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Master Melvin

April 13, 2019

Master Melvin

A few thoughts about finding the appropriate value for Mel Ott


            1) The cornerstone of sabermetrics, the first observation upon which all the rest relies, is that the purpose of the game is to win, and that therefore each player’s value *is* the number of games that he has won for his team. 

            2)  WAR assumes that value is not in the number of games won for the team, but in the number of games won for the team above the number that could have been won by an easily available alternate had the player not been there.   That’s OK; I’m not arguing with that.  I would point out that the calculation of WAR can never be MORE accurate than the calculation of wins, since it relies upon a prior calculation of wins, and must always be less accurate, because it relies upon (and always will rely upon) substituting arbitrary values for unknowns.  

            3)  There is an additional caveat with the cornerstone observation, which is that some wins are more valuable than other wins.  If two teams meet late in the season and one of them goes into the game tied for first and the other is 40 games out of first and long since eliminated, then the game is more important to one team than it is to the other, and thus a win by one team has more value than a win by the other team. 

            From a logical standpoint, point (3) is as important as point (2); however, as there is a more-or-less agreed-upon protocol for handling point (2), but no agreement as to how to handle point (3), we thus make adjustments for point (2) while ignoring point (3).  Relevant to this discussion, however, is neither point (2) nor point (3), but point (1); I merely wanted to acknowledge that point (1) is not an absolute truth. 


            4) Point (1) is that Wins are the foundation of analysis.   Point (4) is that runs are NOT the foundation of analysis.   Runs are the pathway toward wins.  

            5)  WINS are not park-dependent.  The park does not win games.  In each park in each game, excepting ties, there is one win and one loss.  In a balanced schedule, each team plays (essentially) the same number of home and road games.  We don’t park-adjust WINS; we park-adjust RUNS. 

            If you park-adjust WINS, you wind up adjusting wins out of existence.  You can’t do that.  Wins are the be-all and end-all of analysis.   You can’t accidentally adjust wins out of existence in the course of your analysis. 

            6)  The Polo Grounds, where Ott played his home games his entire career, was a home-run hitter’s park.  Ott hit 511 home runs in his career—323 in his home park, 188 on the road.  I think it is the most pronounced home/road home run split of any player in history with a large number of home runs.

            7)  Because it was a HOME RUN park, people assume that it was a HITTER’S park.  I myself believed that to be true, early in my career, before we developed the robust information sources that we have now.  But it actually wasn’t a hitter’s park, at all; it was actually a pitcher’s park.   This chart gives the park Home Run Factors and park Run Factors for the years 1926 to 1947, when Ott was there.  As most of you know, a factor of 100 means that the park was average in this respect.  200 means that twice as many home runs per game were hit in that park as in the team’s road games.



Home Runs



























































































            If we overlay that data with Ott’s Plate Appearances for each season, we can calculate his career park effects.  The Home Run effect of the park, relevant to Ott and weighted by his plate appearances per year, is 216 for home runs, but 97 for runs.  

            8)  Two conclusions from that:  a) Ott’s home run totals for his career were LESS effected by the park than his team overall, and b) the runs that Ott created were, on average over his career, MORE valuable than if they had been created in a neutral park. 

            9)  A modern reader will not understand how it is possible for a park to have a home run factor of 275, but a park run factor of 89.   What people may not get is that at time (a) home runs were less common as an element of offense than they are now, and (b) in some parks there were almost no home runs at all, but many runs still scored.   In 1931 Cincinnati hit only six home runs all year in their home park, and Boston only 16.  No team other than New York hit more than 51 home runs in their home park. 

            10)  What is relevant to the question of Mel Ott’s value is not what he would have done or might have done in some other park or at some other time, but what he DID do in the time and place where he played.  

11)  We establish that value—his offensive value--by the ratio of his runs created to the wins of the team, using either actual wins—which I prefer—or expected wins, which is used by (I believe) both of the WAR methods. 

12)  When we do those things, Ott has 528 Win Shares, 107.8 WAR by baseball reference, 110.5 WAR by Fangraphs.  Jimmie Foxx has 435 Win Shares, 96.6 WAR by Baseball Reference, 101.8 WAR by Fangraphs.    These numbers are not inflated in any way, shape or form by park effects; rather, they adjust for park effects, thus removing the advantage that Foxx had from playing in a better hitter’s park. 

Allowing that there may still be other considerations such a peak value impact, defense and pennant race impact, Ott appears to be more valuable than Jimmie Foxx.

            13)  I’m in the middle of a long study comparing player’s performance in MVP voting to their "actual" value.   While I am not finished with the study, and Ott is not the MOST undervalued player I have found so far, he under-performed in MVP voting to a really remarkable degree, I think for two reasons:  (a) that he walked a lot, which was not appropriately valued by sportswriters in that era, and (b) that people misjudged the park effects then as they do now. 

            14)  Regarding point (3) above, I can suggest two options.  First, one could adjust each plate appearance by its "pennant impact"; in other words, figure what the team’s chances of winning the pennant are before the plate appearance and after the plate appearance, and sum up the pennant impact of each plate appearance. 

            There are, however, three HUGE problems with that approach.  First, in order to estimate the pennant chances before and after every plate appearance, you have to make dozens of assumptions about what other teams are going to do, and other issues.  Do that for 600 plate appearances, and you have hundreds of thousands of little unstated assumptions which are buried inside your calculation.  If those little unstated assumptions are wrong by just a tiny bit, the end product can be wrong by a lot.

            The second problem if you figure the increases and decreases in the chance of winning the pennant (or a game) is that it is a zero-sum calculation, in which the average player is at zero.   The average player does not have a value of zero.  The average player has a value which we could represent as the number of games he has won for his team, or as the number he has won above replacement level, but you can’t represent it as zero.  Thus, after figuring the pennant gains and losses, you have to twist the data somehow to adjust for that, which introduces another potential source of error.

            The third problem is that a single hit or a few hits can have an immense impact on a team’s chance of winning the pennant.   If you value the players on the 1978 Yankees based on each play’s impact on the team’s chance of winning the pennant, you almost certainly will conclude that Bucky Dent was more valuable to the team than Ron Guidry was.  (Guidry went 25-3 with a 1.74 ERA; Bucky Dent hit .243 with 5 homers, 40 RBI, but hit a three-run homer in the seventh inning of the deciding game.) This conclusion may be valid in a certain narrow sense, but the problem with it is that without Ron Guidry’s season, Bucky Dent would never have been in position to have any impact on the pennant race. 

            Figuring value by pennant race impact disconnects the player’s VALUE from his TALENT to a probably unacceptable extent.  Bucky Dent’s value in 1978 was much greater than the expected outcome of his talent.  That’s actually the issue with making adjustments based on actual team wins, rather than expected team wins.   If a team should win 85 games based on their runs scored and runs allowed but actually wins 95 games, do you evaluate them as an 85-win team or a 95-win team?  I would prefer to evaluate them as a 95-win team, but mine is a minority position.  It’s the same issue with studying pennant impact.

            15)  Because of these problems, incorporating pennant impact in value assessments in that way is probably impossible.   The other alternative is this, or something like this: 

            Suppose that, in addition to the actual games won by the team, we added:

o   Two games if they made Post-Season play,

o   Four games if they won the league championship, and

o   Six games if they won the World Championship. 

If you do that, then you give 2-3% advantage in value to a player on a team that wins 88 games and does win their division, as compared to a team that wins 88 games and does not win their division.

I don’t know that that’s unreasonable; I’m not saying it should be done, but I don’t know that it would be unreasonable.   In essence, the old MVP voters, before modern analysis, gave about a 10% advantage to a player on the league championship team.   That’s too much.  If you give that much of an advantage based on the team winning the pennant, that undermines the rest of the value analysis.   It almost guarantees that a player on the first-place team will win the MVP Award, unless it is an unusual year.   It makes a .270 hitter with 15 homers look like a better player than a .270 hitter with 15 homers on a second-place team. 

16)  It is a principle of modern analysis that a player should be evaluated on the basis of what HE has done, not on the basis of what his teammates have done.   That is a completely valid principle, of course.

But it’s not the only valid principle. 

If you say that the point of the competition is to win the pennant, therefore winning the pennant has to be factored into each player’s value, I don’t have a problem with that.   If you say that an 88-win season in which you win the World Series has to be evaluated differently than an 88-win season in which you finish fourth, I don’t have a problem with that.   I think that valid analysis can be done either way, as long as you don’t push it so hard that the "special value" of winning the pennant obliterates the "ordinary value" of playing well and helping your team to win games.









I will open this up to comments by BJOL subscribers tomorrow or Monday. 


COMMENTS (17 Comments, most recent shown first)

In 8), the word is “affected,” not “effected.” Maybe so many uses of the word “effect” got you, or maybe you were making a point.
4:08 PM Jun 16th
Until you see the actual pictures of the ballparks with dimensions its hard to imagine the park effects. It greatly helps to do this to conceptualize what happened is certain places.
9:46 AM Apr 24th
Excellent debunking job here by Bill -- and also unmasking the true nature of a very important, consequential ballpark in ML history, the Polo Grounds.

Years ago, Bill had pointed out another park effect of Coogan's Bluff -- why first basemen (e.g. Marv Throneberry in 1962) played what seemed to be way out of position in this park. Something you never would have realized -- until Bill noticed, explored and explained. Thanks.
6:59 AM Apr 18th
Don't want to sound nitpicky, but 1929-37 is nine years, and the Giants won the pennant three times in that span (1933, '36 and '37). That's not "very rarely" in anyone's sense of the term.
3:20 PM Apr 16th
My own analysis confirms that Ott was more valuable than Foxx. He had 11 seasons of 4 or more WAA; Foxx had 9. 11 is only one less than Gehrig and it's more than Joe D would have had even if he had topped 4 WAA in 1943-5. Ott was a very great player.

At San Diego I'll be giving a presentation about the Stoneham Giants. in two different eras--1929-37 and 1961-68--they had at least three Hall of Famers on the roster but very rarely won the pennant. In the first era these were Ott, Terry, and Hubbell; in the second, Mays, McCovey, Marichal, Cepeda. Neither the Cardinals in the first era nor the Dodgers in the second had comparable top-line talent but did much better. I'll explain how.

Regarding park effects: if you hit many more home runs than an average player would have in your home park, you are very great. Period. The issue of how much the park helped you (and anyone else) is irrelevant.

David K
8:27 AM Apr 16th
I appreciate your research; thanks.
12:48 AM Apr 16th
Oh and related to the article, career championship WPA totals are:

Mel Ott 1.698 (

Jimmie Foxx 1.337 ( 1.337)

The biggest play of Ott's career was a solo home run off Jack Russell in game 5 of the 1933 World Series in the top of the 10th, 2 out, bases empty and the game tied 3-3. Worth .085 championships

For Foxx it was a 2-run HR off Burleigh Grimes in game 5 of the 1930 World Series. Top of the 9th, 1 out, runner on 3rd, 0-0 tie. Worth .221 championships.

11:39 PM Apr 15th
The Baseball Gauge shows "Championship Win Probability Added", which calculates how much each play increased the odds of winning the World Series. It's the same calculation as win probability added but he also factors in the chance of winning the World Series (explained here: Last year's leaders were:

.239 Yasiel Puig
.229 Steve Pearce
.164 Josh Hader
.141 Walker Buehler
.139 Pedro Baez

Full list here:

Puig tops the chart because he had the biggest play of the year -- a 3-run home run in game 7 of the NLCS, top of the 6th, 2 outs, runners on 1st and 2nd, ahead by a run. That home run increased LA's chance of winning the world series by .127 (ie 12.7%). If they lost the game they would have 0% chance of winning the WS, if they won the odds would be 50%. Baseball Reference shows the home run increased LA's chance of winning the game from 67% to 91%. Since they would have a 50% chance of winning the series if they won the game, the odds of winning the series went from 67% x 50% = 33.5% to 91% x 50% = 45.5%. The difference of 45.5 - 33.5 = 12.0%, which is in line with Baseball Gauge's 12.7% (which uses slightly different win probabilities than Baseball Reference).

The full list of top plays is here:

If you change "Game Type" to "Regular Season", then the biggest play was DJ LeMahieu's 2-run HR in the bottom of the 9th on September 12 to give Colorado a 5-4 win over Arizona.

The 1978 cWPA leaders are:

.256 Rich Gossage
.244 Thurman Munson
.243 Ron Guidry
.236 Bucky Dent
.235 Davey Lopes

Bucky Dent's home run scores at .113, fifth-best that season ( The reason it isn't higher is that championship series plays are only half as valuable as World Series plays, and the most important regular season plays are only half as valuable as championship series plays. In the World Series, the odds of winning the World Series can swing from 0 to 100%. But in the championship series, the odds of winning the World Series can only swing from 0 to 50% (because if you win the ALCS, you still only have a 50% chance of winning the World Series). In the round before the championship series, the odds of winning the World Series can only swing from 0 to 25%, and so forth.
2:14 PM Apr 15th
Another entertaining article that makes the reader think abut baseball analysis. I agree that wins are the key stat, not projected wins. And that to better estimate player value we have to include the information whether the player being analyzed also contributed to a team that made the playoffs or won the pennant or won the World Series. That is why I like #15. This inclusion of data also helps to capture the team 'mesh' that allows the team to win the pennant. This includes such intangibles as leadership, inter-player relationships, 'clutch' performance, etc. There has to be acknowledgement that the player's performance helped lead the team to the team's ultimate goal of that season. And adding #15 data does lead to the conclusion that two players with the exact same statistics (park adjusted), and one player's team won the pennant and the other player's didn't, the player on the team that won the pennant has to be given credit for a better season.

#15 might even be smoothed a little by some small addition that a player gets a little extra for his team having 100 wins, 95 wins, etc. But still have the addition for pennant win higher than games won addition. This would smooth the step-function of playoffs/no playoffs and help in recognizing that winning that 95th game late in the season is more important than winning that 80 game late in the season (assuming that neither team made playoffs).
1:04 PM Apr 15th
Brock Hanke
I've been poking around home/road homer splits for a while now, and I have found no larger a split in the Modern Homer Era (1920+) than Mell Ott's. Chuck Klein, a product of the Baker Bowl, has a split of 1.70 to 1. Ott has 1.72 to 1.

However, if you consider the Dead Ball Era, 1901-1919, you get a couple of MUCH stronger splits, due to the Baker Bowl. The largest home/road homer split that I know of in baseball since 1901 is Gavy Cravath, who played his entire career in the Baker Bowl and has a split of 3.85 to 1, which makes Ott look like amateur hour. To get an idea of how large Cravath's split is, the SECOND-largest split I have found is Fred Luderus, the first baseman on Cravath's teams. Luderus' split is exactly 3 to 1. Luderus and Cravath are basically exact contemporaries. They both retired after 1919, and one of them, I think Cravath, began his career only one year earlier. The two players could hardly be more different. Luderus was a lefty fly-ball hitter, who would probably hit 40+ homers a year nowadays. Cravath was a RIGHTY bat, and the Baker Bowl's effect was due to a very small right field.

In Bill's Sherry Magee comment in the New Historical, he quotes Cravath as advising fellow Phillie Magee to grip down on the bat as hard as he could, because that would give Magee more power (this is a direct quote), "in any park." This is nonsense, although it puts paid to the idea that Cravath adapted himself to his park or something. I went out and tried that swing. What happens is you cannot roll your wrists, and so you get an opposite-field slash with a strong uppercut. This produces endless opposite-field cans of corn. In normal ballparks, those get caught by outfielders. In the Baker Bowl, they sometimes went over the RF fence. Cravath led the National League in homers for several years, including two in which he hit NO road homers at all.
7:56 AM Apr 15th
I've never figured out if a player with a big home/road differential should be admired or denigrated. If a guy hits 10 home runs on the road and 30 at home, you could say he isn't really that good a hitter - he's just helped by his home park. Or you could say he's a great hitter, able to put up big numbers by taking advantage of his home park.

12:58 AM Apr 15th
I mean, of course, ranking Ott as a better player than Foxx. I would have thought that Foxx, a first baseman, loses more positional adjustment points (on Baseball Reference) than Ott, a left fielder, but Ott actually loses more that way than Jimmie.
10:50 PM Apr 14th
What is strange is that Mel Ott has a higher lifetime WAR (107.8) than Jimmie Foxx (95.8). No one, looking at their statistics would regard Ott as a better player than Foxx, except maybe in defense. Foxx: .325/.428/.609; Ott: .304/.414/.533. Foxx of course hit 58 home runs one year, but also hit 50, 48, 44, 41, and 30 or more seven other times. Ott, playing in a good home run park, hit 42 tops, and also seven seasons of 30+ home runs. Playing at the same time and in the same league as Ruth, Gehrig, DiMaggio, Greenberg, Simmons, Gehringer, Grove, and Feller etc. Foxx won three MVP awards- Ott won none, of course, although the NL had fewer great players and he was playing for a good team in New York City. I suppose it comes down to Foxx bing basically finished at the age of only 32 in 1942, while Ott was good until 1945, when he was 36. But I can't see anyone ranking Ott as a better player than Ott.
6:04 PM Apr 14th
This is not perfectly on-point, but Ott, not Mays or Bonds, has the Giants franchise record for RBIs, with 1860. And, Ott and Foxx--both came up as 17-year-olds, but Ott had more staying power than Foxx.
4:23 PM Apr 14th
#2 - just measuring total contributions to wins instead of wins above replacement level performance does not make sense to me. I wish I could articulate better why that is wrong. I would say it seems self-evident . . . but we don’t dare say things like that here. Let me circle back to this.

I agree with Bill’s earlier writings that even if we can improve our measures of WAR, it still wouldn’t be great. There is still more value in a very high WAR for a couple seasons than an equal amount of WAR spread out over many seasons. That is a problem that would be exacerbated by measuring wins instead of WAR. There are levels of replacement. When a pitcher in your rotation is injured, he isn’t always replaced by a replacement level pitcher, he is replaced by someone slightly better than that - the top long reliever, for example, and a replacement level pitcher is called up to replace the relief pitcher.

We haven’t yet come up with a way to better measure a player’s value given that fundamental flaw. However, roster make-up these days is now so specialized that every player is now generally replaced by a minor leaguer - a replacement level performer specifically groomed for that specific role. Thus, I think WAR is a more accurate measure of a modern player’s value than simply wins created (as concept - of course, it depends on how well one is measuring WAR and wins).

#3/14 - Another problem with measuring impact on pennant races is that pennants are not the only thing. When a fan watches their team play, they enjoy the experience more when their team wins. More wins the better. Winning more games than one loses is an avoidance of shame. Winning enough games to be in a pennant chase has real value to a fan, even if that team fails to get to the play-offs. Each win in the play-offs has its own added value.

For that matter, losing a close game is way more fun than losing a blow out. Perhaps, creating and preventing runs are just as important as wins and losses and championships.

Some people are goal oriented, some focus more on the process. The extreme of one type of person might only value championships while the extreme opposite enjoys each individual action.

#15 & 16 - completely agree.

I was working on a project that overwhelmed me where I was trying to find which teams had a legitimate claim to be the greatest ever up to that point in time. I added value to the team’s accomplishments almost exactly as you suggest. For example, could you say the 1906 116-36 Chicago Cubs were not the greatest team up to that point in history just because they lost the World Series in 6 games?
12:29 PM Apr 14th
Speaking of a guy who was a SABR favorite, Ott did at least one other thing that was ahead of its time.

It's that "stepping into the bucket" bat swing. During the 1970s, my dad said his hitting method was frowned upon even 40 years after Ott played. I guess baseball shrugged it off as "Ott's the only guy who can do it." I don't remember any players from the 1970s swinging that way, at least in the National League.

Nowadays, it's not that unusual. Weird batting stances started taking hold in the 1980s, and nowadays it's a "if it works, don't fix it" attitude on batting styles instead of rigid orthodoxy.
11:20 AM Apr 14th
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