Betting models using AI: a review on ANN, SVM, and Markov chain

Aladár Kollár

MPRA Paper from University Library of Munich, Germany

Abstract: In today's modern world, sports generate a great deal of data about each athlete, team, event, and season. Many people, from spectators to bettors, find it fascinating to predict the outcomes of sporting events. With the available data, the sports betting industry is turning to Artificial Intelligence. Working with a great deal of data and information is needed in sports betting all over the world. Artificial intelligence and machine learning are assisting in the prediction of sporting trends. The true influence of technology is felt as it offers these observations in real-time, which can have an impact on important factors in betting. An artificial neural network is made up of several small, interconnected processors called neurons, which are similar to the biological neurons in the brain. In ANN framework, MLP, the most applicable NN algorithm, are generally selected as the best model for predicting the outcomes of football matches. This review also discussed another common technique of modern intelligent technique, namely Support Vector Machines (SVM). Lastly, we also discussed the Markov chain to predict the result of a sport. Markov chain is the sequence or chain from which the next sample from this state space is sampled.

Keywords: Artificial Intelligence; ANN; Betting; sports; SVM; Markov chain (search for similar items in EconPapers)
JEL-codes: C5 C55 C6 (search for similar items in EconPapers)
Date: 2021-03-21
New Economics Papers: this item is included in nep-big, nep-cmp, nep-ore and nep-spo
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