2022 Blogmas Day 0 – Baseball Statistics

After a couple of years toying with the idea, I’ve finally decided to do a blogmas, my own take on creative challenges such as Advent of Code. In this case, you’ll be treated to 25 days of posts about the wonderful world of baseball statistics.

Don’t go running away yet. My goal is to build up these posts in a way that someone passingly familiar with the sport should be able to follow along, gathering the requisite knowledge to understand each subsequent statistic as we progress. I’ll do my best to explain some cultural context around each statistic, and provide a fun bit of trivia through the Stathead tool I discovered a couple of months ago.¹And, I might add, I’ve been looking for an excuse to finally use that tool for something interesting. This is sort of an excuse to do so.

The beauty of baseball is that many of the statistics are very easily tracked. It’s a game made of discrete plays, where only a few things can happen. A ball is pitched, and it gets hit somewhere.²Modern statistics make use of advanced tracking to more accurately consider how baserunners compare to each other, for example. But I don’t necessarily plan to cover many statistics that rely heavily on external data sources. Compare this to American football: It is also made of discrete plays, but the dynamics of 11 players on each side all having something to do with the end result really complicates matters. So, due to the comparative simplicity of the outcomes in each play of baseball, many baseline statistics are easy to gather and distribute, leading to a huge community of fans who engage with these numbers. Eventually, more complicated statistics were created to both better reflect the changing landscape of the game, and to more properly evaluate a player using modern understandings of player value.

Over the next four weeks, I hope you gain appreciation for how baseball statistics grew: how we went from boxscores in newspapers to large communities dedicated to baseball research, where people maintain huge databases, and complicated (sometimes proprietary) statistics are developed. If you want to see these statistics in action by the end of our journey together, watch literally any video on Foolish Baseball. He is the current champion of positively using advanced statistics to understand baseball in an entertaining way.

Retroactive Table of Contents

1. Batting Average
2. On Base and Slugging Percentage
3. OPS and OPS+
4. Weighted On Base Average
5. Three True Outcomes
6. Isolated Power
7. Batting Average on Balls in Play
8. Weighted Runs Above Average and Runs Created
9. Offensive Wins Above Replacement
10. Win Probability Added
11. Earned Run Average
12. Other Basic Pitching Statistics
13. Walks and Hits per Inning Pitched
14. ERA+
15. Fielding Independent Pitching
16. Pitcher Miscellany
17. Expected FIP
18. Fixing ERA+ With a Minus
19. Leverage Index
20. Pitcher WAR
21. Fielding Percentage and Range Factor
22. Ultimate Zone Rating
23. Defensive Runs Saved and Defensive WAR
24. Retrospective

• 1
  And, I might add, I’ve been looking for an excuse to finally use that tool for something interesting. This is sort of an excuse to do so.
• 2
  Modern statistics make use of advanced tracking to more accurately consider how baserunners compare to each other, for example. But I don’t necessarily plan to cover many statistics that rely heavily on external data sources.