Basketball game-related statistics that discriminate between European players competing in the NBA and in the Euroleague
Author | Affiliation | |||
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LT | Lietuvos sporto universitetas | LT | ||
Masiulis, Nerijus | Lietuvos sporto universitetas | LT | ||
Vaquera, Alejandro | University of Leon | ES | ||
Date |
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2018 |
This study aimed to identify the game-relat ed statistics that discriminated between Euroleague basketball players and European basketball players playing in the NBA, when competing in the same event (EuroBasket 2015). There was a total of 78 matches played by 24 teams in two groups of analysis: NBA, participants in the European Championship wh o played in the NBA season of 2014-2015 (n = 26); Euroleague, participants in the European Championship who played in the Euroleague season of 2014-2015 (n = 82). The players’ performance variables were normaliz ed to the time they spent on the court. To identify which variables best discriminated between the NBA an d the Euroleague performanc e profiles, a descriptive discriminant analysis was conducted. Structure coeffici ents (SC) from the matrix greater than |0.30| were interpreted as meaningful contributors to discrimi nating between the groups. The results revealed a significant function ( p = 0.008, canonical correlation of 0.51, Λ = 0.74, reclassification = 84.2%) and substantial performance differences in game-related statistics much related to the influence of body size (body height and mass), such as two-point field goals made (SC = 0.42) and missed (SC = 0.40), free-throws made (SC = 0.55), defensive rebounds (SC = 0.62), blocks (SC = 0.48) and suffered fouls (SC = 0.34). No differences were found at the level of game-related statistics indirectly related to perception, such as assists, turnovers or steals. Also, the greater body size in NBA players was likely related to higher variability in performance, thus, being an important topic for coaches and recruiters to analyse.
Journal | IF | AIF | AIF (min) | AIF (max) | Cat | AV | Year | Quartile |
---|---|---|---|---|---|---|---|---|
Journal of Human Kinetics | 1.414 | 2.883 | 2.883 | 2.883 | 1 | 0.49 | 2018 | Q3 |
Journal | IF | AIF | AIF (min) | AIF (max) | Cat | AV | Year | Quartile |
---|---|---|---|---|---|---|---|---|
Journal of Human Kinetics | 1.414 | 2.883 | 2.883 | 2.883 | 1 | 0.49 | 2018 | Q3 |
Journal | Cite Score | SNIP | SJR | Year | Quartile |
---|---|---|---|---|---|
Journal of Human Kinetics | 2.2 | 1.02 | 0.644 | 2018 | Q2 |