Applying Machine Learning Techniques to Baseball Pitch Prediction

@inproceedings{Hamilton2014ApplyingML,
  title={Applying Machine Learning Techniques to Baseball Pitch Prediction},
  author={Michael Hamilton and Phuong Hoang and Lori Layne and J. Murray and D. Padget and Corey Stafford and Hien Tran},
  booktitle={ICPRAM},
  year={2014}
}
Major League Baseball, a professional baseball league in the US and Canada, is one of the most popular sports leagues in the world. [...] Key Method We apply several common machine learning classification methods to PITCHf/x data to classify pitches by type. We then extend the classification task to prediction by utilizing features only known before a pitch is thrown. By performing significant feature analysis and introducing a novel approach for feature selection, moderate improvement over former results is…Expand
8 Citations

Figures, Tables, and Topics from this paper

Machine Learning Applications in Baseball: A Systematic Literature Review
  • 10
  • PDF
A Survey of Baseball Machine Learning: A Technical Report
  • 3
An Input Support System for Customized Scouting Charts of Baseball Games
  • PDF
Ball 3D Trajectory Reconstruction without Preliminary Temporal and Geometrical Camera Calibration
  • 6
  • PDF
Sport Analytics: Science or Alchemy?

References

SHOWING 1-9 OF 9 REFERENCES
Predicting the Next Pitch
  • 17
  • Highly Influential
  • PDF
Slugging Percentage in Differing Baseball Counts
  • 1
  • Highly Influential
Pattern Recognition, Fourth Edition
  • 618
Support Vector Machines Explained
  • 159
  • PDF
An introduction to ROC analysis
  • 12,683
  • PDF
Wikipedia glossary of baseball
  • Retrieved July, 2013 from htt p : ==en:wikipedia:org=wiki=Glossary o f baseball.
  • 2013
Major league baseball attendance records
  • Retrieved June 19, 2013 from htt p : ==espn:go:com=mlb=attendance==year=2012. Pitchf/x (2013). MLB pitch f/x data. Retrieved July, 2013 from htt p : ==www:mlb:com.
  • 2012