In 1988, when the statistical revolution that would become MoneyBall was in its infancy, Bill James wrote:

A power pitcher has a dramatically higher expectation for future wins than does a finesse picther of the same age and ability.

A quarter century later, this claim remains somewhat controversial, as can be seen in the boards. I do not propose to end the argument today. Indeed, I'm hoping to start a debate on it. To that end, I'd like to share a nascent data set and some early conclusions. I believe that the initial results will surprise some.

To begin tackling the larger claim, I'd like to address a slightly different question: are power pitchers more likely to repeat a strong year, controlling for age? This approximates James's original claim by making (the dubious) assumption that two pitchers who had a strong year are of equal ability and uses controls for age to address the "same age" part of the claim.

I started by taking every pitcher in 2009 who threw more than 100 innings, which left me with 130 pitchers. I then needed a way to divide pitchers into power pitchers vs. finesse pitchers. As a first pass, I decided to calculate their average velocity. The idea behind this is that true power pitchers, such as Verlander and Felix Hernandez, tend to throw everything hard. The velocities went from a high of 91.8 MPH for Josh Johnson to a low of 65.63 (1 million CubsDen Dollars to the poster who can guess who that was. Cash value of 1 million CubsDen Dollars = $0.00 USD). I then divided pitchers into thirds based on velocity and considered the top third to be power pitchers and the bottom third to be finesse pitchers.

Next, I needed to determine a performance metric. I determined that ERA was appropriate. Why ERA? Because metrics such as FIP are based on James's work and may give a slight edge to power pitchers, due to the emphasis on strikeouts. Like I did with velocity, I divided pitchers into thirds based on ERA.

The results are summarized in the figure above. A trend can be seen in this data. High velocity pitchers tend to have lower ERAs and low velocity pitchers tend to have higher ERAs. Thus, based on this data set, we find evidence that is consistent with Friday's work: high velocity (strikeout) pitchers are more likely to have a lower ERA.

However, the question I want to address here is whether pitchers who have a good year are likely to repeat that year. Therefore, I took the pitchers in the high velocity-low ERA box and the low velocity-low ERA box and tracked them into the future.

The power pitchers were Edwin Jackson, Yovani Gallardo, Zack Greinke, Josh Johnson, CC Sabathia, Justin Verlander, Clayton Kershaw, Jake Peavy, Hiroki Kuroda, Ubaldo Jimenez, Jon Lester, Felix Hernandez, Roy Halladay, Josh Beckett, Matt Cain, and Cub favorite Carlos Zambrano. The finesse pitchers were Javier Vazquez, Jarrod Washburn, Bronson Arroyo, Adam Wainwright, Ted Lilly, Dallas Braden, Mark Buehrle, Wandy Rodriguez, Kenshin Kawakami, Jered Weaver, John Lannan, and Randy Wolf.

The first thing I did was enter their ages and ERAs for the 2010, 2011, 2012, and 2013 seasons. Jarrod Washburn's final season was 2009, so he was dropped from the data set. Since we're interested in whether pitchers could repeat a good season, I calculated the difference in ERA between their strong 2009 season and the four following seasons. Hereafter, this will be referred to as the ERA differential.

**Warning: the next section is kind of mathy. You can skip it and not miss anything.**

First, I ran a simple test on the two groups. I ran a statistical test called a t-test to see whether, statistically, the era differentials were lower for power pitchers than for finesse pitchers.

I then regressed the difference on a dummy variable for finesse, age, and age squared. The dummy variable is a variable equal to 1 if the pitcher is a finesse pitcher and 0 otherwise. In a regression, this will give the impact of being a finesse pitcher on ERA differential. Age and age squared are included to reflect the idea of a "prime." Players should get better up to a certain age, and then start to slowly get worse. If this is true, the coefficient on age will be positive and the coefficient on age squared will be negative.

**If you skipped the mathy part, you can pick up again here.**

Simply comparing the two sets of differentials does not indicate any difference in the ERA differntials. In fact, there is 80% certainty that the differentials are the same for power pitchers and finesse pitchers.

When this is extended to regression analysis, I find the same thing. The coefficient on finesse pitchers, while positive, is not statistically different from zero. The coefficients on age have the expect sign, though the magnitude suggests the "prime" occurs in the early to mid-30s.

The results give hope to both sides of the debate. It is possible that the data set is simply not big enough. If more players and years are added, it may turn out that the positive coefficient on finesse pitchers remains and becomes significant.

However, for now, the conclusion I draw is that, while a fireballer is more likely to have a low ERA, a good pitcher is a good pitcher and just as likely to remain so year over year.

Filed under: Analysis

"to a low of 65.63 (1 million CubsDen Dollars to the poster who can guess who that was. Cash value of 1 million CubsDen Dollars = $0.00 USD)."

Jamie Moyer?

That being said,.... nice article Mike. Some things to think about.

Mike,

What software are you using to run your regressions and t-tests? SAS Stata?

STATA.

Nice. That's not cheap stuff. Do you have it from work? School?

Simply curious. I worked with both programs during grad school.

Also, I really appreciate your higher level of analysis. Well done.

I have it from work. You're correct, it isn't cheap, but it's very good at what it does. Someone suggested R on the last one of these, and I'm thinking I might try doing some in R, both because I need to learn it and it's programmability might make some more complicated ideas I have easier to do.

jaime moyer.

No way its Moyer. Has to be the knuckleballer Wakefield

Wakefield would be a good guess as well.

This is the winner.

Moyer was second.

Yes! Please put my winnings towards a years subscription to CubsDen. I enjoy the new Econoball articles. Keep it up.

Mike - suppose you used strikeouts per inning instead of velocity to separate them into groups. In other words, are strikeouts strictly a function of velocity? And if not, how does a strikeout rate project into future years (or future year).

Interesting questions. Might be worth checking the relationship between velocity and strikeouts, now that you mention it, instead of assuming it.

Mike, the one thing that stands out between power and finesse pitchers is health. Lots of pitchers start out in there mid 20s as power guys who consistently throw in the mid 90s. They end up developing 2 seam Fbs and better secondary pitches as they age. Few genuine power guys become sucessfull finesse pitchers, Tom Seaver and Ron Guidry are the only names of note whove sucessfully transistioned from high K pitchers to pitch-to-contact success. Most power arms usually suffer from injuries before they lose effectiveness.

I would like to see the data. But anecdotally I can surmise that there are more power pitchers that make it to the bigs at a young age than finesse by their very definition. Finesse takes a lot of time/reps to master at a level that is as effective as a young guy throwing smoke. So yes your probably right in your statement that more power arms end up injured and out of ball after their MLB arrival than finesse pitchers, but it is hard to go beyond that statement without the data isolated in ratios with ceterus peribus. More than I have time to research today...

Think about finesse guys who have won a lot of games in the majors. Moyer comes t o mind immediately, maybe a Frank Tanana, but as you said, it took them years to develop there ability. Tanana started off as a power arm, and injuries forced him to adapt. My main point is that most power arms develop injury problems that lead to ineffectiveness, and the choice becomes retire or adapt. Relatively few power arms eventually do, Its a struggle someone like CC Sabathia is going thru now. His continued MLB success will rely on his ability to spot his FB now rather than earlier in his career.

My guess on the lowest average velocity pitcher would be Tim Wakefield.

And it was an interesting analysis (despite obvious methodology flaws/limitations), but kind of a strange topic to even investigate. It seems axiomatic that pitching velocity would provide no guarantee of pitching consistency. I understand Bill James raised the issue, but pitching success involves far more variables than just average velocity. Any good pitcher or hitter will tell you it's not how hard you throw, but more how well you command location and change speeds. Without that, no one can have success getting the same hitters in a lineup out 2 to 3 times in a given start.

I think this was touched on in the previous EconoBall post (EconoBall Chapter 1, if you will), but I would suspect the power is better set up with a very slow secondary pitch. I think there was a Japanese reliever on the White Sox a few years back who had something like a high-80's fastball but a high-50's changeup. I would suspect that would yield better results than a hypothetical pitcher with speeds all in the range of, say, 88 - 98 MPH.

Could you run an analysis on pitch speed variance? Do you have the data for that?

I do and I'm going to.

Mike,

I'm having a problem with your data - the trend in baseball these days is having more power pitchers on your roster, so you need to look at a much broader spectrum of pitchers than just one year. ERA alone doesn't necessarily mean a good pitching performance - nine walks in a game, albeit stranding them on base doesn't mean a good performance in my book.

I was also always under the assumption that finesse pitchers usually had more control and command of the ball than power pitchers and that fact alone proves they are more repeatable in their delivery and therefore game outcomes. I mean, if they couldn't control an underwhelming fastball they wouldn't even be in the majors.

I totally agree that more data would be helpful. However, I'd disagree that ERA is necessarily a poor metric here. I'm looking at groupings of 16 and 11 pitchers, over the course of a season, and it seems unlikely that every one of them got there by walking nine guys and stranding them. But, beyond that, if they DID get there by walking 9 guys and stranding them, that's exactly what we're trying to identify. If that's how it happened, we'd expect ERAs to jump in future years when they no longer strand all 9 of those walks.

However, it is a good idea to track things like velocity, walks, etc over the future years.

This brings to mind a memory I have of Joey Jay (Reds back in the 60s) pitching a no-hitter while walking 11 IIRC. Talk about stranding runners.

I love this stuff!!!!

Thanks.

This Is an excellent if somewhat esoteric series. I hope to see many more of these articles, and hope that they will make you rich and famous.

Heh, For now, I'm just enjoying doing them. I've had this idea forever, but only recently found a way to get the data I need. John was kind enough to let me use his blog to publish them.

Hey Mike, is the title of the article a play on the short story:

Are Enormous Ewers More Likely to Repeat a Good Pour-formance than Finesse Flasks? JK. ;)

On a serious note, I agree with "a good pitcher is a good pitcher". I just think that it is easier to project power pitchers a little better for an organization.

Best to leave knuckleballers out of this because they're just weird.

They strike out Major League hitters while throwing at Little League speeds.

Yeah, I agree. He saved me a hard choice by not falling into the "Finesse" bin.

Hey Mike, good article, I suspected as much.

BTW... Was it Charlie Hough? Although I can't find his FB velocity, but he did pitch until he was about 46-47 and was always a soft-tossing knuckleballer.

Great stuff Mike. Looking forward to where you go with the deeper statistical analysis in future articles. Do you already have some future topics planned out?