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Pre- and within-season attendance forecasting in Major League Baseball: A random forest approach

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  • Steffen Q. Mueller

    (Chair for Economic Policy, University of Hamburg)

Abstract

This study explores the forecasting of Major League Baseball game ticket sales and identifies important attendance predictors by means of random forests that are grown from classification and regression trees (CART) and conditional inference trees. Unlike previous studies that predict sport demand, I consider different forecasting horizons and only use information that is publicly accessible in advance of a game or season. Models are trained using data from 2013 to 2014 to make predictions for the 2015 regular season. The static within-season approach is complemented by a dynamic month-ahead forecasting strategy. Out-of-sample performance is evaluated for individual teams and tested against least-squares regression and a naive lagged attendance forecast. My empirical results show high variation in team-specific prediction accuracy with respect to both models and forecasting horizons. Linear and tree-ensemble models, on average, do not vary substantially in predictive accuracy; however, OLS regression fails to account for various team-specific peculiarities.

Suggested Citation

  • Steffen Q. Mueller, 2018. "Pre- and within-season attendance forecasting in Major League Baseball: A random forest approach," Working Papers 065, Chair for Economic Policy, University of Hamburg.
  • Handle: RePEc:hce:wpaper:065
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    File URL: https://www.hced.uni-hamburg.de/WorkingPapers/HCED-065.pdf
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    More about this item

    Keywords

    Attendance; Major League Baseball; Random forest; Conditional forest; Sport demand; Sports forecasting; Ticket sales; Variable importance;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Z2 - Other Special Topics - - Sports Economics

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