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Closed vs. Open-Skill Contexts in Basketball: Insights into Reactive and Nonreactive Short Distance Sprint
Asaf Shalom1, Roni Gottlieb2, Julio Calleja-Gonzalez3
1Department of Physical Education, The Research Center for Sports and Physical Activity, Tel Hai Academic College, Kiryat Shmona 1220800, Israel.
Sports (Basel, Switzerland)
|March 27, 2026
Summary
Basketball players sprint slower in unpredictable (open-skill) conditions compared to predictable (closed-skill) ones. Player rankings also vary significantly between these sprint types, highlighting distinct performance profiles.
Area of Science:
- Sports Science
- Biomechanics
- Motor Control
Background:
- Basketball performance relies on short-distance sprints under predictable (closed-skill) and unpredictable (open-skill) conditions.
- Understanding sprint differences is crucial for player development and talent identification.
Purpose of the Study:
- Compare sprint performance in closed-skill versus open-skill conditions in young male basketball players.
- Analyze sprint times across different distances and assess the interaction between condition and distance.
- Evaluate the consistency of player rankings across sprint conditions.
Main Methods:
- 37 male basketball players (aged 16-18) performed 5m and 10m sprints in both closed- and open-skill formats.
- Repeated-measures ANOVA and paired-samples t-tests analyzed performance differences.
- Correlation analyses examined the consistency of player rankings between conditions.
Main Results:
- Sprint times were significantly slower in open-skill conditions (p < 0.001) at both 5m and 10m distances.
- No significant interaction was found between sprint condition and distance.
- Player rankings showed low consistency between closed- and open-skill sprints.
Conclusions:
- Open-skill sprinting in basketball involves a unique blend of physical acceleration and perceptual-cognitive processing.
- Reactive sprint assessments are recommended for a more comprehensive evaluation of explosive speed in basketball.
- Performance in predictable sprints does not reliably predict performance in unpredictable scenarios.
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