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The Journal of sports medicine and physical fitness · 2023

Investigating the effects of athlete-reported pre-training well-being and recovery on subsequent training loads in basketball players.

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Sansone Pierpaolo, Conte Daniele, Li Feng, Tessitore Antonio

Аннотация

BACKGROUND: Basketball players' external and internal training loads have been extensively monitored. However, no study has evaluated if pre-training athlete-reported conditions influence them. Therefore, this study investigated the effects of athlete-reported pre-training well-being and recovery on subsequent external load intensity, perceived exertion scores and their ratio (efficiency index) in youth basketball training.

METHODS: The external load (EL) intensity (EL∙min-1), ratings of perceived exertion (RPE) and efficiency index (EL∙min-1:RPE) of 15 youth basketball players (age: 15.2±0.3 years) were monitored during team-based training sessions. Before each session, players reported their levels of perceived recovery (using a modified 10-point Total Quality Recovery, TQR, scale), fatigue, sleep quality, muscle soreness, mood, and stress. Statistical analyses were performed via linear mixed models.

RESULTS: EL∙min-1 was higher when player reported better pre-training recovery (P= 0.001). Higher RPE scores and lower efficiency indexes were registered in players reporting better pre-training conditions, respectively. Specifically, RPE scores were higher when players reported better TQR, fatigue, muscle soreness and stress scores (all P<0.05), while training efficiency was, conversely, lower in correspondence of better TQR and sleep (all P<0.05).

CONCLUSIONS: This study identified influences of athlete-reported pre-training well-being and recovery on subsequent external intensity, RPE and efficiency index in youth basketball players. Recovery and well-being indicators could be monitored seen their influence on subsequent training loads. Current findings can be considered by basketball sport scientist when selecting athlete monitoring questionnaires and when interpreting training load outputs.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты