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Scoring and Shooting Abilities of NBA Players

Author

Listed:
  • Piette James

    (University of Pennsylvania)

  • Anand Sathyanarayan

    (University of Pennsylvania)

  • Zhang Kai

    (University of Pennsylvania)

Abstract

We propose two new measures for evaluating offensive ability of NBA players, using one-dimensional shooting data from three seasons beginning with the 2004-05 season. These measures improve upon currently employed shooting statistics by accounting for the varying shooting patterns of players over different distances from the basket. This variance also provides us with an intuitive metric for clustering players, wherein performance of players is calculated and compared to his cluster center as a baseline. To further improve the accuracy of our measures, we develop our own variation of smoothing and shrinkage, reducing any small sample biases and abnormalities.The first measure, SCAB or, Scoring Ability Above Baseline, measures a player's ability to score as a function of time on court. The second metric, SHTAB or Shooting Ability, calculates a player's propensity to score on a per-shot basis. Our results show that a combination of SCAB and SHTAB can be used to separate out players based on their offensive game. We observe that players who are highly ranked according to our measures are regularly considered as top performers on offense by experts, with the notable exception of LeBron James; the same claim holds for the offensive dregs. We suggest possible explanations for our findings and explore possibilities of future work with regard to player defense.

Suggested Citation

  • Piette James & Anand Sathyanarayan & Zhang Kai, 2010. "Scoring and Shooting Abilities of NBA Players," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(1), pages 1-25, January.
    • Handle: RePEc:bpj:jqsprt:v:6:y:2010:i:1:n:1
    DOI: 10.2202/1559-0410.1194
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    Cited by:

    1. Aaron D. Hill & Federico Aime & Jason W. Ridge, 2017. "The performance implications of resource and pay dispersion: The case of Major League Baseball," Strategic Management Journal, Wiley Blackwell, vol. 38(9), pages 1935-1947, September.
    2. Marco Sandri & Paola Zuccolotto & Marica Manisera, 2020. "Markov switching modelling of shooting performance variability and teammate interactions in basketball," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1337-1356, November.
    3. Seong W. Kim & Sabina Shahin & Hon Keung Tony Ng & Jinheum Kim, 2021. "Binary segmentation procedures using the bivariate binomial distribution for detecting streakiness in sports data," Computational Statistics, Springer, vol. 36(3), pages 1821-1843, September.
    4. Scott D. Grimshaw & Jeffrey S. Larson, 2021. "Effect of Star Power on NBA All-Star Game TV Audience," Journal of Sports Economics, , vol. 22(2), pages 139-163, February.

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