Efficiency and productivity evaluation of basketball players' performance

Abstract Aim: Basketball players' performances have been traditionally summarized in indices that rely on the game-related statistics (e.g. rebounds, field goals, etc). Indices are defined according to different methods (e.g. Efficiency Index - Ei, Plus-Minus, Wins Produced), seeking distinct analytic objectives. Ei is frequently used given its simplicity. However, it has questionable validity since it measures productivity instead of efficiency and uses biased calculations for scoring. This study aimed to define indices of efficiency (Basketball Efficiency Index (BEi)) and productivity (Basketball Productivity Index (BPi)) of a player's contribution to the team performance with greater validity than Ei. Methods: We gathered public NBA game-related statistics (2014/2015 - 2018/2019). We analyzed: Ei's and BEi's winning prediction accuracy; Ei's and BEi's point spread prediction accuracy; the correlation between GRS and Ei, BEi, BPi, and PER; players' rank correlation between indices. Results: In comparison to Ei, both BEi and BPi reduced the weight of points scored on the final value. Less reliance on points scored results in a more accurate comparison of the contribution of players independent of their tactical roles. Conclusion: These indices may improve coaches' understanding of the real contribution of each player to team performance.

Relationship between physical fitness and game-related statistics in elite professional basketball players: Regular season vs. playoffs

AIMS This study aimed to verify th erelation ship between of anthropometric and physical performance variables with game-related statistics in professional elite basketball players during a competition. METHODS Eleven male basketball players were evaluated during 10 weeks in two distinct moments (regular season and playoffs). Overall, 11 variables of physical fitness and 13 variables of game-related statistics were analysed. RESULTS The following significant Pearson's correlations were found in regular season: percentage of fat mass with assists (r = -0.62) and steals (r = -0.63); height (r = 0.68), lean mass (r = 0.64), and maximum strength (r = 0.67) with blocks; squat jump with steals (r = 0.63); and time in the T-test with success ful two-point field-goals (r = -0.65), success ful free-throws (r = -0.61), and steals (r = -0.62). However, in playoffs, only stature and lean mass maintained these correlations (p ≤ 0.05). CONCLUSIONS The anthropometric and physical characteristics of the players showed few correlations with the game-related statistics in regular season, and these correlations are even lower in the playoff games of a professional elite Champion ship, wherefore, not being good predictors of technical performance.(AU)