EVALUATION OF ATHLETE LOAD AND RELATIONSHIP BETWEEN EQUATION VARIABLES IN DIVISION I WOMEN’S LACROSSE
Andrew Thornton, Jennifer A. Bunn, FACSM. Sam Houston State University, Huntsville, TX.
BACKGROUND: Athlete monitoring systems have developed proprietary algorithms to create a generalized “load” score for athletes. This score, measured in arbitrary units (AU) typically includes external load variables, but there are inconsistencies of definitions found in the field surrounding this term and the proprietary nature of the calculation by device manufacturers. The primary purpose of this study was to evaluate the proprietary metric from VX Sport, Athlete Load (AL), for collegiate women’s lacrosse across different positions, and compare training to games. A secondary purpose was to evaluate the relationship between AL and the equation variables [duration total, total distance, high-intensity distance (HID), and total sprints] and session rating of perceived exertion. METHODS: Global positioning system units and heart rate monitors were worn by athletes (n = 22) during 104 training sessions and nine games. Data were uploaded to VX Sport Software where it was trimmed to remove any downtime during the recorded session as accurately as possible. RESULTS: Analyses indicated no differences (p = 0.186) between training AL (48.0 ± 5.8 AU) and game AL (57.7 ± 32.8 AU), along with no positional differences (p = 0.913) between the attackers (training: 49.5 ± 5.6 AU; game: 55.7 ± 37.0 AU), midfielders (training: 49.4 ± 7.4 AU; game: 58.9 ± 33.2 AU), and defenders (training: 45.6 ± 5.8 AU; game: 58.9 ± 32.4 AU). Correlation analyses between equation variables indicated strong correlations during training for HID (r = 0.75), and sprints (r = 0.83) all p < 0.001; with games showing strong correlation with distance (r = 0.84) and HID (r = 0.80), all p < 0.001. CONCLUSIONS: The data suggests there is no difference between training and games. This is likely a result of differences in playing time with athletes that experience less time on the field bringing the mean score down. Furthermore, the data shows that HID and sprints contribute more to AL during training whereas distance and HID contribute more during games. A likely explanation for this is due to more distance being covered in games than practice by each athlete and the nature of practices, with the drills performed requiring a high number of sprints. Additionally, there is more time spent in HID during games however, it is over a longer period of time essentially making the ratio of time spent in HID during training even to that of games.
Thornton, A and Bunn, FACSM, JA
"EVALUATION OF ATHLETE LOAD AND RELATIONSHIP BETWEEN EQUATION VARIABLES IN DIVISION I WOMEN’S LACROSSE,"
International Journal of Exercise Science: Conference Proceedings: Vol. 16:
1, Article 215.
Available at: https://digitalcommons.wku.edu/ijesab/vol16/iss1/215