1. Lopez – MA 276 MA 276: Sports and statistics Lecture 2: Statistics in baseball 0

2. Lopez – MA 276 Goals i)Overview of sabermetrics: What to look for? ii)Example: Runs created iii)Additional topics after lecture -Bunting/pitchouts, Pitch framingBunting/pitchoutsPitch framing -Defensive independent pitchingDefensive independent pitching 1 Tools i)Bivariate tools: scatter plots, r, R-squared ii)In-sample versus out-of-sample comparisons

3. Lopez – MA 276 What is sabermetrics? ‘Search for objective knowledge about baseball’ -Bill James Ex: Which player on the Red Sox contributed most to his team’s offense? Ex: Which player is your favorite? Ex: Which player deserves the MVP award? 2

4. Lopez – MA 276 Questions we’ll want to answer 1 – Is the metric important to success? 2 – How well does the metric measure a player’s contribution? 3 – Is the metric repeatable? 3

5. Lopez – MA 276 Is the metric important to success? What’s “important?” What’s “success?” -Examples in baseball Stolen bases Batting average Home runsWalks RBIsSlugging percentage 4

6. Lopez – MA 276 How well does the metric measure a player’s contribution? Stolen bases Batting average Home runsWalks RBIsSlugging percentage Which are impacted by a player’s teammates? Which are impacted by a player’s ballpark? Which are impacted by a player’s coach? Which are impacted by a player’s era? 5

7. Lopez – MA 276 Is the metric repeatable? Stolen bases Batting average Home runsWalks RBIsSlugging percentage How to judge repeatable? Why is repeatability (?) important? How does sample size fit in? 6

8. Lopez – MA 276 Ex: Runs created 7 Why runs created?

9. Lopez – MA 276 Ex: Runs created 8 General assumptions & expectations Different valuations to different types of hits Hitters only control their performance -What is assumed here? Hitters do not control when they hit Hitters do not control importance of at-bat relative to game’s outcome

10. Lopez – MA 276 Ex: Runs created 9

11. Lopez – MA 276 Ex: Runs created 10 Benefits of runs created Team level accuracy: - Basic version can predict a team’s run total within a 5% margin of error Individual talent: - Reflects individual performance only Repeatability? - To be determined in Thursday’s lab.

12. Lopez – MA 276 Ex: Runs created 11 Weaknesses of runs created What if clutch exists? Ballpark dependencies Opponent dependencies

13. Lopez – MA 276 Ex: Runs created 12 What’s it look like?

14. Lopez – MA 276 Ex: Runs created 13

15. Lopez – MA 276 Ex: Runs created 14 How do we describe the association between runs created and actual runs?

16. Lopez – MA 276 Ex: Runs created 15 What about the association between team runs and other team variables? Note: What does the select command do?

17. Lopez – MA 276 Ex: Runs created 16

18. Lopez – MA 276 Ex: Runs created 17 What about runs created against more popular but advanced metrics?

19. Lopez – MA 276 Ex: Runs created 18

20. Lopez – MA 276 What we’ve shown 1 – Is runs created important to success? -Yes. Strong link to team runs 2 – How well does the metric measure a player’s contribution? -Pretty well. Other advanced formulas exist -Adjustments possible 3 – Is the metric repeatable? -Let’s find out 19

21. Lopez – MA 276 Ex: Runs created 3 – Is the metric repeatable? Explanatory power vs. Predictive power 20

22. Lopez – MA 276 Ex: Runs created 3 – Is the metric repeatable? 21

23. Lopez – MA 276 Ex: Runs created 3 – Is the metric repeatable? 22

24. Lopez – MA 276 Ex: Runs created Implications: Other tools for assessing error: MSE: MAE: 23

25. Lopez – MA 276 Additional topics 24 Bunting, pitchouts Pitch framing Defensive independent pitching 1 – Importance 2 – Player-specific contributions 3 – Repeatability