Seasonal accumulated workloads in collegiate men's soccer: a comparison of starters and reserves. J Strength Cond Res 35(11): 3184-3189, 2021-The purpose of this investigation was to quantify and compare player's season total-, match-, and trainingaccumulated workload by player status characteristics (i.e., starter vs. reserve) in American collegiate men's soccer. Global positioning system (GPS) and heart rate (HR)-derived workloads were analyzed from 82 collegiate male soccer athletes from 5 separate teams over the 2016 and 2017 seasons. Differences in total physical and physiological workloads (i.e., total distance, accelerations, and weighted HR-zone training impulse [TRIMP] score) as well as workloads over a range of intensity zones were examined using multilevel mixed models, with mean difference (MD) and effect size (ES) reported. Starters accumulated substantially more total distance (MD 5 82 km, ES 5 1.23), TRIMP (MD 5 2,210 au, ES 5 0.63), and total accelerations (MD 5 6,324 n, ES 5 0.66) over the season. Total accumulated distance in all velocity zones (ES [range] 5 0.87-1.08), all accelerations zones (ES [range] 5 0.54-0.74), and time spent at 70-90% HRmax (ES [range] 5 0.60-1.12) was also greater for starters. Reserves accumulated substantially more total distance (MD 5 20 km, ES 5 0.43) and TRIMP (MD 5 1,683 au, ES 5 0.79) during training. Although reserves show elevated physical and physiological loads during training compared with starters, there is an imbalance in overall workloads between player roles, with starters incurring substantially more match and total seasonal workloads. These results indicate managing player workloads in soccer requires attention to potential imbalances between players receiving variable match times. Coaches and practitioners in collegiate men's soccer may consider implementing strategies to reduce discrepancies in loading between starters and reserves. Individualized monitoring of training and match workloads may assist in the implementation of more balanced load management programs.

Curtis, RM, Huggins, RA, Benjamin, CL, Sekiguchi, Y, Adams, WM, Arent, SM, Jain, R, Miller, SJ, Walker, AJ, and Casa, DJ. Contextual factors influencing external and internal training loads in collegiate men's soccer. J Strength Cond Res 34(2): 374–381, 2020—This study investigated factors influencing training loads (TL) in collegiate men's soccer. Total distance, high-speed running distance (>14.4 km·h−1), high-intensity heart-rate zone duration (HI HRZ, >70% heart rate relative to maximum), and session rating of perceived exertion were assessed daily from 107 male soccer players competing for 5 National Collegiate Athletics Association Division I teams. Differences between athlete role (starter and reserve), position (defender, midfielder, and forward), season phase (preseason, in-season, and postseason), days relative to match (MD-1 to MD-5+), days between matches (<4, 4–5, >5 days), previous match outcome (win, loss, and draw), and upcoming opponent relative ranking (weaker, trivial, and stronger) were examined. Mean differences (MD) and effect sizes (ESs) with 90% confidence intervals were reported. There were trivial and insignificant differences by player role, position, or upcoming opponent strength, and small-moderate increases in preseason TL compared with in-season (ES [range] = 0.4–0.9). TLs were lower for MD-1 and higher for MD-5+ (ES [range] = 0.4–1.3) when compared with MD-2-4. External loads (ES = −0.40 ± 0.20) were less after wins compared with losses. TLs are increased in the preseason, when training sessions occur greater than 5 days from a match and after losses. Contextualizing factors affecting TLs has implications for developing workload prescription and recovery strategies.

Heat acclimation (HA) is the process of intentional and consistent exercise in the heat that results in positive physiological adaptations, which can improve exercise performance both in the heat and thermoneutral conditions. Previous research has indicated the many performance benefits of HA, however, a meta-analysis examining the magnitude of different types of performance improvement is absent. Additionally, there are several methodological discrepancies in the literature that could lead to increased variability in performance improvement following HA and no previous study has examined the impact of moderators on performance improvement following HA. Therefore, the aim of this study was two-fold; (1) to perform a meta-analysis to examine the magnitude of changes in performance following HA in maximal oxygen consumption (VO2max), time to exhaustion, time trial, mean power, and peak power tests; (2) to determine the impact of moderators on results of these performance tests. Thirty-five studies met the inclusion/exclusion criteria with 23 studies that assessed VO2max (n = 204), 24 studies that assessed time to exhaustion (n = 232), 10 studies that performed time trials (n = 101), 7 studies that assessed mean power (n = 67), and 10 papers that assessed peak power (n = 88). Data are reported as Hedge's g effect size (ES), and 95% confidence intervals (95% CI). Statistical significance was set to p < 0.05, a priori. The magnitude of change following HA was analyzed, with time to exhaustion demonstrating the largest performance enhancement (ES [95% CI], 0.86 [0.71, 1.01]), followed by time trial (0.49 [0.26, 0.71]), mean power (0.37 [0.05, 0.68]), VO2max (0.30 [0.07, 0.53]), and peak power (0.29 [0.09, 0.48]) (p < 0.05). When all of the covariates were analyzed as individual models, induction method, fitness level, heat index in time to exhaustion (coefficient [95% CI]; induction method, −0.69 [−1.01, −0.37], p < 0.001; fitness level, 0.04 [0.02, 0.06], p < 0.001; heat index, 0.04 [0.02, 0.07], p < 0.0001) and induction length in mean power (coefficient [95% CI]; induction length 0.15 [0.05, 0.25], p = 0.002) significantly impacted the magnitude of change. Sport scientists and researchers can use the findings from this meta-analysis to customize HA induction. For time to exhaustion improvements, HA implementation should focus on induction method and baseline fitness, while the training and recovery balance could lead to optimal time trial performance.

Background: Sleep and mood are critical factors that contribute to health and wellness and are of particular interest to collegiate athletes who are juggling high physical, academic, and social demands. The aim of this study was to examine how psychological measures, player status, and sex-related factors were associated with perceived sleep quality. Hypothesis: Higher levels of global sleep dysfunction will be related to poor mood and increased anxiety, and there will be differences in sleep dysfunction in male compared with female athletes as well as regarding playing status. Study Design: Prospective cohort study. Level of Evidence: Level 4. Methods: During the 2016 through 2018 National Collegiate Athletic Association (NCAA) seasons, the Pittsburgh Sleep Quality Index (PSQI), Profile of Mood States, and Sports Anxiety Scale–2 questionnaires were administered to 230 soccer athletes at 6 separate time points throughout each season. Results: PSQI results yielded scores ≥5 in 54% of observations. Increased sleep dysfunction was significantly related to decreased vigor and increased tension, depression, anger, fatigue, somatic anxiety, worry, and concentration disruption, although effect sizes (ES) were trivial (ES, –0.03 to 0.15). The odds ratio (OR) of reporting global sleep dysfunction increased by 8%, 9%, and 25% for every 1-unit increase in tension (OR, 1.08; 95% CI, 1.02-1.16; P = 0.015), fatigue (OR, 1.09; 95% CI, 1.03-1.16; P = 0.002), and concentration disruption (OR, 1.25; 95% CI, 1.09-1.45; P = 0.002), respectively. The odds of reporting global sleep dysfunction were 55% lower for males than females (OR, 0.45; 95% CI, 0.25-0.79; P = 0.006). Conclusion: Global sleep dysfunction was prevalent in NCAA soccer players and was related to negative mental health outcomes. Female participants experienced increased odds of reporting global sleep dysfunction. Clinical Relevance: Regular monitoring allows for a greater understanding of the interrelatedness between sleep and mental health in athletes.