A comprehensive survey of the home advantage in American football
Author:
Affiliation:
1. Department of Biostatistics , Harvard T. H. Chan School of Public Health 1857 , Boston , MA , USA
2. National Football League , New York , NY , USA
Abstract
Publisher
Walter de Gruyter GmbH
Link
https://www.degruyter.com/document/doi/10.1515/jqas-2024-0016/pdf
Reference48 articles.
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2. Benz, L.S. and Lopez, M.J. (2023). Estimating the change in soccer’s home advantage during the Covid-19 pandemic using bivariate Poisson regression. AStA Adv. Stat. Anal. 107: 205–232, https://doi.org/10.1007/s10182-021-00413-9.
3. Boulier, B. and Stekler, H.O. (2003). Predicting the outcomes of National League Football games. Int. J. Forecast. 19: 257–270, https://doi.org/10.1016/s0169-2070(01)00144-3.
4. Brooks, S.P. and Gelman, A. (1998). General methods for monitoring convergence of iterative simulations. J. Comput. Graph. Stat. 7: 434–455, https://doi.org/10.2307/1390675.
5. Carl, S. and Baldwin, B. (2023). nflfastR: functions to efficiently access NFL play by play data, Available at: .
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