years following anterior cruciate ligament reconstruction. \\u003cem\\u003eJ Orthop Sci. \\u003c/em\\u003e2011;16(5):531-535.\\u003c/li\\u003e\\n\\u003cli\\u003eChhabra A, Starman JS, Ferretti M, et al. Anatomic, radiographic, biomechanical, and kinematic evaluation of the anterior cruciate ligament and its two functional bundles. \\u003cem\\u003eJ Bone Joint Surg Am. \\u003c/em\\u003e2006;88 Suppl 4:2-10.\\u003c/li\\u003e\\n\\u003cli\\u003eConte S, Camp CL, Dines JS. Injury Trends in Major League Baseball Over 18 Seasons: 1998-2015. \\u003cem\\u003eAm J Orthop (Belle Mead NJ). \\u003c/em\\u003e2016;45(3):116-123.\\u003c/li\\u003e\\n\\u003cli\\u003eConte S, Requa RK, Garrick JG. Disability days in major league baseball. \\u003cem\\u003eAm J Sports Med. \\u003c/em\\u003e2001;29(4):431-436.\\u003c/li\\u003e\\n\\u003cli\\u003eDahm DL, Curriero FC, Camp CL, et al. 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Preoperative quadriceps strength is a significant predictor of knee function two years after anterior cruciate ligament reconstruction. \\u003cem\\u003eBr J Sports Med. \\u003c/em\\u003e2009;43(5):371-376.\\u003c/li\\u003e\\n\\u003cli\\u003eErickson BJ, Chalmers PN, D\\u0026apos;Angelo J, et al. Performance and Return to Sport After Anterior Cruciate Ligament Reconstruction in Professional Baseball Players. \\u003cem\\u003eOrthop J Sports Med. \\u003c/em\\u003e2019;7(10):2325967119878431.\\u003c/li\\u003e\\n\\u003cli\\u003eErickson BJ, Harris JD, Cvetanovich GL, et al. Performance and Return to Sport After Anterior Cruciate Ligament Reconstruction in Male Major League Soccer Players. \\u003cem\\u003eOrthop J Sports Med. \\u003c/em\\u003e2013;1(2):2325967113497189.\\u003c/li\\u003e\\n\\u003cli\\u003eEvans J, Mabrouk A, Nielson JL. Anterior Cruciate Ligament Knee Injury. In: \\u003cem\\u003eStatPearls.\\u003c/em\\u003e Treasure Island (FL): StatPearls Publishing Copyright \\u0026copy; 2024, StatPearls Publishing LLC.; 2024.\\u003c/li\\u003e\\n\\u003cli\\u003eFabricant PD, Chin CS, Conte S, et al. Return to play after anterior cruciate ligament reconstruction in major league baseball athletes. \\u003cem\\u003eArthroscopy. \\u003c/em\\u003e2015;31(5):896-900.\\u003c/li\\u003e\\n\\u003cli\\u003eFortenbaugh DM. The Biomechanics of the Baseball Swing. In: Asfour S, Abdelrahman K, Latta L, Onar-Thomas A, Fleisig G, eds.\\u003cem\\u003e A dissertation at the University of Miami. .\\u003c/em\\u003e2011.\\u003c/li\\u003e\\n\\u003cli\\u003eGiordano K, Chaput M, Anz A, et al. Knee Kinetics in Baseball Hitting and Return to Play after ACL Reconstruction. \\u003cem\\u003eInt J Sports Med. \\u003c/em\\u003e2021;42(9):847-852.\\u003c/li\\u003e\\n\\u003cli\\u003eGirdwood M, Culvenor AG, Rio EK, et al. Tale of quadriceps and hamstring muscle strength after ACL reconstruction: a systematic review with longitudinal and multivariate meta-analysis. \\u003cem\\u003eBr J Sports Med. \\u003c/em\\u003e2024.\\u003c/li\\u003e\\n\\u003cli\\u003eGokeler A, Benjaminse A, Hewett TE, et al. Proprioceptive deficits after ACL injury: are they clinically relevant? \\u003cem\\u003eBr J Sports Med. \\u003c/em\\u003e2012;46(3):180-192.\\u003c/li\\u003e\\n\\u003cli\\u003eIngram JG, Fields SK, Yard EE, Comstock RD. Epidemiology of knee injuries among boys and girls in US high school athletics. \\u003cem\\u003eAm J Sports Med. \\u003c/em\\u003e2008;36(6):1116-1122.\\u003c/li\\u003e\\n\\u003cli\\u003eLegnani C, Del Re M, Vigan\\u0026ograve; M, et al. Relationships between Jumping Performance and Psychological Readiness to Return to Sport 6 Months Following Anterior Cruciate Ligament Reconstruction: A Cross-Sectional Study. \\u003cem\\u003eJ Clin Med. \\u003c/em\\u003e2023;12(2).\\u003c/li\\u003e\\n\\u003cli\\u003eLogerstedt D, Lynch A, Axe MJ, Snyder-Mackler L. Symmetry restoration and functional recovery before and after anterior cruciate ligament reconstruction. \\u003cem\\u003eKnee Surg Sports Traumatol Arthrosc. \\u003c/em\\u003e2013;21(4):859-868.\\u003c/li\\u003e\\n\\u003cli\\u003eLu Y, Chen P, Sheu H, et al. Fastball Quality After Ulnar Collateral Ligament Reconstruction in Major League Baseball Pitchers. \\u003cem\\u003eAm J Sports Med. \\u003c/em\\u003e2024;52(10):2611-2619.\\u003c/li\\u003e\\n\\u003cli\\u003eMai HT, Chun DS, Schneider AD, et al. Performance-Based Outcomes After Anterior Cruciate Ligament Reconstruction in Professional Athletes Differ Between Sports. \\u003cem\\u003eAm J Sports Med. \\u003c/em\\u003e2017;45(10):2226-2232.\\u003c/li\\u003e\\n\\u003cli\\u003eMajor League Baseball. MLB.com.\\u003c/li\\u003e\\n\\u003cli\\u003eMajor League Baseball. Statcast. June 9,2021.\\u003c/li\\u003e\\n\\u003cli\\u003eMangine GT, Hoffman JR, Vazquez J, et al. Predictors of fielding performance in professional baseball players. \\u003cem\\u003eInt J Sports Physiol Perform. \\u003c/em\\u003e2013;8(5):510-516.\\u003c/li\\u003e\\n\\u003cli\\u003eMigliorini F, Vecchio G, Eschweiler J, et al. Reduced knee laxity and failure rate following anterior cruciate ligament reconstruction compared with repair for acute tears: a meta-analysis. \\u003cem\\u003eJ Orthop Traumatol. \\u003c/em\\u003e2023;24(1):8.\\u003c/li\\u003e\\n\\u003cli\\u003eMizels J, Erickson B, Chalmers P. Current State of Data and Analytics Research in Baseball. \\u003cem\\u003eCurr Rev Musculoskelet Med. \\u003c/em\\u003e2022;15(4):283-290.\\u003c/li\\u003e\\n\\u003cli\\u003eMyklebust G, Bahr R. Return to play guidelines after anterior cruciate ligament surgery. \\u003cem\\u003eBr J Sports Med. \\u003c/em\\u003e2005;39(3):127-131.\\u003c/li\\u003e\\n\\u003cli\\u003ePaterno MV, Ford KR, Myer GD, Heyl R, Hewett TE. Limb asymmetries in landing and jumping 2 years following anterior cruciate ligament reconstruction. \\u003cem\\u003eClin J Sport Med. \\u003c/em\\u003e2007;17(4):258-262.\\u003c/li\\u003e\\n\\u003cli\\u003ePaterno MV, Rauh MJ, Schmitt LC, Ford KR, Hewett TE. Incidence of contralateral and ipsilateral anterior cruciate ligament (ACL) injury after primary ACL reconstruction and return to sport. \\u003cem\\u003eClin J Sport Med. \\u003c/em\\u003e2012;22(2):116-121.\\u003c/li\\u003e\\n\\u003cli\\u003ePaterno MV, Schmitt LC, Ford KR, et al. Biomechanical measures during landing and postural stability predict second anterior cruciate ligament injury after anterior cruciate ligament reconstruction and return to sport. \\u003cem\\u003eAm J Sports Med. \\u003c/em\\u003e2010;38(10):1968-1978.\\u003c/li\\u003e\\n\\u003cli\\u003ePowell JW, Barber-Foss KD. Injury patterns in selected high school sports: a review of the 1995-1997 seasons. \\u003cem\\u003eJ Athl Train. \\u003c/em\\u003e1999;34(3):277-284.\\u003c/li\\u003e\\n\\u003cli\\u003eRenstr\\u0026ouml;m PA. Eight clinical conundrums relating to anterior cruciate ligament (ACL) injury in sport: recent evidence and a personal reflection. \\u003cem\\u003eBr J Sports Med. \\u003c/em\\u003e2013;47(6):367-372.\\u003c/li\\u003e\\n\\u003cli\\u003eSchmitt LC, Paterno MV, Hewett TE. The impact of quadriceps femoris strength asymmetry on functional performance at return to sport following anterior cruciate ligament reconstruction. \\u003cem\\u003eJ Orthop Sports Phys Ther. \\u003c/em\\u003e2012;42(9):750-759.\\u003c/li\\u003e\\n\\u003cli\\u003eVentura A, Iori S, Legnani C, et al. Single-bundle versus double-bundle anterior cruciate ligament reconstruction: assessment with vertical jump test. \\u003cem\\u003eArthroscopy. \\u003c/em\\u003e2013;29(7):1201-1210.\\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\":\"info@researchsquare.com\",\"identity\":\"bmc-musculoskeletal-disorders\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"bmsd\",\"sideBox\":\"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://author-welcome.nature.com/12891\",\"title\":\"BMC Musculoskeletal Disorders\",\"twitterHandle\":\"BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"baseball, anterior cruciate ligament reconstruction, Major League Baseball, athletic performance metrics\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-9413563/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-9413563/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eObjectives:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eTo evaluate performance changes in Major League Baseball (MLB) fielders following anterior cruciate ligament reconstruction (ACLR) using advanced Statcast metrics related to baserunning, defense, and batting.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDesign:\\u003c/strong\\u003e \\u0026nbsp;Retrospective, case-control study\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eMLB fielders who underwent ACLR between 2015 and 2023 were identified through official MLB injury reports. Players with at least 100 plate appearances (PA) before and after surgery were included. A 1:2 matched control group was established based on position, batting stance, and pre-injury performance. Performance metrics were analyzed across baserunning (e.g., sprint speed, extra bases taken), defense (e.g., Ultimate Zone Rating, Defensive Runs Saved), and batting (e.g., On-base Plus Slugging, Weighted Runs Created Plus). Statistical analyses compared pre- and post-injury metrics within the study group and against controls.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eFourteen fielders met the inclusion criteria and were matched to 28 control players. Post-ACLR, the study group exhibited significant declines in sprint speed (-0.55 ft/sec, p = 0.04), extra bases taken (-0.34, p = 0.03), and Defensive Runs Saved (-3.93, p = 0.04). No significant differences were observed in batting metrics. The control group showed no comparable performance declines.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusion:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eACLR negatively impacts baserunning and defensive performance in MLB fielders, particularly in speed-related and agility-dependent metrics. However, batting metrics remained stable, suggesting a limited association with offensive performance impairment. These findings highlight the need for rehabilitation strategies that focus on mobility and defensive agility post-ACLR.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Performance after Anterior Cruciate Ligament Reconstruction in Major League Baseball Fielders\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2026-05-11 07:05:06\",\"doi\":\"10.21203/rs.3.rs-9413563/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2026-05-18T16:57:59+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"260156539667298299121826915500190711070\",\"date\":\"2026-04-28T16:15:14+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2026-04-28T07:49:50+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2026-04-18T10:38:58+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2026-04-18T10:38:07+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Musculoskeletal Disorders\",\"date\":\"2026-04-14T09:32:21+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-musculoskeletal-disorders\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"bmsd\",\"sideBox\":\"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://author-welcome.nature.com/12891\",\"title\":\"BMC Musculoskeletal Disorders\",\"twitterHandle\":\"BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"8cda1c72-368e-49ab-a3dd-2ba9fae8af60\",\"owner\":[],\"postedDate\":\"May 11th, 2026\",\"published\":true,\"recentEditorialEvents\":[{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2026-05-18T16:57:59+00:00\",\"index\":30,\"fulltext\":\"\"}],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-05-11T07:05:07+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2026-05-11 07:05:06\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-9413563\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-9413563\",\"identity\":\"rs-9413563\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}