Friday, April 5, 2013

Ranking the Opening Day Starters

I'm liking this "ranking" thing. It's good. Here's a list of the MLB Opening Day starters for each team, based on how well I think they'll do in 2013. The methodology:

There are a bunch of stats that are good predictors of future performance for pitchers. has a bunch of these advanced stats that measure all kinds of things, but there are a few that stand out as good predictors for pitchers. Prepitchtors. Pitchdictors. Something. I used a couple for determining which starters would have the best 2013.

The first is SIERA, which stands for Skill-Interactive ERA. It basically measures how well a pitcher did, regardless of the fielders behind him, and with batted-ball effects taken into account. For more details, check out the explanation at FanGraphs.

The second is xFIP, or Expected Field-Independent Pitching. This essentially does what SIERA does, except it's a tiny bit simpler. Instead of taking all batted-ball effects into account like SIERA does, it basically just regresses how well a pitcher did, regardless of the fielders behind him, and giving him a league-average Home Runs per Fly Ball percentage. I won't get into why this is a thing here, but again, read it at FanGraphs if you're curious.

So those two stats were essentially where I started. A pitcher's SIERA and xFIP from the previous year factored in heavily into my predictions. A few other stats factored into my predictions, though they may be less precise and advanced. One was BABIP, and specifically, how good a pitcher's BABIP was last year compared to his career average. If it was better last year than normal, that means that the pitcher is generally more likely to regress back to his normal BABIP and have a slightly worse year, and vice versa. Another factor was the pitcher's 2012 WAR. How good was this guy, in terms of WAR, last year? It's something to consider. And finally, the final two factors I used were age and games started over the past 3 years. I used these to approximate the likelihood that a pitcher would have a step-back year or a breakout year, and to gauge the likelihood that the pitcher would miss time due to injury.

So when I took all these into account, I had a pretty good idea of how a pitcher would perform this year. Armed with all these statistical tools, I ultimately added one more factor to the equation: what I know about the pitcher in general. Stats can only be used to predict to a degree, and if I know something about this pitcher, his team, or his situation, then that swayed my opinions as well.

ENOUGH OF THIS! Let's get to the list.

30. Jhoulys Chacin, Rockies

29. Edinson Volquez, Padres

28. Ricky Nolasco, Marlins

27. Matt Harrison, Rangers

26. A.J. Burnett, Pirates

25. Justin Masterson, Indians

24. Vance Worley, Twins

23. Tim Hudson, Braves

22. Bud Norris, Astros

21. Jason Hammel, Orioles

20. Jon Niese, Mets

19. Jeff Samardzija, Cubs

18. Yovani Gallardo, Brewers

17. Jon Lester, Red Sox

16. Jered Weaver, Angels

15. Johnny Cueto, Reds

14. Adam Wainwright, Cardinals

13. Ian Kennedy, Diamondbacks

12. Matt Cain, Giants

11. R.A. Dickey, Blue Jays

10. James Shields, Royals

9. C.C. Sabathia, Yankees

8. Brett Anderson, Athletics

7. Chris Sale, White Sox

6. Clayton Kershaw, Dodgers

5. Stephen Strasburg, Nationals

4. Cole Hamels, Phillies

3. Justin Verlander, Tigers

2. Felix Hernandez, Mariners

1. David Price, Rays

Thoughts? I know Sean's not gonna be happy about this one. And that's really all that matters.

1 comment:

  1. "Age is a scientific journal focused on the biology of aging and research on biomedical applications that impact aging. This includes evolutionary biology, biophysics, genetics, genomics, proteomics, molecular biology, cell biology, biochemistry, endocrinology, immunology, physiology, pharmacology, neuroscience, and psychology."

    Thanks for linking that...