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Exploiting sports-betting market using machine learning
16 references·0 citing·40 second hop
Exploiting sports-betting market using machine learning (2019)Exploiting sports-betting market using ma…Efficiency of online football betting markets (2018)Efficiency of online football…A bivariate Weibull count model for forecasting association football scores (2017)A bivariate Weibull count mod…Profiting from an inefficient association football gambling market: Prediction, risk and uncertainty using Bayesian networks (2013)Profiting from an inefficient…A Review of Data Mining Techniques for Result Prediction in Sports (2013)A Review of Data Mining Techn…DOES SPORTSBOOK.COM SET POINTSPREADS TO MAXIMIZE PROFITS? (2012)DOES SPORTSBOOK.COM SET POINT…The use of data mining for basketball matches outcomes prediction (2010)The use of data mining for ba…Prediction accuracy of different market structures — bookmakers versus a betting exchange (2010)Prediction accuracy of differ…Issues in sports forecasting (2010)Issues in sports forecastingPredicting NBA Games Using Neural Networks (2009)Predicting NBA Games Using Ne…Sports forecasting: a comparison of the forecast accuracy of prediction markets, betting odds and tipsters (2008)Sports forecasting: a compari…A Starting Point for Analyzing Basketball Statistics (2007)A Starting Point for Analyzin…Odds-setters as forecasters: The case of English football (2005)Odds-setters as forecasters: …Why are Gambling Markets Organised so Differently from Financial Markets? (2004)Why are Gambling Markets Orga…Forecasting sport: the behaviour and performance of football tipsters (2000)Forecasting sport: the behavi…The Sharpe Ratio (1994)The Sharpe RatioPORTFOLIO SELECTION* (1952)PORTFOLIO SELECTION*Forecasting methods and applications (1993)Forecasting: Methods and Applications (1999)The Economics of Football (2001)Forecasting football results and the efficiency of fixed‐odds betting (2004)The 12th Man?: Refereeing Bias in English and German Soccer (2009)The Home Advantage In Sport Competitions: A Literature Review (1992)Predicting the World Cup 2002 in soccer: Performance and confidence of experts and non-experts (2005)Predicting Wimbledon 2005 tennis results by mere player name recognition (2007)The second leg home advantage: Evidence from European football cup competitions (2007)Racial Discrimination Among NBA Referees (2007)Racial Discrimination Among NBA Referees (2010)Characterizing the spatial structure of defensive skill in professional basketball (2015)Trends in NBA and Euroleague basketball: Analysis and comparison of statistical data from 2000 to 2017 (2019)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)The Use of Knowledge in Society (1996)Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EURO 2008 (2009)Predicting wins and spread in the Premier League using a sentiment analysis of twitter (2016)How does spectator presence affect football? Home advantage remains in European top-class football matches played without spectators during the COVID-19 pandemic (2021)Modern Portfolio Theory and Investment Analysis. (1982)The Statistics of Sharpe Ratios (2002)An econometric model of serial correlation and illiquidity in hedge fund returns (2004)Deep Direct Reinforcement Learning for Financial Signal Representation and Trading (2016)Random variables, joint distribution functions, and copulas (1973)Modelling Association Football Scores and Inefficiencies in the Football Betting Market (1997)Analysis of sports data by using bivariate Poisson models (2003)A hybrid random forest to predict soccer matches in international tournaments (2019)Plus–minus player ratings for soccer (2019)Anomalies: Parimutuel Betting Markets: Racetracks and Lotteries (1988)Bettors Love Skewness, Not Risk, at the Horse Track (1998)Contract Design and Self-Control: Theory and Evidence (2004)OUTCOME UNCERTAINTY AND THE COUCH POTATO AUDIENCE (2005)Using ELO ratings for match result prediction in association football (2009)Believing what we do not believe: Acquiescence to superstitious beliefs and other powerful intuitions. (2015)A game-predicting expert system using big data and machine learning (2019)Sports Analytics algorithms for performance prediction (2019)Big data analytics for modeling scoring probability in basketball: The effect of shooting under high-pressure conditions (2017)Conditional value-at-risk for general loss distributions (2002)Optimal Versus Naive Diversification: How Inefficient is the 1/ N Portfolio Strategy? (2007)The relationship between corporate social responsibility and shareholder value: an empirical test of the risk management hypothesis (2008)
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References

  • 1952PORTFOLIO SELECTION*13,480 cited
  • 1994The Sharpe Ratio2,542 cited
  • 2004Why are Gambling Markets Organised so Differently from Financial Markets?377 cited
  • 2007A Starting Point for Analyzing Basketball Statistics294 cited
  • 2005Odds-setters as forecasters: The case of English football213 cited
  • 2008Sports forecasting: a comparison of the forecast accuracy of prediction markets, betting odds and tipsters190 cited
  • 2000Forecasting sport: the behaviour and performance of football tipsters118 cited
  • 2009Predicting NBA Games Using Neural Networks113 cited
  • 2010The use of data mining for basketball matches outcomes prediction109 cited
  • 2017A bivariate Weibull count model for forecasting association football scores108 cited
  • 2010Issues in sports forecasting99 cited
  • 2010Prediction accuracy of different market structures — bookmakers versus a betting exchange94 cited
  • 2018Efficiency of online football betting markets77 cited
  • 2013A Review of Data Mining Techniques for Result Prediction in Sports75 cited
  • 2012DOES SPORTSBOOK.COM SET POINTSPREADS TO MAXIMIZE PROFITS?70 cited

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2013
Profiting from an inefficient association football gambling market: Prediction, risk and uncertainty using Bayesian networks
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