Tag Archives: wins

Could We Assign “Wins” Differently?

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If you’ve been here before, or someone like Brian Kenny tweeted a link to this post, you know that we are big proponents of the #KillTheWin movement. We don’t like wins and losses as a pitching statistic for many reasons. You can pitch well and not get a win, you can pitch terribly and get a win, wins don’t even out, and wins are extremely misleading. Put simply, wins are dependent on things that pitchers can’t control and it’s silly to measure them based on something their teammates do. Here are links to all of our formative #KillTheWin work:

But today I’d like to address a solution that a lot of people are calling for. You see, the old guard won’t let go of the wins and losses concept and language. They can’t accept things like FIP, xFIP, and WAR, or even K%, BB%, GB%. Even ERA is doesn’t satisfy their longing for the “W.” So I’d like to propose a simple idea that simply changes the methodology for awarding wins and losses. Currently, a starter has to pitch at least 5 innings, leave with a lead, and not watch the bullpen surrender that lead. If we invented wins and losses today, no doubt we wouldn’t use such a silly rule.

So let’s use a better one. If there is an appetite for Wins and Losses, why don’t we actually tie wins and losses to performance? Here are two basic proposals that do that while solving a couple of key issues with wins.

The first problem with wins and losses is that it depends on how much and when your team scores. So what we want is something that only measures the impact of the pitcher on the game. Another problem with wins and losses is that the no-decision essentially erases everything you did on a given day. If a pitcher throws 7 shutout innings and gets a no decision, that game shows up in every single one of his stats except wins and losses. We want to judge every start a pitcher makes, not just one in which the right conditions are met by his offense and bullpen.

To partially resolve this issue, let’s turn to the 2013 Tigers as an example. Instead of wins and losses as determined by the current rule, what if we allocate them by Win Probability Added (WPA) or Run Expectancy 24 (RE24)? Those two stats are a bit complicated to calculate, but extremely easy to understand. WPA reflects the percentage by which a player improved his team’s chances of winning. It is very context dependent, but you can still earn positive values even when your team is losing. RE24 is a similar statistic except it doesn’t pay attention to the score of the game and just reflects how many runs above or below average you are contributing. Think of it this way, in a 10-0 game a solo homerun has a pretty low WPA because the game is already decided, but it has the same RE24 in a 10-0 as it does in a 2-0 game. Both allow for the addition of value in a context dependent sense, but both also allow a player to add value even when his team is not. Both of these stats are readily available on FanGraphs and Baseball-Reference.

Below I present the 2013 Tigers with WPA and RE24 “wins.” If a pitcher has a positive WPA or RE24 for a single game they get a win. If it’s negative, they get a loss. No no-decisions and no concern about how the game actually ended. Did the pitcher improve his team’s chances of winning a single game? That’s what wins and losses should tell us, so let’s try this.

There are obvious weakness to this approach, namely that I’m not addressing by how much a pitcher helped his team, but to answer that question, we have season long numbers that are more important. This approach is meant to give people who want to see wins and losses a better reflection of true value.

Pitcher Starts W-L WPA W-L RE24 W-L
Fister 28 12-7 18-10 19-9
Sanchez 24 12-7 16-8 17-7
Scherzer 27 19-1 22-5 22-5
Verlander 29 12-10 17-12 18-11
Porcello 26 11-7 15-11 16-10

You will notice a couple of things. You’ll notice that Scherzer’s no-decisions are primarily the function of his team bailing him out and Fister, Sanchez, and Verlander’s are almost all a case of the Tigers not providing enough run support. Porcello’s are divided pretty evenly. This is interesting because it shows that even on individual teams, wins/losses/no decisions are handed out irregularly despite the same contingent of position players.

For the die-hard #KillTheWin-er, this approach is still too context dependent and derived from an illogical attempt to hand wins and losses to a single player. But for a more traditional observer, hopefully this is compelling. Even if you like wins and losses, surely you can appreciate that the actual way in which wins and losses are assigned is arbitrary and foolish. Why is 5 innings the cutoff? Why do you not get a win if you pitch 8 shutout innings and your team wins in a walkoff? Why should you get a win if you allow 6 runs? Even if you want to track day to day contribution, at least track it in a way that reflects what the player you’re judging actually did.

Now I’m not sure if this is the best way, but this is definitely an improvement over wins and losses as currently defined. The current stat makes no contribution to analysis, this one makes some contribution. I’d still rather pay attention to season long numbers, but if we’re going to judge a player in each individual game, let’s at least do it right.


Jon Heyman Kills The Win While Trying to Save It

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Here at New English D we are on the front lines of the #KillTheWin movement. If you’re new to the site and are open-minded, please check out our 5 part series on why wins aren’t useful:

All of those links make a singular case. Wins are not useful when evaluating individual pitchers. The goal of baseball fans and analysts is to properly understand the game we love. Wins don’t cause poverty, but wins are detrimental to our understanding of baseball because so many people use them as a measure of value, which they are not.

Today, Jon Heyman wrote about Max Scherzer (currently leading the league in wins by a lot) and couldn’t resist fighting back against the #KillTheWin movement. He makes several points. First, he argues that Scherzer should narrowly beat Felix for the AL Cy. Hey, we agree on that! Second, he says those of us trying to kill the win are wasting our time. That’s silly because we enjoy killing the win and baseball is about having fun, but I’m not going to engage in pettiness when the real issues are much more important.

Next, Heyman says:

Wins do matter (though clearly not nearly as much as we once thought — and I give the stat guys credit for pointing this out.) No starter gets to 19-1 only because they are lucky, or because they “happened” to be “standing on the mound” when his team scored a ton of runs, as some would have you believe.

So here we see Heyman acknowledge that he places less stock in wins today that he used to. Meaning that he was wrong before and therefore could be wrong again. Furthermore, Heyman says no one goes 19-1 because of luck/happenstance/standing on the mound. Actually, Jon, they do. Scherzer is an excellent starting pitcher, but he is not meaningfully better than Felix. Certainly not better than Kershaw or Harvey. Yet he has many more wins than they do and many fewer losses. The difference is that the Tigers score crazy amount of runs for Scherzer because they are really good at scoring runs. Additionally, he gets more runs than his other rotation-mates. Scherzer gets 7.32 runs per 9. Felix gets 4.73. Chris Sale gets 3.03.

Even if you want to dramatically oversimplify baseball and assume a pitcher controls everything that happens when he is on the mound (he doesn’t), he still has no control over what his offense does. In order to get a win, you have to be in the game when your team takes the lead for the final time. If you team doesn’t score, or scores AT THE WRONG TIME, you do not get a win regardless of how you pitched.

It’s obvious that Heyman knows this based on his comments throughout the piece:

There are a lot better numbers to illustrate a pitcher’s performance over a season than wins and losses.

But does that mean a pitcher’s record is now totally worthless?

Heyman argues that wins are not the most important thing, but that they are not worthless. Which poses the important question at which I will now arrive. What do wins tell us that we can’t see in other stats?

What is the value of seeing a W/L record beyond seeing things like ERA, K%, BB%, GB%, FIP, xFIP, WAR, RE24, SwStr%, IP, etc? What do wins and losses add to the discussion?

Nothing. Not one thing. Heyman says consistency, but that isn’t the case. Check out the link about about “misleading” and you’ll see that argument doesn’t hold water. Good, consistent pitchers can win less often than bad and inconsistent ones. Heyman says wins aren’t about being in the right place at the right time, but they clearly are. The Tigers score a disproportionate number of runs for Scherzer than they do for his teammates. Scherzer is both good and lucky. They aren’t mutually exclusive, but that doesn’t mean he should get credit for something he had nothing to do with.

Scherzer is great. He has an excellent W/L record. Those two things are related, but not highly related. Good pitchers, on average, win more often than bad ones because they have some control over the number of runs they allow but that doesn’t mean judging a player by wins and losses is useful. It adds nothing to our understanding and does more harm than good. Heyman cites Tillman making the ASG as case and point.

Wins influence people’s thinking, whether it’s Tillman in the ASG or it’s Dusty Baker leaving Bailey on the mound when he was losing it so he could “have a chance to get a win.”

My argument here is that wins provide us with no meaningful information and at best are trivial and at worst are negatively impacting games. Heyman concludes:

The goal, ultimately, is to win games when a pitcher takes the mound, and Scherzer has done that better than anybody. Yes, there is a lot of luck involved in getting pitcher wins. But in Scherzer’s case, he has pitched great, too, and no one should claim he hasn’t.

Which is interesting, because the Scherzer is getting a lot of luck as far as wins go. Sale isn’t pitching as well as Scherzer, but he’s not pitching 9-12 to 19-1 worse. Also, Heyman is using a strawman argument in his closing. No one, not one single person, thinks Scherzer hasn’t been great. He’s been amazing. Fantastic. Cy Young or very close to it, brilliant. That’s not what this is about at all. He’s 19-1 and Chris Sale is 9-12. He’s not “10 wins” better than Sale. Not under any real definition of pitching ability or performance. This is a statistic that doesn’t reflect performance at all. It adds nothing to the conversation you can’t get elsewhere. That’s why we want to kill it.

I would like to point out the broader issue. Heyman is actually one of the more evolutionary members of the old guard. He clearly sees the fault in wins, but still wants to defend them. Read his defense. Think about it for yourself, it’s like he wants to hold onto wins because he’s used to them. And that’s not a good reason. “How we’ve always done things” is not a good way to make decisions.

I don’t understand the purpose of Heyman’s argument. Why does he want to save them? What utility do they bring to the conversation? This is not a personal assault on Heyman, but he put his views out there in writing, so they are open to criticism. I’m an academic and a baseball writer, so I know about critical feedback. You’re welcome to criticize my reasoning as well. I can take it, don’t worry. I offered Heyman a chance to clarify his message on Twitter and he has yet to do so. If he writes back, I’ll be glad to amend this post.

There is no value in looking at wins and losses for a starting pitcher. That’s not about Scherzer or Felix, it’s about analysts and fans. In fact, Heyman and his fellow BBWAA members should use their access to go ask Scherzer about wins, or even Google his quotes on the issue. He gets it and he’s the person who benefits most from looking at wins. If he doesn’t care about them, it’s time to let them go.

12 Other Reasons To Kill The Win

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Over the last few weeks I’ve been breaking down reasons to ignore the pitcher win and I think the case is pretty airtight. First I gave you the 9 best seasons under 9 wins, then I gave you the 9 worst 20 win seasons, and showed you that wins do not even out over a career. Finally, I presented a case study in wins using Cliff Lee and Barry Zito’s 2012 season. The evidence is clear, wins do not reflect individual performance and shouldn’t be used as such. But if you’re not convinced, read this and tell me what you think (all numbers for starting pitchers from 2013 entering 6/13):

  1. A pitcher has gone 6+ IP and allowed 0 ER and not earned a win 68 times.
  2. If you lower that to 5+IP and 0 ER, it goes up to 82 times.
  3. A pitcher has gone 6+ IP and allowed 4 or fewer baserunners and not earned a win 50 times.
  4. A pitcher has gone 6+ IP, allowed 4 or fewer baserunners AND allowed 0 ER and not earned a win 20 times.
  5. A pitcher has gone 8+ IP and allowed 1 or fewer ER and not earned a win 23 times.
  6. A pitcher has gone 8+ IP and allowed 1 or fewer ER and earned a LOSS 4 times.
  7. A pitchers has gone 5 IP or fewer and allowed 10 or more baserunners and earned a win 29 times.
  8. A pitcher has gone 6 IP or fewer and allowed 5 ER or more and earned a win 12 times.
  9. A pitcher has allowed 6 ER or more an earned a win 7 times.
  10. A pitcher has walked 6 or more batters and earned a win 9 times.
  11. A pitcher has allowed 12 baserunners or more and earned a win 23 times. Only two of them went 7 or more innings.
  12. A pitcher has gone 7+IP with 10+ K, 2 or fewer BB, and 3 or fewer ER and not earned a win 28 times.

So let’s review. You can have a great season and win fewer than 9 times. You can have a below average season and win 20. You can have a much better career than another pitcher and finish with the same winning percentage. A pitcher can dramatically out pitch another and have way fewer wins in a season. And finally, the above 12 things can happen…before the All-Star break.

I’ll close with this. In 2012 a pitcher went 7 or more innings and allowed 0 ER 363 times. They didn’t earn a win 57 times in those starts. Do we really care about a statistic that says a pitcher who goes 7 or more innings while allowing 0 ER shouldn’t get a win 16% of the time?

I know I don’t.

A Case Study in Wins

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To bring you up to speed I’ve been laying out evidence over the last few weeks in an effort to help banish the pitcher win as a method for measuring individual performance. I’ve covered a number of topics such as:

The simple complaint with the win statistic is that it doesn’t measure individual performance but is used by people to reflect the quality of an individual. Wins are about pitchers, but they are also about run support, defense, the other team, and luck. We shouldn’t use such a blunt tool when measuring performance when we have better ones. I’ve provided a lot of evidence in the links above supporting this claim, but those have posts about the best and worst and about career long samples. Today, I’d like to offer a simple case study from 2012 to illustrated the problem with wins.

The faces I’ll put on this issue are Cliff Lee and Barry Zito, both of whom appeared on the lists above.

Let’s start with some simple numbers from their 2012 campaigns to get you up to speed. Lee threw more than 25 more inning than Zito and performed better across the board:


Lee had a much higher strikeout rate and much lower walk rate.


Lee had a lower ERA, FIP, and xFIP and if you prefer those numbers park and league adjusted, they tell the same story:



If you’re someone who likes Wins Above Replacement (WAR) or Win Probability Added (WPA) it all points in Lee’s favor as well:


By every reasonable season long statistic, Cliff Lee had a better season than Barry Zito. If you look more closely, you can see that Lee had a great year and Zito had a below average, but not terrible season. There is simply no case to be made that Barry Zito was a better pitcher than Cliff Lee during the 2012 season. None.

But I’m sure you can see where this is going. Cliff Lee’s Won-Loss record was 6-9 and Barry Zito’s was 15-8. Lee threw more innings, allowed fewer runs per 9, struck out more batters, walked fewer batters, and did just about everything a pitcher can do to prevent runs better than Barry Zito and he had a much worse won-loss record. Something is wrong with that. Let’s dig a bit deeper and consider their performances in Wins, Losses, and No Decisions.

Let’s start with something as simple as ERA. In Wins, Losses, and ND, Cliff Lee allowed fewer runs than Zito despite pitching his home games in a park that skews toward hitters and Zito in a park that skews toward pitchers:


In fact, Lee’s ERA in Losses is almost identical to Zito’s in No Decisions. He allowed the same number of runs when he pitched “poorly” enough to lose as when Zito pitched in a “neutral” way. If we take a look at strikeout to walk ratio, it looks even more lopsided:


Lee way outperforms Zito in the measure even if you put Lee’s “worst” starts up against Zito’s “best” ones. Let’s take a look at OPS against in these starts, and remember, Lee pitches in a hitters’ park and Zito in a pitchers’ park:


Again we find that Lee pitches as well in Losses and Zito does in No Decisions and performs much better across the board. Not only does Lee allow fewer runs in each type of decision, he has a better K/BB rate, and a lower OPS against in pitching environments that should favor Zito.

Everything about their individual seasons indicates that Cliff Lee had a much better season than Barry Zito and when you break it down by Wins, Losses, and Decisions, it is very clear that Lee performed better in all of these types of events. Lee was unquestionably better. No doubt. But Lee was 6-9 and Zito was 15-8. Zito won more games and lost fewer.

If we look at the earned run distribution, you can clearly see that Lee was better overall, on average, and by start:


You likely don’t need more convincing that Lee was better than Zito, in fact, you probably knew that from the start. Lee was better in every way, but Zito’s record was better. How can wins and losses be useful for measuring a player when they can be so wrong about such an obvious case?

Cliff Lee prevented runs better than Zito last season. He went deeper into games. More strikeouts, fewer walks, lower OPS against in a tougher park. He was better than Zito in Wins, Losses, and ND and often better in Losses than Zito was in ND. How can this be? It’s very simple. Wins and Losses aren’t just about the quality of the pitcher, not by a long shot. Even ignoring potential differences in defensive quality (Giants were slightly better) and assuming pitchers can control every aspect of run prevention it still isn’t enough. Lee was better and had a worse record. What good is a pitching statistic if it is this dependent on your offense? It isn’t any good.

Here friends, are their run support per 9 numbers. This should tell you the whole story:


The Giants got Zito 6 runs a game on average and the Phillies got Lee 3.2. It didn’t matter that Lee way out pitched Zito, he still had no shot to win as many games because the Giants scored runs for Zito and the Phillies didn’t score for Lee. The Giants during the entire season scored 4.4 runs per game. The Phillies scored 4.2. This isn’t as easy as saying that pitchers on better teams win more often. Lee’s team scored much less for him on average and the Giants scored much more for Zito on average.

You can’t just say that a pitcher with a great offense will win more often, it comes down to the precise moments in which they score. How can that possibly have anything to do with the pitchers this statistic hopes to measure? It can’t.

If my global evidence about the subjectivity and uselessness of wins didn’t get you, I hope that this has. There is no justification for using wins to measure pitchers when something like this can happen. Lee was much better than Zito in every way, but if you’re using wins and losses, you wouldn’t know it.

And, just in case you were wondering, Lee was a better hitter too.


The Nine Worst 20 Win Season in MLB History

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To regular readers it will come as no surprise that I’m part of the movement to remove the pitcher won/loss record from our baseball evaluations. I’ve written on the subject quite a bit, both with respect to individual seasons and entire careers, and this piece seems like a perfect fit to round out the discussion. It also helps that I got a direct request for this exact thing after I posted yesterday’s piece:

So what follows are The Nine Worst 20 Win Seasons in MLB history. It gets a little tricky to draw lines here, so let me give you a quick primer. I don’t want this post to be about pitchers who made a lot of starts so they got a lot of wins, but rather about pitchers who performed poorly and still got wins. Therefore, instead of using Wins Above Replacement as I did for the under 9 list, I will be using ERA- and FIP-, which are simply statistics that calculate the difference between a pitcher’s ERA or FIP and league average during that year. Also it controls for park effects, but it’s basically a way to compare an ERA from the deadball era to one from the steroid era.

I would personally prefer to see this done with FIP-, because it better reflects a pitcher’s skill, but I’m going to use ERA- as well so that this piece is more convincing. A pitcher who allows a lot of runs shouldn’t win a lot of games, and you should agree with that if you’re old school or new school.

Additionally, I’ve included lists from 1901-2012 and just 1945-2012 if you’re concerned about the number of starts inflating someone’s win total. That’s fair, so I’ve broken it down into four separate lists, all telling you the same thing. You can have a bad year and win 20 games. 20 games is the old school gold standard of performance, so this cutoff makes sense. If you’ll recall, there have been more than 8,000 qualifying seasons in MLB history and if you try to predict WAR, ERA, or FIP with wins, you get an adjusted R squared of less than .40 in all cases. This isn’t just about a few examples, it’s about the entire population of starting pitchers. For more on this, read the two links above and check out the bottom of this piece.

Here we go.

1945-2012 by ERA-

Rank Season Name Team W L IP ERA-
9 1950 Johnny Sain Braves 20 13 278.1 100
8 1965 Sammy Ellis Reds 22 10 263.2 101
7 1973 Paul Splittorff Royals 20 11 262 102
6 1971 Steve Carlton Cardinals 20 9 273.1 103
5 1970 Jim Merritt Reds 20 12 234 104
4 1980 Joe Niekro Astros 20 12 256 106
3 1972 Stan Bahnsen White Sox 21 16 252.1 113
2 1959 Lew Burdette Braves 21 15 289.2 113
1 1966 Denny McLain Tigers 20 14 264.1 113

1945-2012 by FIP-

Rank Season Name Team W L IP FIP-
9 1971 Dave McNally Orioles 21 5 224.1 110
8 1967 Mike McCormick Giants 22 10 262.1 110
7 1959 Lew Burdette Braves 21 15 289.2 111
6 1990 Bob Welch Athletics 27 6 238 112
5 1958 Bob Turley Yankees 21 7 245.1 112
4 1979 Joe Niekro Astros 21 11 263.2 114
3 1967 Earl Wilson Tigers 22 11 264 114
2 1973 Catfish Hunter Athletics 21 5 256.1 122
1 1966 Denny McLain Tigers 20 14 264.1 123

1901-2012 by ERA-

Rank Season Name Team W L IP ERA-
9 1910 George Mullin Tigers 21 12 289 109
8 1914 Christy Mathewson Giants 24 13 312 110
7 1911 Jack Coombs Athletics 28 12 336.2 110
6 1906 Christy Mathewson Giants 22 12 266.2 112
5 1972 Stan Bahnsen White Sox 21 16 252.1 113
4 1919 Hooks Dauss Tigers 21 9 256.1 113
3 1959 Lew Burdette Braves 21 15 289.2 113
2 1966 Denny McLain Tigers 20 14 264.1 113
1 1903 Henry Schmidt Superbas 22 13 301 118

1901-2012 by FIP-

Rank Season Name Team W L IP FIP-
9 1911 Bob Harmon Cardinals 23 16 348 114
8 1921 Joe Oeschger Braves 20 14 299 114
7 1967 Earl Wilson Tigers 22 11 264 114
6 1903 Henry Schmidt Superbas 22 13 301 114
5 1906 Jack Taylor – – – 20 12 302.1 115
4 1910 George Mullin Tigers 21 12 289 117
3 1908 Nick Maddox Pirates 23 8 260.2 121
2 1973 Catfish Hunter Athletics 21 5 256.1 122
1 1966 Denny McLain Tigers 20 14 264.1 123

And now, to bring the point home even further, let’s put an innings cap at 210 and take a look at 15+ win seasons since 1945 by ERA-

Rank Season Name Team W L GS IP ERA FIP WAR FIP- ERA-
9 2003 Ramon Ortiz Angels 16 13 32 180 5.2 5.26 0.9 119 117
8 1983 Eric Show Padres 15 12 33 200.2 4.17 4.37 0.3 121 118
7 1989 Storm Davis Athletics 19 7 31 169.1 4.36 4.4 0.5 123 119
6 2004 Shawn Estes Rockies 15 8 34 202 5.84 5.54 1 112 120
5 1966 Dave Giusti Astros 15 14 33 210 4.2 3.57 2.6 105 120
4 1999 Kirk Rueter Giants 15 10 33 184.2 5.41 5.01 1.1 113 124
3 1989 Andy Hawkins Yankees 15 15 34 208.1 4.8 4.44 1.2 117 124
2 1969 Steve Blass Pirates 16 10 32 210 4.46 3.72 2 109 126
1 1980 Dan Spillner Indians 16 11 30 194.1 5.28 4.45 1.4 110 130

And now again with FIP-

Rank Season Name Team W L G GS IP ERA FIP WAR ERA- FIP-
9 2012 Barry Zito Giants 15 8 32 32 184.1 4.15 4.49 0.9 110 120
8 1983 Eric Show Padres 15 12 35 33 200.2 4.17 4.37 0.3 118 121
7 1984 Eric Show Padres 15 9 32 32 206.2 3.4 4.23 0.7 97 122
6 1963 Phil Regan Tigers 15 9 38 27 189 3.86 4.58 0 104 123
5 1989 Storm Davis Athletics 19 7 31 31 169.1 4.36 4.4 0.5 119 123
4 1975 Jack Billingham Reds 15 10 33 32 208 4.11 4.43 0.4 114 124
3 2006 Steve Trachsel Mets 15 8 30 30 164.2 4.97 5.5 0.1 114 125
2 1971 Chuck Dobson Athletics 15 5 30 30 189 3.81 4.19 0.1 117 126
1 1950 Tommy Byrne Yankees 15 9 31 31 203.1 4.74 5.51 0.5 107 128

Even when we limit the number of innings a pitcher throws, pitchers can still accumulate wins despite pitching much worse than league average.

So whether you like the simple and easy ERA or the more predictive and true FIP, here you have plenty of evidence that winning a lot of games doesn’t mean you had a good season. Guys on this list were 10 and 20% worse than league average in these seasons and still won the magic 20 games. This is further proof that wins do not reflect a pitcher’s individual performance.

You can be worse than average and still win at an elite level. Last week I showed how you can be much better than average and win fewer than 10 games. Yesterday, I showed that this isn’t a small sample size, single season trick. This is true in small samples and in large samples.

Here’s a quick look at every individual season in MLB history again up against ERA-. There is a trend, but the variation is huge. The adjusted R squared is .3046, meaning wins can only explain 30% of the variation in ERA relative to league average.


FIP- actually makes wins fare worse, at .1709 adjusted R squared. I won’t bother showing the graph because this one makes the point just fine. You can have an all time great season at run prevention and win 10 games and you can have a well below average season and win 20. Wins are about many factors and pitching is just one of them. You can have a great outing, great season, and great career and never get the wins you deserve and the exact opposite is true as well.

It’s time to outgrow the win and start talking about things that actually measure performance. Even if it’s ERA, which isn’t even the best way to do things. Let’s look at innings and strikeouts and FIP and WAR and everything else. Wins are the oldest statistic there is but they’ve long since lost their usefulness.

If you’re someone who believes heavily in wins, I challenge you to write a cogent response that defends their use. I’d be happy to publish it if you don’t have your own forum and will respond to your arguments. I want to be someone who helps move sabermetrics from a niche tool to the mainstream and I don’t want this to be about drawing lines between people who love baseball. This is my argument against wins, I hope that you take it to heart and really think about it.

Ask questions, look for evidence, and let’s talk about baseball. Share this with people who love wins and hate them. This shouldn’t be a partisan debate between the new and old, it should be about knowledge and fun. Always.

What About Pitcher Wins With A Long Lens?

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This season, the debate between those who like using wins to judge pitchers and those who want nothing more than to forget that statistic exists has heated up and we’ve seen the movement heavily publicized by MLB Network’s Brian Kenny, who takes on “wins” on a daily basis.

The argument against using wins is simple. The way pitcher wins are determined does not reflect individual pitcher performance, and therefore is an improper judge of how well someone performed. There are countless examples, most clearly Cliff Lee last season and James Shields and Chris Sale this season. Last week, we took on some of the best seasons ever by pitchers who won 9 or fewer times in a season. So much of what leads to wins is completely out of the pitcher’s control and they shouldn’t be judged based on how many runs their team scored for them. Run support, even if we strip away defense, the opposing pitcher, and dumb luck, is a clear and important factor in how many wins you have.

Last week, I gave you this graph which showed that in the 8,000+ qualifying seasons since 1901, wins did very little to explain overall performance:


But those numbers just reflect single seasons. I started wondering about bigger samples. Pitchers can get really lucky or unlucky in a given start and clearly they can in given seasons, but what about in their careers? Can you fake your way through an entire career of wins? It turns out that you can. Let’s take a look.

Below is a graph of Wins per Start (so as to control for guys who made 400 starts and guys who make 250 starts) and ERA- (which is simply ERA scaled to league average during that era and adjusted for park effects. Lower ERA- is better and 100 is league average, meaing ERA- of 90 is 10% better than average). What you see here is that wins fare no better in career samples than season ones (sample size of 2,155):


The trend line is clear in that the lower your ERA-, the more frequently you win, but there is significant variation at each point. For example, at a wins per start of 40%, some pitchers have ERA- of 80 and some have ERA- of 120. The adjusted R squared here is .3966, which means that only 40% of the variation in ERA- can be explained by Wins per Start. That’s less than half.

If we used FIP-, which is the scaled version of Fielding Independent Pitching (FIP), the results are even more troubling for wins.


The adjusted R squared here is only .2131, meaning that only about 21% of the variation in FIP- can be explained by Wins per Start. You can win 50% of your starts as the best pitcher of all time or as one of the worst.

The takeaway here is very simple and very important. Your ability as a pitcher to keep the other team from scoring (as seen with ERA-) and your ability to prevent runs based on only that which you can control (FIP-) are not that heavily correlated with winning. You can’t use a pitcher’s wins to predict how good they are because you can win if you prevent runs like a superstar or if you prevent runs like a Triple A long reliever. Even if you strip out defense and the quality of the other offense and give the pitcher credit for every single run he allows, there is still the issue of team run support that he has zero control over.

Last week I provided simple, straightforward evidence for why wins don’t reflect performance over the course of the season, but here I’ve shown that wins don’t even tell you much over the course of an entire career. It’s the job of a starting pitcher to limit the runs they allow, but the ability to limit runs doesn’t correlate very well with how often you win because so much of that is out of your hands.

Wins are not a good measure of individual performance and we should stop using them as such. This isn’t because sabermetricians don’t understand the point of the game, which is to win, but rather because we understand that “wins” as a stat for pitchers tells us nothing about how much they contributed to helping their team win. Pitchers try to prevent runs. That is only half of the game. They shouldn’t be praised or blamed for what happens on the other side.

The Nine Best Seasons Under 9 Wins

Clip art illustration of a Cartoon Tiger with a Missing Tooth

At New English D we’re among the those who wish to see the pitcher win removed from our baseball consciousness. It doesn’t measure an individual pitcher’s skill, but that’s how people use it. A pitcher’s won-loss record is about his performance, but it’s also about his defense, his run support, the other starting pitcher, and the other team’s offense. Also, luck, but I’m fine with luck.

Our most recent podcast covers the topic at length, but evidence and examples can do more to convince you about the flaws of wins than my rambling ever could. The catalyst for this post comes from something I discovered last night when contributing to Brian Kenny’s noble effort to #KillTheWin:

Matt Harvey (Go Heels!) is better in games he doesn’t win than almost every other pitcher in the league is overall. It’s time we get his back.

The rules are simple, these are The Nine best season by Wins Above Replacement (WAR) for qualifying starting pitchers who won fewer than nine games. In MLB history, there are 8286 qualifying seasons from 1901-2012 with 1187 finishing with fewer than 9 wins. These are the best.

9. Cliff Lee, 2012 Phillies

6-9, 211 IP, 3.16 ERA, 3.13 FIP, 4.9 WAR

8. Ken Johnson, 1962 Colt .45s

7-16, 197 IP, 3.84 ERA, 2.80 FIP, 5.0 WAR

7. Dutch Leonard, 1949 Cubs

7-16, 180 IP, 4.15 ERA, 2.71 FIP, 5.0 WAR

6. Bill Gullickson, 1981 Expos

7-9, 157.1 IP, 2.80 ERA, 2.11 FIP, 5.0 WAR

5. Al Benton, 1942 Tigers

7-13, 226.2 IP, 2.90 ERA, 3.07 FIP, 5.0 WAR

4. Steve Rogers, 1976 Expos

7-17, 230 IP, 3.25 ERA, 2.85 FIP, 5.1 WAR

3. Bob Welch, 1986 Dodgers 

7-13, 235.2 IP, 3.28 ERA, 2.78 FIP, 5.3 WAR

2. Curt Schilling, 2003 Diamondbacks

8-9, 168 IP, 2.95 ERA, 2.66 FIP, 5.7 WAR

1. Nolan Ryan, 1987 Astros

8-16, 211.2 IP, 2.76 ERA, 2.47 FIP, 6.6 WAR

Wins generally correlate with good performance, but there are many cases in which good performances don’t result in wins and bad performances do. Pitchers can improve their likelihood of victory by pitching well, but they can’t guarantee it. Wins aren’t a completely useless measure of pitcher performance, but when we have so many statistics that are dramatically better, why should be place any importance on wins?

Here’s some evidence writ large. If we use Wins to predict three other statistics, WAR, ERA, and FIP, it doesn’t look good for wins.

Adjusted R Squared 0.38 0.24 0.13

What these numbers tell us is that 38, 24, and 13% of the variation in these numbers can be explained by variation in wins. Let’s give Wins the benefit of the doubt and pick WAR for the graph. There is a clear trend, but there is a lot of variation in WAR that wins can’t explain. The sample size here is over 8,000. You can be both terrible and amazing and achieve the same number of wins.


It’s time to #KillTheWin.

The Morning Edition (June 24, 2013)

Clip art illustration of a Cartoon Tiger with a Missing Tooth


From Last Night:

  • The Pirates get 3 in the 9th to tie, 4 in the 10th to take the lead and almost give it back as they outlast the Angels
  • Morales walks off on the A’s in 10
  • The Mets get 8 as Harvey goes 6 scoreless
  • Cashner is brilliant, but Street blows it in the 9th
  • Latos K’s 13 Dbacks and the Reds survive a rough inning from Chapman
  • Toronto slugs their way to 11 straight wins

What I’m Watching Today:

  • Cliff Lee visits Petco (10p Eastern)
  • Bumgarner faces Ryu (10p Eastern)

The Big Question:

  • How can MLB only schedule four games for today?

Clayton Kershaw has thrown 113.1 IP, 8.8 K/9, 2.5 BB/9, 2.06 ERA, 2.16 FIP, and 2.9 WAR.

Mat Latos has thrown 103.1 IP, 8.7 K/9, 2.44 BB/9, 3.05 ERA, 3.02 FIP, and 2.3 WAR.

They aren’t dramatically different, but Kershaw is pretty much better across the board. Kershaw is 5-5 and Latos is 7-1. It’s time to stop caring about pitcher won loss record, it simply isn’t an indicator of individual pitcher performance.

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