Hannah Nelson1, Katie Pierce2, Paul Loprinzi1, Matthew Jessee1, Chas Ossenheimer1, Melinda Valliant1, Thomas Andre1. 1University of Mississippi, Oxford, MS. 2University of Tennessee, Knoxville, TN.

BACKGROUND: Monitoring the workload of athletes in both an individual and team setting has become common practice. This practice can look different depending on the physical demands of the sport. In volleyball, an inertial measurement unit known as Vert can be utilized to track the number of jumps and other jump-related variables performed by players. Other ways in which jump frequency can be estimated are needed for teams and players without Vert. This study aimed to determine if volleyball athletes can accurately predict the number of jumps they perform after training and match play when given a perceptual scale. A secondary aim of this study was to determine if player position, session rating of perceived exertion (sRPE), and perceived sets played affected the player’s accuracy when predicting jump count. METHODS: Thirteen female NCAA DI volleyball players competing on a team in the Southeastern Conference participated in this study. A survey was given following each practice and match and asked for sRPE, perceived sets played, jump count, and any self-counting of jumps. Around fifteen minutes before the end of each practice and match, the participants received the questionnaire as an automated message on their phones through the MyTeams app. Analytical workload data was collected via Vert worn during practices and matches in a waistband. Accuracy of the players' jump range selection was done by block coding. Generalized estimating equations (GEE) were used to determine if each player’s jump count accuracy differed based on player position, sRPE, or perceived sets played. RESULTS: It was found that 23.2% of the team’s jump count range estimations were accurate within 25 jumps of the actual number performed. 58% of the player’s responses were accurate within 50 jumps of the actual number performed. Position was the only variable to associate (p<0.001, r=0.263) with player jump count accuracy with setters being the least accurate (10.8%) and liberos being the most accurate (32.8%). CONCLUSIONS: Based on these results, a subjective perceptual scale may be worth further exploration, however, adjustments may be needed on the perceived jump count scale to improve accuracy among positions.

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