Chad Billingsley Has “The Heater You Can Live With”
Ok, so after a full year of working in my basement office at Woodland Pattern Book Center, I finally noticed this decal on a (possibly nonfunctional) heating unit:
Download, print as stickers, and apply where appropriate.
Of course, I immediately interpreted the phrase with my baseball brain: “The Heater You Can Live With” is a heater (a fastball, and, in my mind, a four-seam fastball, specifically) that is passable, that gets the job but is not overwhelming; a heater that chips in but upon which a pitcher is not overly reliant; a heater that, looks like the average of all heaters in the game, so as not garner attention, but like I said, is still capable of getting an out, or setting up other pitches, or even causing the occasional whiff.
With the generous help of Jeff Zimmerman, I compiled data to look for the most average four-seamer that I could find based on Usage (FA%) Velocity (vFA), Horizontal Movement (FA-X), Vertical Movement (FA-Z), and Whiff Rate (FASwgStr%).
The table below includes the Standard Deviations from the Mean (a crude “z-score”) in each of the aforementioned categories from 2011-2012 (minimum 100 heaters thrown and at least one whiff). I then averaged these “z-scores” and ranked the top 25 pitchers:
| Name | Team | Age | Z-avg | SwgStr%z | FA%z | vFAz | FA-Xz | FA-Zz |
|---|---|---|---|---|---|---|---|---|
| Mark Melancon | - – - | 27 | 0.4839 | 0.0569 | 0.0488 | 0.2655 | 0.0358 | 0.0768 |
| Chad Billingsley | Dodgers | 27 | 0.5368 | 0.1779 | 0.2591 | 0.0759 | 0.0239 | 0.0000 |
| Casey Janssen | Blue Jays | 30 | 0.5481 | 0.0304 | 0.1771 | 0.0948 | 0.1075 | 0.1382 |
| Roy Oswalt | - – - | 34 | 0.5745 | 0.0113 | 0.0952 | 0.0569 | 0.3344 | 0.0768 |
| Jason Isringhausen | - – - | 39 | 0.6769 | 0.1007 | 0.2021 | 0.2086 | 0.0119 | 0.1536 |
| Tommy Hunter | - – - | 25 | 0.7148 | 0.4112 | 0.0987 | 0.0190 | 0.1552 | 0.0307 |
| Francisco Rodriguez | - – - | 30 | 0.7379 | 0.2184 | 0.0952 | 0.1138 | 0.2030 | 0.1075 |
| Shawn Kelley | Mariners | 28 | 0.7468 | 0.2146 | 0.3254 | 0.0379 | 0.1075 | 0.0614 |
| Jeremy Hellickson | Rays | 25 | 0.7556 | 0.2250 | 0.0011 | 0.0569 | 0.2269 | 0.2457 |
| Tim Lincecum | Giants | 28 | 0.7630 | 0.1845 | 0.0417 | 0.0948 | 0.2269 | 0.2150 |
| Matt Guerrier | Dodgers | 33 | 0.7690 | 0.1757 | 0.4516 | 0.0190 | 0.1075 | 0.0154 |
| Zack Greinke | Brewers | 28 | 0.7713 | 0.0303 | 0.1344 | 0.2465 | 0.1911 | 0.1690 |
| Jose Arredondo | Reds | 28 | 0.7779 | 0.0956 | 0.1379 | 0.0000 | 0.0836 | 0.4608 |
| Jason Hammel | - – - | 29 | 0.8032 | 0.1959 | 0.0595 | 0.3414 | 0.1911 | 0.0154 |
| Jordan Lyles | Astros | 21 | 0.8211 | 0.2805 | 0.0153 | 0.1517 | 0.3582 | 0.0154 |
| Joakim Soria | Royals | 27 | 0.8226 | 0.3822 | 0.0759 | 0.0948 | 0.0239 | 0.2457 |
| Graham Godfrey | Athletics | 27 | 0.8228 | 0.2014 | 0.0296 | 0.3034 | 0.2269 | 0.0614 |
| Anibal Sanchez | Marlins | 28 | 0.8332 | 0.0754 | 0.4551 | 0.0569 | 0.0000 | 0.2457 |
| Josh Roenicke | Rockies | 29 | 0.8380 | 0.2528 | 0.1329 | 0.3414 | 0.0955 | 0.0154 |
| Yovani Gallardo | Brewers | 26 | 0.8484 | 0.1597 | 0.0652 | 0.2276 | 0.1194 | 0.2765 |
| Matt Cain | Giants | 27 | 0.8637 | 0.3504 | 0.0474 | 0.0190 | 0.3702 | 0.0768 |
| Logan Ondrusek | Reds | 27 | 0.8721 | 0.2434 | 0.1843 | 0.2465 | 0.1672 | 0.0307 |
| Mat Latos | - – - | 24 | 0.9447 | 0.1360 | 0.0595 | 0.3414 | 0.1314 | 0.2765 |
| Vicente Padilla | - – - | 34 | 0.9506 | 0.2146 | 0.0118 | 0.2465 | 0.3702 | 0.1075 |
| Gavin Floyd | White Sox | 29 | 0.9700 | 0.3514 | 0.1700 | 0.0000 | 0.4179 | 0.0307 |
It’s nice to notice that the vertical movement on Billingsley’s four-seamer is exactly the mean (at least of the sample used). That doesn’t mean that it doesn’t possess vertical motion, it just means that if you mapped it out with all the other four-seamers, you wouldn’t really notice it. It’s nice to notice this because I’m choosing to overlook Mark Melancon’s Z-avg and give the very first hypothetical “The Heater You Can Live With” badge to Chad Billingsley — because I think it just seems more appropriate to give it to a starting pitcher.
Because it pleases me.
Why didn’t I just limit the data to starting pitchers, then, you might ask. Well, because I thought it would still be interesting to see which relievers have the most average four-seam fastball. And because I do what I please; I pay you no mind.
You might also ask, Why is this on NotGraphs? It’s full of numbers! Z-scores! Sortables! Sundry maths! Jeff Zimmerman! I assure you, save the data produced by J.Z. (on Whiff Rates), the numbers here were manipulated in such a clumsy manner as to make NotGraphs proud. Plus, it coins a phrase! It provides ephemera! It has provided no statistical insight whatsoever!
Ok, ok, back to my mini helmets…
One would think NotGraphs includes charts. Not to mention a freakin z-score.
Tsk, tsk.
It’s almost as if you didn’t read the last paragraph.
Almost-although I did think my IF NotGraphs, THEN NotCharts thing was pretty funny.
NotGraphs, ButCharts
at least I appreciate the inclusion of Matt Cain, continuing a fine FanGraphs and now NotGraphs (ButCharts) tradition!
“I then averaged these ‘z-scores’”
Looks like you added, not averaged. I highly doubt either way is a statistically rigorous method, but that’s ok because this is notgraphs. Does anybody know the correct way to do this?
Fun article.
LOL. That’s why I’m at NotGraphs!
I went back to my spreadsheet and averaged them. It didn’t make any different in the standings, of course, because I was just dividing the totals by five…
Now, if I was really ambitious, I would have decided upon arbitrary weights to assign each stat according to which of them I think most defines a “live-with-able” heater.
1) Adding them is the same as averaging them. (The only difference is a fixed multiplicative factor of five, which doesn’t matter for ranking.)
2) Both are reasonable statistical methods. The sum of expected is equal to the expected value of the sum. It’s fairly arbitrary what metric to use.
3) However, I suppose I’d prefer the Euclidean norm. (i.e., distance norm, square root of the sum of the squares.)
This article puts the “graphs” in “notgraphs.” Or, maybe it removes the “not” from “notgraphs.” Either way, for some reason I find the presence of a graph (defined here broadly enough as to include charts) more comment-worthy than the content of the article. That’s not to say I find the content unworthy of comment. Here is that comment:
I am surprised to see Zack Greinke on this list and I am saddened to see Lincecum.
Bip, I can think of at least a few things to note with a guy like Greinke (and maybe Lincecum, too):
1. Just because their four-seamers are “average” in terms of motion, velocity, usage, etc., doesn’t mean they can’t throw a great one when they need to. This is just a couple hundred pitches have average out over the last year and a half.
2. With Greinke especially, this isn’t his best pitch, or his strikeout pitch. Greinke (and other guys) throw 5-6 pitches and vary speeds within many of them. Even if Greinke’s four-seamer was truly average, it wouldn’t matter: his other pitches make up for it.
3. While this does consider “movement”, it does not consider placement; i.e., the pitcher is not really being credited for command or control here. That’s another thing that Greinke or someone like Oswalt is excellent at.
You probably knew all these things. But even considering all of the above, it’s still surprising to see some of these guys here. In the case of Lincecum, he still has movement in his four-seamer — at least relative to the guys listed here — but he doesn’t use it as much and his velocity has become pretty pedestrian.
In Lincecum’s case, I’m sure that before this year his fastball was too fast to appear on this list, meaning that he’s lost enough velocity to bring it down to average levels. I actually haven’t studied Greinke much, but I think I assumed his fastball was also a lot faster than average.
Greinke’s fastball is faster than average. It’s the amount he uses it (very near average) and the Whiff% that bring him back toward the mean. The relatively low Whiff% could be for any number of reasons, possibly that he doesn’t use it as a strike-out pitch, but perhaps in situations when batters are taking a pitch. It would be interesting to see SwgStr% vs. Str%.