The Value of Statistics Contributing to Scoring in the NBA: A Quantitative Approach

Jim Lackritz and Ira Horowitz

The American Economist, 2021, vol. 66, issue 2, 175-189

Abstract: We model three years of National Basketball Association (NBA) data to calculate the number of points generated from assists, offensive rebounds, and steals. We partition the data into eight groups based on the combinations of occurrences (or not) of these three statistics in a made basket. A linear programming model solves for the coefficients of each of the three statistics in each combination, and the weighted average of the coefficients by combination frequency produces a final value for the points generated by each statistic. A fraction of these points is assigned to the player that made the assist, offensive rebound, or steal, with the remaining portion of the points scored assigned to the scorer. A scale for total points accounted for by a player from points scored, assists, offensive rebounds, and steals is developed and used to compare the offensive production of a sample of NBA players from the 2018–2019 season. JEL Classifications : C1, C3,C6, Z2

Keywords: offensive performance metric; linear programming; point allocation (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:sae:amerec:v:66:y:2021:i:2:p:175-189

DOI: 10.1177/0569434520968477

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