Functional ratings in sports

Lowery Brad (), Slater Abigail and Thies Kaison
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Lowery Brad: Department of Mathematics, University of Sioux Falls, 1101 W 22nd St, Sioux Falls, 57105-1699, SD, USA
Slater Abigail: Department of Mathematics, University of Sioux Falls, 1101 W 22nd St, Sioux Falls, 57105-1699, SD, USA
Thies Kaison: Department of Mathematics, University of Sioux Falls, 1101 W 22nd St, Sioux Falls, 57105-1699, SD, USA

Journal of Quantitative Analysis in Sports, 2020, vol. 16, issue 3, 183-191

Abstract: In this paper, we present a new model for ranking sports teams. Our model uses all scoring data from all games to produce a functional rating by the method of least squares. The functional rating can be interpreted as a team average point differential adjusted for strength of schedule. Using two team’s functional ratings we can predict the expected point differential at any time in the game. We looked at three variations of our model accounting for home-court advantage in different ways. We use the 2018–2019 NCAA Division 1 men’s college basketball season to test the models and determined that home-court advantage is statistically important but does not differ between teams.

Keywords: basketball; least squares; linear regression; NCAA; rankings (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1515/jqas-2020-0001

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