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Football Spreads

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Presentation from 11/19/2014 at Cleveland R User Group on using R to improve and track spread NFL picks throughout the season.

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Football Spreads

  1. 1. Spread Football Analysis Tim Hoolihan tim@hoolihan.net @thoolihan
  2. 2. What Is A Spread? • Point Differential • Added to favored team to determine adjusted score • Attempts to get 50% of betters on each side of the bet* • Different than trying to be accurate. For example: large fan-base skew • Rule of Thumb: Home Team starts with -3
  3. 3. Goals • Come back from a horrible start in my league • Pet project in R that motivates learning more
  4. 4. Track • Google Spreadsheet • Download as CSV • Blank copy you can edit: http://bit.ly/1xLvg64
  5. 5. Functions For Game Types
  6. 6. …continued
  7. 7. League Trends • rmarkdown • convert to html
  8. 8. Home vs Away Favorite vs Underdog • First meaningful insight • It appears away favorites are a better pick • Why?
  9. 9. Testing The Math
  10. 10. Spread Performance By Team
  11. 11. My Trends
  12. 12. Upcoming Games
  13. 13. My Results & Progress
  14. 14. Residuals
  15. 15. Packages • rmarkdown • scales • dplyr • ggplot2 • gridExtra
  16. 16. dplyr • Workshop exposure • chaining, functional • Linq in .Net • Closures (JavaScript, Ruby) • Domain Specific Language - like (see Residuals.R)
  17. 17. ggplot2 • Nice, but challenging • qplot vs ggplot
  18. 18. Have I Learned Anything? • Yes, a lot more R • League position improved from basement to basement stairs • Don’t pick home underdogs
  19. 19. What Comes Next? • Calculate Correct, other columns • Clustering by spread size • Model training (machine learning… caret?) • My performance vs recommendation • Break out web pages further (league, my performance, next week) • Shiny?
  20. 20. Your Turn • https://github.com/thoolihan/FootballPicks • Google Docs http://bit.ly/1xLvg64 • tim@hoolihan.net

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