Comparing the performance of machine learning and statistical models in predicting football games
DOI:
https://doi.org/10.47611/jsr.v12i4.2201Keywords:
sports analytics， betting，predict，specific games，algorithms， models，random forest classifiers，Poisson regressionAbstract
In the realms of sports analytics and betting, the ability to accurately predict the outcome of specific games has been a particular subject of interest that has undergone intense research and development. In recent years, with the widespread distribution of technology and online resources, the utilization of algorithms and models has gradually become more prevalent in sports forecasting as they are able to consume and interpret high volumes of data, far beyond the capacity of humans. Algorithms such as random forest classifiers and Poisson regression have stood out in particular, each with its own strengths and limitations.
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El, Jari. "Historical Developments of Random Forest." Medium, 24 July 2020, drjariel.medium.com/historical-developments-of-random-forest-41492deb6737. Accessed 4 Aug. 2023.
Emons, Michael. "Burnley 1-2 Newcastle: Callum Wilson Scores Twice as Clarets Are Relegated to Championship." BBC, 22 May 2022, www.bbc.com/sport/football/61453542. Accessed 5 Aug. 2023.
"Ensemble methods." scikit-learn, scikit-learn.org/stable/modules/ensemble.html. Accessed 5 Aug. 2023.
"A History of Brentford FC." Brentford F.C., www.brentfordfc.com/en/history. Accessed 5 Aug. 2023.
"How has the COVID-19 pandemic affected Premier League matches?" Premier League, 15 June 2020, www.premierleague.com/news/1682374. Accessed 5 Aug. 2023.
Morgan, Tom, et al. "Newcastle United takeover confirmed as £305m deal with Saudi-backed consortium finalised." The Telegraph, 7 Oct. 2021, www.telegraph.co.uk/football/2021/10/07/newcastle-united-takeover-live-saudi-buyers-announcement-latest/. Accessed 5 Aug. 2023.
Newcastle United Transfers 21/22. Transfermarkt, www.transfermarkt.com/newcastle-united/transfers/verein/762/saison_id/2021. Accessed 5 Aug. 2023.
Poisson, Siméon-Denis. Recherches sur la probabilité des jugements en matière criminelle et en matière civile. Paris, Bachelier, 1837. La Bibliotheque nationale de France, gallica.bnf.fr/ark:/12148/bpt6k110193z/f6.item#. Accessed 4 Aug. 2023.
R, Sruthi E. "Understand Random Forest Algorithms With Examples (Updated 2023)." Analytics Vidhyan, 17 June 2021, www.analyticsvidhya.com/blog/2021/06/understanding-random-forest/. Accessed 4 Aug. 2023.
Roback, Paul, and Julie Legler. Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in. E-book ed., Boca Raton, CRC Press, 2021.
Sheehan, David. "Predicting Football Results With Statistical Modelling: Dixon-Coles and Time-Weighting." GitHub, 13 Sept. 2018, dashee87.github.io/football/python/predicting-football-results-with-statistical-modelling-dixon-coles-and-time-weighting/. Accessed 5 Aug. 2023.
"Statistical functions (scipy.stats)." SciPy, docs.scipy.org/doc/scipy/reference/stats.html. Accessed 5 Aug. 2023.
Visualization of a Random Forest Model Making a Prediction. Medium, towardsdatascience.com/understanding-random-forest-58381e0602d2. Accessed 5 Aug. 2023.
Yiu, Tony. "Understanding Random Forest." Medium, 12 June 2019, towardsdatascience.com/understanding-random-forest-58381e0602d2. Accessed 4 Aug. 2023.
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