(61) Days of rest and distance traveled may influence game outcomes in Division I women’s soccer

Purpose: Collegiate women soccer athletes play approximately 18 games over a 10-week competitive season. Often, athletes play 2 games per week with limited rest days between games. Additionally, these athletes must travel to half of their games. Rest days and travel may impact overall performance. Thus, the purpose of the present study was to identify the influence of number of rest days, distance traveled, and player load on game outcomes (i.e., wins, losses). Methods: Global positioning system (GPS) data obtained by the coaching staff of a Midwestern NCAA Division I women’s soccer program was retrospectively examined. Players wore the GPS integrated with heart rate (HR) analysis during all games through the 2023 season. From the GPS, player load was obtained. Distance traveled was calculated in miles from the home field to the field of the opponent for away games. For home games, the distance was entered as “0 miles”. The number of days between games was used as the number of rest days. Lastly, game outcomes were coded as follows: losses = 0 and wins = 1. Two games were removed from the analysis as the athletes flew to the location and one was removed as it resulted in a tie, thus the remaining 15 games were analyzed. Of the 15 games, the team finished with 10 wins, 5 losses. Binary logistic regression was used to identify the influence of player load, distance traveled, and rest days on game outcomes. Continuous variables were assessed for multicollinearity. Significance was set to p< 0.05. Results: Multicollinearity did not exist among any of the continuous variables; therefore, they were all included in the regression model. Distance traveled (β=-0.005; p< 0.001) and number of rest days (β=0.592; p=0.001) were identified as significant predictors of game outcomes while player load was not significant (β=-0.002; p=0.249). The model (β=-0.687; p< 0.001) was able to accurately predict 74.2% of the game outcomes (losses = 32.4%; wins = 94.5%). Conclusions: Results from the present study suggest distance traveled has a negative influence on game outcomes while the number of rest days is positive. Player load may not have been a significant predictor as player load may not be different in wins versus losses. While distance traveled and number of rest days may influence game outcomes, the current model did not accurately predict losses, thus caution should be used when applying the results of the present study. Practical Applications: It is recommended coaches adjust the intensity of practices with minimal rest days between games to give the athletes an opportunity to recover and be aware of the potential influence of the distance traveled. Acknowledgements: None