1. Relationship Between Training Workloads, Match Workloads, and Match Performance in Elite Netball.
- Author
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Simpson, Marni J., Jenkins, David G., Connick, Mark, and Kelly, Vincent G.
- Subjects
PHYSICAL training & conditioning ,BASKETBALL ,EMPLOYEES' workload ,EXERCISE intensity ,BODY movement ,EXERCISE ,HEART beat ,ATHLETIC ability ,ALGORITHMS ,MOTOR ability - Abstract
Purpose: This study examined the relationships between training workloads, game workloads, and match performance in an elite netball team. Methods: Ten elite female netball athletes were monitored over a complete season. Training and game external workloads were determined through inertial movement units and expressed as absolute PlayerLoad (PL) and change of direction (COD). Monthly workload and training efficiency index were also calculated, which used internal workloads (session rating of perceived exertion and summated heart-rate zones). Game performance was assessed through a performance analysis statistic algorithm called NetPoints. To account for the influence of team game workloads on each other, the average workload for midcourt positions (avgMC) was calculated for each game. Data for each athlete were transformed into z scores, and linear mixed modeling was used to build models to examine the relationships between workloads and game performance. Results: Monthly PL, training efficiency index PL, and avgMC PL were statistically significant (P <.05) and positively related to game PL (z = 0.20–0.35, P <.001–.02). For game COD, statistically significant positive relationships were found between monthly COD (z = 0.29 [0.11], P =.01) and avgMC COD (z = 0.21 [0.09], P =.03). The models for NetPoints found significant negative relationships with monthly PL (z = 0.46 [0.12], P <.001) and COD (z = −0.36 [0.11], P =.01). Conclusions: Higher monthly workloads are related to higher game workload; however, they are also related to decreases in match performance. Therefore, netball practitioners should consider that increases to training workload in a 4-week period prior to a game can influence game workloads and performance. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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