Demonstrates that offensive efficiency, not frequency, predicts success in NBA teams.
The present study examined whether offensive play-type indicators in professional basketball reflect broader latent playing-style dimensions and whether play-type usage or efficiency is more strongly associated with competitive success. Data were obtained from the official NBA statistics website and included 6400 games across five seasons (2019–2020 to 2023–2024), comprising 5979 regular-season games and 421 playoff games. For each offensive play type, two indicators were analysed separately: usage percentage and efficiency, operationalised as points per possession (PPP). Principal component analyses were conducted independently for regular-season and playoff data, and for usage and efficiency variables. In addition, linear mixed-effects models were used to examine the relationship between play-type indicators and competitive success while accounting for games nested within teams. Only regular-season efficiency variables showed adequate sampling adequacy for factorial analysis (KMO = 0.774), yielding a four-component solution that explained 58.85% of the total variance. In the mixed-effects models, usage variables were not significantly associated with success, whereas efficiency indicators showed greater explanatory value. Specifically, pick-and-roll ball handler PPP and spot-up PPP emerged as the strongest positive predictors of success, with smaller effects observed for roll-man PPP and cut PPP. The efficiency-only model improved model fit relative to the frequency-only model (marginal R2 = 0.799 vs. 0.755), whereas adding usage variables to efficiency provided only a negligible additional contribution (marginal R2 = 0.803). These findings suggest that, in the NBA, competitive success is more closely related to the effectiveness with which offensive actions are executed than to the relative frequency with which they are used. From an applied perspective, play-type efficiency appears to provide more actionable information than usage-based summaries for performance analysis and tactical decision-making.
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Borrega-Solano et al. (2026) studied this question.
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