Tuesday, January 1, 2008
The Wang Effect?
If you're a baseball fan with at least some proclivity towards stats, you're probably familiar with Voros McCracken's DIPS theory. McCracken basically stated that a pitcher's ability to control what happens on balls in play is variable and volatile. Some overly extreme devotees to this theory take it to mean that a pitcher has zero control over a ball hit into play, but that's not really true. If it was, you wouldn't have groundball pitchers and fly ball pitchers. Also, selection bias would mean that anyone who reaches the majors may have a certain level of skill on balls in play that allowed them to get that far. I still think DIPS theory is useful in many ways, primarily because it taught me to look more closely at a pitcher's peripherals, but it's really just a fraction of any evaluating of pitching that I do.One of the often-stated mantras about Chien-Ming Wang is that he generates easily fieldable ground balls, which means his success despite a low strikeout rate is not really that much of a fluke. It's possible this is true, at least in the regular season, but is there a way to quantify it?
I recorded zone rating daily throughout 2007 to see if I could use the day by day data to answer questions like this. Here's a look at what the numbers showed.
| Split | G | GS | Ch | INN | PO | A | E | DP | ZR | PM | Diff |
| Team Total | 1307 | 1133 | 3054 | 10150 | 3211 | 1337 | 74 | 450 | .830 | 2535 | -18 |
G: Games
GS: Games started
Ch: Fieldable chances as defined by zone rating
INN: Defensive innings
PO: Putouts
A: Assists
E: Errors
ZR: Zone rating (PM/Ch) PM: Plays made Diff: Plays made compared to average This is how the Yankees did as a team in 2007. Overall they made 18 plays fewer than average.
Here's a look at how the team did in the games Wang started. This does include all innings in those games including those not pitched by Wang, but I have no way to separate those out.
| Split | G | GS | Ch | INN | PO | A | E | DP | ZR | PM | Diff |
| Wang Total | 248 | 215 | 591 | 1957.1 | 631 | 318 | 7 | 96 | .853 | 504 | 10 |
Interesting, huh? In the games that Wang pitched, the team was 10 plays better than average.
Lastly, here's the team in games Wang did not start.
| Split | G | GS | Ch | INN | PO | A | E | DP | ZR | PM | Diff |
| Total - Wang | 1059 | 918 | 2463 | 8192.9 | 2580 | 1019 | 67 | 354 | .825 | 2031 | -28 |
A few things to bear in mind about this data before we make too much of it.
1) It's only one year. Unfortunately no one I know of tracked daily zone rating before this season so sample size is an issue.
2) Like I said, this includes innings pitched by relievers and not just Wang. That muddies the numbers up a little.
3) BIP (ball in play) distribution. Perhaps Wang's balls in play just happened to find their way to the better fielders on the team? We can check that too.
| Player | Pos | wG | wINN | wCh | wPM | wZR | wDiff | nwG | nwINN | nwCh | nwPM | nwZR | nwDiff | ZR Ratio | ||
| Phillips, Andy | 1B | 13 | 90 | 17 | 14 | .824 | 0 | 44 | 341 | 73 | 62 | .849 | 1 | 97.0% | ||
| Mientkiewicz, Doug | 1B | 13 | 79 | 16 | 13 | .813 | 0 | 57 | 379 | 73 | 61 | .836 | 0 | 97.2% | ||
| Cairo, Miguel | 1B | 4 | 33 | 13 | 9 | .692 | -2 | 18 | 123.1 | 29 | 23 | .793 | -1 | 87.3% | ||
| Phelps, Josh | 1B | 5 | 23 | 6 | 4 | .667 | -1 | 24 | 139.3 | 21 | 18 | .857 | 0 | 77.8% | ||
| Betemit, Wilson | 1B | 3 | 21 | 1 | 0 | .000 | -1 | 11 | 53.1 | 17 | 14 | .824 | 0 | 0.0% | ||
| Giambi, Jason | 1B | 4 | 21 | 7 | 4 | .571 | -2 | 14 | 100 | 19 | 17 | .895 | 1 | 63.9% | ||
| Nieves, Wil | 1B | 1 | 6 | 1 | 1 | 1.000 | 0 | 0 | -5 | -1 | -1 | 1.000 | 0 | 100.0% | ||
| Damon, Johnny | 1B | 1 | 6 | 2 | 2 | 1.000 | 0 | 4 | 2.1 | -2 | -2 | 1.000 | 0 | 100.0% | ||
| Cano, Robinson | 2B | 30 | 267 | 117 | 105 | .897 | 9 | 129 | 1141 | 401 | 333 | .830 | 3 | 108.1% | ||
| Rodriguez, Alex | 3B | 30 | 258 | 85 | 70 | .824 | 5 | 124 | 1072 | 285 | 213 | .747 | -4 | 110.2% | ||
| Phillips, Andy | 3B | 2 | 10 | 2 | 2 | 1.000 | 0 | 7 | 7 | 0 | 0 | .000 | 0 | 0.0% | ||
| Cairo, Miguel | 3B | 2 | 5 | 2 | 1 | .500 | -1 | 5 | 30 | 8 | 8 | 1.000 | 2 | 50.0% | ||
| Gonzalez, Alberto | 3B | 1 | 2 | 1 | 1 | 1.000 | 0 | 0 | 0 | -1 | -1 | 1.000 | 0 | 100.0% | ||
| Jeter, Derek | SS | 28 | 242 | 105 | 85 | .810 | -1 | 127 | 1076 | 372 | 280 | .753 | -25 | 107.6% | ||
| Betemit, Wilson | SS | 3 | 18 | 3 | 2 | .667 | 0 | 5 | 21 | 6 | 6 | 1.000 | 1 | 66.7% | ||
| Cairo, Miguel | SS | 4 | 17 | 3 | 2 | .667 | 0 | 12 | 35 | 26 | 22 | .846 | 1 | 78.8% | ||
| Gonzalez, Alberto | SS | 2 | 10 | 5 | 4 | .800 | 0 | 9 | 29.2 | 14 | 11 | .786 | 0 | 101.8% | ||
| Matsui, Hideki | LF | 19 | 159 | 37 | 33 | .892 | 1 | 93 | 821 | 212 | 172 | .811 | -11 | 109.9% | ||
| Damon, Johnny | LF | 10 | 87 | 15 | 14 | .933 | 1 | 22 | 184 | 64 | 54 | .844 | -1 | 110.6% | ||
| Cabrera, Melky | LF | 2 | 17 | 5 | 5 | 1.000 | 1 | 16 | 125 | 29 | 26 | .897 | 1 | 111.5% | ||
| Thompson, Kevin | LF | 3 | 12 | 1 | 1 | 1.000 | 0 | 2 | 10.2 | 6 | 5 | .833 | 0 | 120.0% | ||
| Cairo, Miguel | LF | 1 | 8 | 9 | 8 | .889 | 0 | 2 | 5 | -6 | -6 | 1.000 | -1 | 88.9% | ||
| Cabrera, Melky | CF | 28 | 239 | 68 | 63 | .926 | 3 | 103 | 833 | 312 | 280 | .897 | 4 | 103.2% | ||
| Damon, Johnny | CF | 6 | 50 | 13 | 13 | 1.000 | 1 | 42 | 327 | 121 | 106 | .876 | -1 | 114.2% | ||
| Abreu, Bobby | RF | 30 | 262 | 53 | 44 | .830 | -2 | 127 | 1071 | 307 | 265 | .863 | -2 | 96.2% | ||
| Duncan, Shelley | RF | 2 | 12 | 3 | 3 | 1.000 | 0 | 6 | 31 | 9 | 8 | .889 | 0 | 112.5% | ||
| Sardinha, Bronson | RF | 1 | 2 | 1 | 1 | 1.000 | 0 | 3 | 10 | 2 | 2 | 1.000 | 0 | 100.0% |
Columns prefaced with a w are the stats in the games started by Wang, columns prefaced by an nw are the non-Wang games. The ZR ratio is the difference between each player's zone rating in Wang games and non-Wang games. A percentage less than 100 means they were worse in Wang's starts and a percentage greater than 100 means they were better in Wang's starts. I'm not looking at runs saved here, but plays made above/below average. Rough rule of thumb is .8 runs per play although it varies a bit by position
Again, I don't know how meaningful this is due to the sample size and non-Wang innings in the 30 Wang games but I think it's pretty cool to look at. Robinson Cano, Derek Jeter, and Alex Rodriguez all had better zone ratings in Wang's starts than in the other games. The first base collective did worse. (wil Nieves at first? WTF?). What's interesting to me is that even the OF saw a boost in games started by Wang, with the exception of RF and Bobby Abreu.
I don't think we can say with any absolute certainty that Wang does allow more easily fieldable balls in play than the typical pitcher, but there's at least circumstantial evidence that he may. It'll be something worth following going forward. It may also make us want to think a little bit more about DIPS theory and about how we assess defense. Just like pitching is partly-related to defense, perhaps defense is partly-related to pitching.
Comments
Interesting stuff, SG. Most mainstream commentators/broadcasters like to say that fielders are better, more alert, and “not back on their heels” when they’re playing behind a pitcher who throws a lot of strikes and works quickly. I have never really given much credence to that, but hmm . . . . Offhand, I can’t recall if Wang is a quick worker but he throws a higher percentage of strikes than the average starter, doesn’t he? I wonder whether that’s showing up in your findings on the team’s glovework behind him.
Cool study.
It might be interesting to look at other similar pitchers - maybe Brandon Webb? It would be impossible but fun to also look at Mariano, who seems to produce a lot of _hard_-to-field GBs.
fielders are better, more alert, and “not back on their heels” when they’re playing behind a pitcher who throws a lot of strikes and works quickly
I think another one that goes right along with that, is that when there AREN’T a lot of balls in play, the fielders kinda fall asleep as well. The broadcasters are generally referring to walks when they talk about that, but I would suppose strike-outs fit into that as well. Wang definitely has a lot of BIP…
It’s going to be interesting with the rest of his career, if his K-rate doesn’t go up appreciably but he still puts up decent numbers. I can certainly see Wang being successful until like his age-35 season, and then one of the “pure” statisticians jumping up and saying, “see, he is a fluke!!!”.
What this appears to suggest is that more difficult balls (harder shots?) are hit to the right side (first base and right field) off Wang than to any other areas of the field, right?
That suggests a few further things - that, if you take out right field & 1st base, the unusual nature of these numbers will even more obviously pronounced. And also, equally obviously, that defense at these positions acquires increased importance when he’s pitching.
On the other hand, there appear to be more balls hit to left and center (taken individually) than to right, and to every other infield position than to first. So… do balls hit close to the right field line represent Wang failures?
Very, very interesting stuff!
Incidentally - first time, long time!
acquires -> acquire
And that Wang should always be brought in to pitch to Sheffield.
Just like pitching is partly-related to defense, perhaps defense is partly-related to pitching.
Perhaps?
“Much of what we think of as pitching is really defense, and much of what we think of as defense is really pitching.”—Bill James, about twenty years ago, IIRC.
Sometimes it seems as if half of Sabermetrics is the rediscovery of things that have always been obviously true to anyone who has ever seriously watched any significant amount of baseball. And the other half is stating these obvious things in ways that irritate half of the people who have always known them to be true. Present company excluded, of course.
Oh, and Happy New Year, too.
Frog—
I read an analysis of fast working pitchers versus slow working pitchers somewhere in the past year—probably Hardball Times. IIRC their conclusion was that no, there is NO negative effect on a defense behind a slow pitcher. Sort of what you’d expect given that every TV analyst says there is such an effect.
However, 1. My memory is faulty, and 2. Even if I DO remember correctly, the HT guys do a lot of “quick and dirty, food for thought” type stuff—not necessarily comprehensive analyses.
Here’s some interesting stuff for the baseball fan. Scroll down to the references, there’s a link to a story by Jim Kaat (!) in Popular Mechanics.
http://www.straightdope.com/mailbag/mbaseballs.html
Offhand, I can’t recall if Wang is a quick worker but he throws a higher percentage of strikes than the average starter, doesn’t he? I wonder whether that’s showing up in your findings on the team’s glovework behind him.
I think Wang is an efficient worker (fewer pitchers per batter faced) and that could definitely have some impact.
It might be interesting to look at other similar pitchers - maybe Brandon Webb?
Yeah, Webb, Carmona and Halladay spring to mind as guys who it’d be interesting to look at.
What this appears to suggest is that more difficult balls (harder shots?) are hit to the right side (first base and right field) off Wang than to any other areas of the field, right?
At least in 2007 lefties hit Wang harder than righties, and that could definitely be what we’re seeing with the RF line effect.
Sometimes it seems as if half of Sabermetrics is the rediscovery of things that have always been obviously true to anyone who has ever seriously watched any significant amount of baseball.
No doubt, but it’s always cool to try and quantify conventional wisdom statistically.
And the other half is stating these obvious things in ways that irritate half of the people who have always known them to be true.
#### you.
#### you.
Did you miss this part: Present company excluded, of course. wink? Or am I missing a hidden smiley of your own?
Or am I missing a hidden smiley of your own?
Yes.
Good. So we’re back to Happy New Year then.
i am VERY interested to see what happens to Wang this year. there has been some talk this winter about signing Wang to a long term deal, but i don’t think the Yankees should think about that until next offseason.
he is probably the most unique pitcher in all of baseball, and i think the Yankees would be smart to collect all of the information they possibly can before committing long term.
there were just a few unanswered questions after the 2007 season, enough to give me a tiny bit of doubt going forward. i am a big Wang fan (heh), so i would love to see him answer those questions this year.
Good. So we’re back to Happy New Year then.
I prefer Merry New Year but I am willing to conform. Happy New Year to all.
he is probably the most unique pitcher in all of baseball, and i think the Yankees would be smart to collect all of the information they possibly can before committing long term.
I think you’re right. His statistical profile is so unique that there’s no way to know what he will do over the next five years. He’s a tick away from imploding, and a tick away from being one of the top pitchers in baseball, and the likelihood of either happening is probably just about the same.
There’s also the rotator cuff tear that’s lingering in the background. I think how the Yankees deal with Wang will depend a lot on Hughes/Joba/IPK and what they end up doing this year.
If the Holy Trinity develops as hoped, and the Yanks get a good season from Horne/Marquez and one of the TJ patients (Garcia), I could see the Yanks shipping Wang for a couple of younger position players. If Wang can win 20, or come close again, he could fetch a lot.
That said, I’d still like to keep him, no matter how well he does.
I think the Yanks will be able to move Horne and or McCutchen for any position player help they need. Both are older prospects who may not have a position in the lineup if all goes as planned. Better to trade them high than have them die on the vine, so to speak.
I don’t think anyone argues that Wang causes players to put balls into play which are more easily fieldable. Wang causes lots of balls to be hit on the ground, where the fielders are more densely packed than in the outfield. So the ball is more likely to be hit in the vicinity of a fielder.
What you don’t account for however, is that because of Wang’s low strike out rates, he also allows more balls to be put into play when compared to the average pitcher. It’s well known that groundball pitchers typically have high hit rates because of this. But even though they allow more baserunners, they’re also able to get more double plays and limit the amount of extra base hits given up.
So since Wang allows more baserunners than the typical pitcher, his success doesn’t lie in causing batters to hit easily fieldable balls. Rather, it lies in his success to cause batters to hit easily fieldable balls when there are other runners on. Creating double plays is the only way in which Wang can combat the extra base runners he allows. And there is a certain degree of luck in how easily a double play can be made on a groundball. That’s why groundball pitchers are often unpredictable.
“What you don’t account for however, is that because of Wang’s low strike out rates, he also allows more balls to be put into play when compared to the average pitcher.”
Well, it’s pretty obvious to anyone with a brain that a pitcher who doesn’t strike people out allows more balls in play. I’m not sure why that needs to be spelled out.
“Creating double plays is the only way in which Wang can combat the extra base runners he allows. “
Player A WHIP: 1.294
Player B WHIP: 1.324
Player A is a guy who according to you is a ground ball pitcher who allows extra base runners. Player B is a strikeout/fly ball pitcher.
A = Wang
B = Matsuzaka
Basically what I’m saying is, what is your point?
What I would like to see, if at all possible, is this data split up for home and away games considering the huge ERA disparity between the two for Wang (although, FIP is surprisingly close in the split).
Basically what I’m saying is, what is your point?
I don’t know. Maybe his point is that walks don’t count. Or maybe it’s that extreme groundball pitchers should be required to walk more guys to make things fair. Or something.
...groundball pitchers are often unpredictable.
And yet Wang has performed with remarkable consistency for over 500 major league innings. When is this unpredictability going to manifest itslef?
When is this unpredictability going to manifest itslef?
hopefully not in the 2007 ALDS!
ouch. just kidding. i am with you for the most part, but Wang is such a funny case that i wouldn’t bet either way on how he will fare next year.
“i am with you for the most part, but Wang is such a funny case that i wouldn’t bet either way on how he will fare next year.”
Wang might be funny, but in a highly predictable, good way.
Totally off topic as usual, the thought of 3 assholeios firing a slingshot at a tiger and having that brave act result in the evisceration of one and mauling of the other two, fills me with a warm feeling.
Sort of ,The What Comes Around Goes Around cliche in Hi Def. Or hi death.
Too bad they capped the angry feline ( if its true)
Woulda liked to be a Panda inna tree for that one.
This post is a perfect example of why I should never watch MSNBC.
I didn’t read all 23 posts, but I don’t think anyone mentioned the key to Wang’s (and sinkerballers in general) success: ground balls are NEVER HOME RUNS. Wang allowed just 9 (!) home runs last year, just 12 the year before that and 9 in 2005. That is simply awesome. He has allowed only 31 home runs in his career. Beckett allowed 36 home runs in 2006 alone (100% the cause of his crappy season that year, since his peripherals were otherwise strong).
You guys can talk about all you want about fielders being on their toes or back on their heels and stuff like that, but the difference in BABIP and ERA between Wang and a flyball pitcher can mostly be attributed to the fact that home runs are never outs. Add 20 solo home runs to Wang’s total last year and his ERA goes to 4.70—before you even take into account what would happen if guys were ever on base when those balls theoretically left the yard.
It’s as basic as that. If Wang can maintain his home run rates, he will continue to succeed.
HRs and walks. but yeah, basically that’s it.
Isn’t this all tautological?
But wouldn’t any pitcher who had a successful year partly due to BABIP show the same boost in ZR w/ his fielders- whether it’s because of luck or skill? Isn’t the way to parse out skill from luck just to look at the BABIP over a much more meaningful sample size?
We already knew he has a low BABIP. What does looking at ZR add?
I’d just like to second dannux’s point and basically say that rather than being an outlier, Wang is actually a perfect example of a pitcher’s DIPS versus performance. The three components to DIPS are strikeouts, walks, and homeruns. Wang doesn’t strike many guys out, but he rarely walks them and gives up very few homers. So he’s a good pitcher. I don’t think this is really a mystery.
Some people seem to think that without the strikeouts, there’s some “correcting factor” that will eventually manifest itself and will prove Wang isn’t that good. Well, that factor can’t be very large as long as Wang maintains his walk and home run rate, can it?
Some people seem to think that without the strikeouts, there’s some “correcting factor” that will eventually manifest itself and will prove Wang isn’t that good.
Now put me in the camp of those that believe Wang is as good as we have seen. But I think the argument for the K-rate spelling his decline is that there hasn’t been a pitcher with this low of a K-rate - compared to the league of course - who has been successful over a career. The ones who are successful are only for a year or so. I think there have been a lot of studies that correlate K-rate to success.
The thing is Wang GB/FB rate is so severe, that I don’t think a lot of people believe he can keep it up. Therefore the thinking goes, “his GB rate isn’t sustainable, so if his K-rate doesn’t improve, then his HR’s will go up, and he’ll be a bad pitcher”. But if he can keep is GB rate steady for another couple of years, I think that argument will start to fade; and you’ll also see more pitchers try to develop a power-sinker!
I’ve said before, I think Wang is a GOOD pitcher, and will continue to be a good pitcher. But if he can get that K-rate up to about 6.5/9IP, I think he will be a GREAT pitcher.
the difference in BABIP and ERA between Wang and a flyball pitcher can mostly be attributed to the fact that home runs are never outs
Except that HRs don’t figure into BABIP, since they aren’t balls in play.
We already knew he has a low BABIP. What does looking at ZR add?
It’s an (admittedly limited and flawed) attempt to understand why the BABIP is low.
But here’s the other thing—aside from 2005, Wang’s BABIPs are not exactly freakish. Among starting pitchers with 100 or more IP, he was 36th (of 126) in 2006 and tied for 46th (of 127) in 2007. So he’s been better than average, but not some kind of unprecedented outlier. The DIPS argument against Wang made some sense after his rookie year—he had an ERA+ of 105 on the strength of a BABIP in the .250’s, and that didn’t look sustainable. Well, the BABIP wasn’t sustainable and it did rise, but his ERA went down and his WHIP stayed the same. You can attribute part of the 2007 success to actually striking out a few guys once in a while, but that certainly wasn’t the case in 2006.
What I would like to see, if at all possible, is this data split up for home and away games considering the huge ERA disparity between the two for Wang (although, FIP is surprisingly close in the split).
There was a thread linked to this entry over at Baseball Think Factory where John Walsh of the Hardball Times posted a couple of splits.
John Walsh Posted: January 02, 2008 at 05:32 PM (#2658655)
I did a quick query on the fraction of ground balls that result in outs for Wang and for all other Yankee pitchers from 2005-2007. Here are the results:+————-+———+———+————————-+
| Pitcher | gb | outs | gb_out_fraction |
+————-+———+———+————————-+
| Other | 5184 | 3710 | 0.7157 |
| Wang | 1134 | 867 | 0.7646 |
+————-+———+———+————————-+Wang does give up more fieldable ground balls.
The home/away splits for Wang are pretty interesting, too:
+———+——-+———+————————-+
| H/A | gb | outs | gb_out_fraction |
+———+——-+———+————————-+
| Home | 641 | 503 | 0.7847 |
| Away | 493 | 364 | 0.7383 |
+———+——-+———+————————-+Looks like the grounds crew are earning their keep.
John Walsh Posted: January 03, 2008 at 03:56 AM (#2658872)
Here are the numbers with turf parks removed:+———+——-+———+————————-+
| H/A | gb | outs | gb_out_fraction |
+———+——-+———+————————-+
| Home | 641 | 503 | 0.7847 |
| Away | 348 | 262 | 0.7529 |
+———+——-+———+————————-+
The difference gets smaller and, in fact, is not statistically significant anymore.
Seems that Wang’s road problems are in a big part turf-related.
Isn’t this all tautological?
Maybe.
But wouldn’t any pitcher who had a successful year partly due to BABIP show the same boost in ZR w/ his fielders- whether it’s because of luck or skill?
Probably, but it wouldn’t necessarily be so uniformly spread among the infielders.
What does looking at ZR add?
More granular data about the actual distribution of the balls in play? Maybe that’s not of any use to you but I think it can be informative. Also, there may be some useful information about the fielders in here. It’s interesting to me that Derek Jeter was so much better behind Wang.
Also FWIW, in that same BBTF thread linked above, mgl (one of the more well-known sabermetric researchers particularly in the area of defense) posted this, which jibes with Walsh’s data:
Ground ball pitchers DO allow easier to field ground balls and fly ball pitchers allow easier to field fly balls. I make adjustments in UZR for the GB/FB ratios of the pitchers behind each fielder. So the first thing to do is to compare Wang’s GB out rate to that of other extreme GB pitchers. I think you will find that it is not all that different.
Wang is not an outlier. As I’ve posted a thousand times, his FIP matches up fairly closely to his performance. There’s nothing inherently fluky about Wang’s performance, except maybe the fact that he has a lower BABIP than the typical ground ball pitcher. This data and Walsh/MGL’s comment make me think it’s more sustainable than I’d expect it to be.
“Ground ball pitchers DO allow easier to field ground balls and fly ball pitchers allow easier to field fly balls.”
This because GBPs who allow hard-to-field GBs don’t make it, and ditto for G->F, and then one compares one group to the other.
An interesting thing to consider but surely unquantifiable would be batter approach for GB vs FB pitchers.
I had a question about Phil Hughes. He’s had a low BABIP throughtout his career and a low one in the majors, is this a cause for concern?
I had a question about Phil Hughes. He’s had a low BABIP throughtout his career and a low one in the majors, is this a cause for concern?
For me, no. I’d rather see someone show a repeated ability to control BABIP than not. It’s a good indicator to me that Hughes’s stuff is harder to make good clean contact on.
I’ve got Hughes projected to put up a 3.88 ERA this season in the latest version of CAIRO based on his career BABIP(MLEs and majors) which comes in around .276. Adding some regression towards the mean takes his projected BABIP to .281, but his peripherals (BB, HR, K) give a FIP of 3.84.
If we regress his BABIP to league average (.305 or so) his ERA would go to around 4.20. A BABIP of .330 would give him an ERA of 4.50 which is a touch worse than my projected league average for a Yankee pitcher (4.46).
So nah, I don’t worry about Hughes’s ability. His health would be a bigger worry for me.
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