BACKGROUND: External workload is the amount of physical work performed, calculated as acute chronic workload ratio (ACWR) and categorized as low, sweet spot, overreaching, and high based on ACWR values. ACWR represents a state of fatigue over preparation and values outside the sweet spot reportedly increase injury risk. Workload management (WM) is the application of workload data to adjust training to maximize performance and minimize injury risk. The purpose was to determine if the number of injured players and team average workload is related to a WM strategy decided upon and implemented by the coaching staff in a Division I men’s soccer program. METHODS: Global positioning system variables (total distance, sprint distance, power plays, work ratio, and player load) and injuries requiring medical attention and loss of participation, were collected for 46 participants (height=178.9±5.8cm, mass=75.2±6.22kg) over two consecutive competitive seasons (2021-22). Rolling average ACWR (RAACWR) and exponentially weighted ACWR (EWACWR) were calculated for each external workload variable for individual participants and as team weekly averages. Season 1: variables were analyzed but WM was not applied. Season 2: variables were analyzed and individual and team data were reported to the coaches who made WM adjustments. In both seasons, the number of times the team’s average RAACWR and EWACWR variables were categorized as “sweet spot” and the number of injured participants were counted and compared using Chi Square Tests of Independence. RESULTS: There was a relationship between the number of RAACWR sweet spot variables and seasons, X2(1, 85) = 4.0, p=0.046, with 60% (27/45) in 2021 and 80% (32/40) in 2022. There was a relationship between the number of EWACWR sweet spots variables and seasons, X2(1, 125) = 12.0, p<0.001, with 29% (19/65) in 2021 and 60% (36/60) in 2022. There was no relationship between the number of injured players and seasons, X2(1, 46) = 0.35, p=0.55, where 35% (8/23) and 48% (11/23) of the players were injured in seasons 2021 and 2022, respectively. CONCLUSIONS: Workload differed between seasons, however, this did not translate to a difference in the number of injured players. The coaching staff effectively applied the workload data to manage external demands and theoretically benefit participant physical performance over time. Further studies examining WM implementation strategies are needed.

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