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Predicting Win-Loss outcomes in MLB regular season games – A comparative study using data mining methods
5 references·0 citing·21 second hop
Predicting Win-Loss outcomes in MLB regular season games – A comparative study using data mining methods (2016)Predicting Win-Loss outcomes in MLB regul…Explaining match outcome in elite Australian Rules football using team performance indicators (2015)Explaining match outcome in e…A Review of Data Mining Techniques for Result Prediction in Sports (2013)A Review of Data Mining Techn…A comparative analysis of data mining methods in predicting NCAA bowl outcomes (2011)A comparative analysis of dat…Sports Data Mining (2010)Sports Data MiningIssues in sports forecasting (2010)Issues in sports forecastingJournal of Sports Science and Medicine (2014)A method to assess the influence of individual player performance distribution on match outcome in team sports (2016)A data-driven prediction approach for sports team performance and its application to National Basketball Association (2019)Training programme designs in professional team sport: An ecological dynamics exemplar (2019)A State-Space Model for National Football League Scores (1998)Decision Support and Business Intelligence Systems (2006)Predicting football results using Bayesian nets and other machine learning techniques (2006)Predicting and explaining corruption across countries: A machine learning approach (2019)Intuitive prediction: Biases and corrective procedures (1982)Judgment under uncertainty: Heuristics and biases (1982)Judgment Under Uncertainty: Heuristics and Biases. (1984)On determining probability forecasts from betting odds (2014)Forecasting the Olympic medal distribution – A socioeconomic machine learning model (2021)Oxford Dictionary of Sports Science and Medicine (1998)Artificial Intelligence in Sports Prediction (2008)The use of data mining for basketball matches outcomes prediction (2010)Increased Prediction Accuracy in the Game of Cricket Using Machine Learning (2018)Exploiting sports-betting market using machine learning (2019)Enterprise Systems and Data Analytics (2015)A Markov Game model for valuing actions, locations, and team performance in ice hockey (2017)Machine Learning Applications in Baseball: A Systematic Literature Review (2017)
this work references cited by second hop

References

  • 2015Explaining match outcome in elite Australian Rules football using team performance indicators145 cited
  • 2010Issues in sports forecasting99 cited
  • 2013A Review of Data Mining Techniques for Result Prediction in Sports75 cited
  • 2011A comparative analysis of data mining methods in predicting NCAA bowl outcomes73 cited
  • 2010Sports Data Mining69 cited

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