Beat the Streak: Prediction of MLB Base Hits Using Machine Learning

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Abstract

As the world of sports expands to never seen levels, so does the necessity for tools that provided material advantages for organizations and stakeholders. The objective of this project is to develop a predictive model capable of predicting the odds a baseball player has to achieve a base hit on a given day. After that, using this information to both have a fair shot at winning the game Beat the Streak and providing valuable insights to the coaching staff. This project builds upon the work developed previously in Alceo and Henriques (2019), adding a full season of data, emphasizing new strategies, and displaying more data visualization content. The results achieved on the new season are aligned with the previous work where the best model, a Multi-layer Perceptron, developed in Python achieved an 81% correct pick ratio.

Original languageEnglish
Title of host publicationKnowledge Discovery, Knowledge Engineering and Knowledge Management
Subtitle of host publication11th International Joint Conference, IC3K 2019, Revised Selected Papers
EditorsAna Fred, Ana Fred, Ana Salgado, David Aveiro, Jan Dietz, Jorge Bernardino, Joaquim Filipe
PublisherSpringer Science and Business Media Deutschland GmbH
Pages108-133
Number of pages26
ISBN (Print)9783030661953
DOIs
Publication statusPublished - 2020
Event11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2019 - Vienna, Austria
Duration: 17 Sept 201919 Sept 2019

Publication series

NameCommunications in Computer and Information Science
Volume1297
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2019
Country/TerritoryAustria
CityVienna
Period17/09/1919/09/19

Keywords

  • Baseball
  • Classification model
  • Data mining
  • Machine learning
  • MLB
  • Predictive analysis

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