No matter what method will be chosen, we will end up with problems. I personally would not choose R+RBI as they are heavily influenced by their teammates. Using LWTS or RC also have problems because they are dependent on the league context, and the impact of a single in 1993 mght not necessarily be the same as in 1903. The pool of players selected also has an influence.

As Robert said though, by looking at the changes over a SMALL set period of time, we might be able to learn something GENERALLY, without getting too specific.

I'm reposting to reactivate this thread. Tom H asked about a thread to discuss the quality of league play, so here it is!

I've had some thoughts on league quality. I figure we need to look at several tools, not just one ultimate tool. As such, I propose the following tools:

* Five year floating comparisons. A player's performance can be compared with what he did up to five years before or after that year. This is the Cramer study, with a partial buffer against the effects of aging.

* Pitchers hitting, relative to the league. After 1975, this becomes less useful because pitchers bat less often in the minors due to the DH rule.

* Fielding percentage, adjusted for strikeouts (PO-SO)/(PO-SO+E). Less useful early in history since players did not start using gloves at the same time.

Are there numbers for the NA? It's probably useless to speculate, but with a little extrapolation it kind of looks like the NA may have been about equal to the early and late AA?

On the other hand, that is not a fair comparison. The NA represented the best baseball, the state of the art, at the time. The AA did not. So I think it is two different things to discount Ross Barnes or Al Spalding versus discounting Stovey, Browning, Caruthers and Mullane. At their best Stovey, Browning, Caruthers and Mullane may never have been as good as their more or less exact contemporaries Brouthers, Connor, Ewing, Glasscock and Clarkson. But at their peak, there was nobody, no rough contemporaries anywhere near as good as Spalding, Barnes and Wright. To me, those are two quite different things that just happen to be described by the same concept--that is, "-.020."

Actually, that study was done by Dick Cramer. It is an interesting study, but it has a fatal flaw -- it makes changes for player aging. The steady upcreep of player skill is probably real but nowhere near as great the Cramer study says it is. The other study outcomes probably are valid.

Tom wrote:

>I would subjectively put the league quality at a level so that the early stars (Barnes-Spalding-Wright) come out as no-better-than-even in terms of peak value with Brouthers-Glasscock-Nichols....

That seems sensible. And in fact they would be more or less equal in terms of peak value, and then the short careers of the early stars would have to be factored in. So, no, none of the stars of the NA is probably the very best of the 19th century at his position, but in terms of peak value (in terms of their contributions toward winning pennants) they were "in the ballpark."

I don't think the quality of the best players has advanced much over time, if at all. The quality of the tofu, marginal regulars, however, is where the increase has occurred.

It is interesting to note from the Cramer study that the rates of increase levelled off some in both 1920 and 1960, so we can assume the increase in quality of play has slowed. I do not think the baseball of today is all that much better than the baseball of 1960 -- were you to have an average team from 1960 play an average team from 2000 for 1000 games, my guess is the 2000 team would win 504 games on average, or something like that.

As to the quality of the early NA, given the incredible disparity among teams (a 71-8 record?!?) and individual player stats, I would subjectively put the league quality at a level so that the early stars (Barnes-Spalding-Wright) come out as no-better-than-even in terms of peak value with Brouthers-Glasscock-Nichols, and not fear to tread any further.

As I've pointed out on the Pitchers thread, there should be little difference in quality between the NA of 1875 (when Boston went 71-8) and the NL of 1876. I'll let those with better numbers track the evolving quality of the earlier NA years and the succeeding ones of the NL. (scruff has published indications that he believes the NA of 1875 may have been tougher.)

However Harry Wright did it, there is no question that he determined who the best players of that era were and get most of them onto his team. He managed to keep them together and winning with apparently few ego problems (at least none that I've read about). This was good for them, but ultimately, this was bad for the NA (we think that there is no hope of competing against the Yankees now; they are nowhere near this dominant). A priori, they are the NA All-Star team; it will be interesting to see if anyone else can crack that lineup.

Tom, I don't know that hitters batting avg relative to the league is a good stat to use. Batting avg is affected by many things.

I'd try to come up with something a little more comprehensive, like XR or RC or something. But then you run into problems with the formulas, etc.

This is what I'd do, if I had the time. Figure runs created for each player on each team, normalize the totals of the individuals to the team total runs, so they come out the same, i.e. the total for Chicago individuals in 1876 equals the actual number of runs the 1876 Cubs scored.

I know some people are opposed to this in theory, but the accuracy of RC and XR is questionable for that time period, and I think the adjustment is necessary, for the stabilizing effect.

Once you have the RC, figure RC per 27 outs (don't use 27, use the league average per game of batting outs recorded, will make a big difference back then, because of all the errors).

Finally, adjust that for the league. Now you've got a number you make meaningful comparisons with.

Alternatively, if you have the WS book (and the digital update from Stats), you can figure out WS per 162 team games or something like that (adjusting for the player's relative playing time), and use that as your comparison number. That would be a helluva lot easier, and the number is meaningful. But I don't think batting average is a good number to use. Just because fielding gets better (moving batting averages down), doesn't mean the quality of league play goes up. Take a league of Ozzie Smith's everywhere, even out in LF. Add Barry Bonds and Rickey Henderson and Jeff Bagwell to the mix (removing two Ozzie LF's and an Ozzie 1B), and the league fielding will get worse, but you're going to have a higher quality league. WS is the kind of number that is perfect for a study like this, even though it is seriously flawed with the pitcher/fielder split on defense for this era.

If you use WS, you can include pitchers as well, or do two separate studies.

Just my .02 . . .

Tom, your points are all well taken. All three of them. :-)

moving to hot topics.

Joe rules!

Transferred from 1932 Ballot Discussion
David Foss:
It's possible that the AL stars may not have affected the "base-level" of play for the league. Is there any evidence that would support that the AL also had more weak players and weak teams... not enough to reverse the discount, but enough to balance things?

Michael Schell (Biostatistics, UNC) believes that "standard deviation measures league talent" inversely. He uses a version of league SD as a measure, which is not an argument, but it is clear that he believes it. [Baseball's All-Time Best Hitters, Princeton U P, 1999, chapter 4.]

For example, "Many of Cobb's American League compatriots would likely have ridden the National League bench during the same era."

That era is 1910-1914, when SD batting average was AL .043, NL .030. In the AL, 4% batted above .350 and 12% below .220 (mean-adjusted). In the contemporary NL and in both leagues 1980-1984, the shares were 0% and 6%. By those measures, the number of extra "low outliers" in AL1910-1914 was greater than the number of extra "high outliers".[*]

Schell's argument implies that the AL was weaker than the NL, 1910-1930; stronger, 1901 and 1960-1975. That isn't plausible.

[*]
jimd suggested that standard deviation is low in NL1910-1914 (s.d. mean-adjusted batting average) because the NL lacked outliers such as Cobb, Jackson, Speaker, Collins, Lajoie on the high side.
http://www.baseballthinkfactory.org/files/primer/hom_discussion/1932_ballot_discussion/P200/#9

Shibe Park 1938-1954 was home to the NL Philies and AL Athletics. For that period, Michael Schell found normalized ballpark batting average .253 in the NL ("a slightly underaverage hitting park") and .256 in the AL --where .255 is the norm.

Such calculations do not measure league quality, but they have a place in interleague comparisons.

Paul, have comparable studies been done for the other shared parks of this era? Polo Grounds 1913-1922; Sportsman's Park 1921?-1952. Informal studies I've done of their park factors during the teens and twenties show that the AL was the "pitchers league" while the NL was the "hitters league"; both of those parks would play as better for hitters in the AL.

This is largely irrelevant to those who use OPS+/ERA+, Win Shares or WARP to evaluate players.

Along the same lines as jimd's post, the NL took steps to decrease offense following the rabbit ball 1930 season while the AL did not. Scoring levels in the NL were lower than the AL between 1931 and WWII... often by as much as a full run per game.

Again this is irrevelent for those who use statistics that are scaled like OPS+/ERA+, etc.

This has been mentioned before, but this thread looks like a good place to restate this.

park factors during the teens and twenties show that the AL was the "pitchers league" while the NL was the "hitters league"; both of those parks would play as better for hitters in the AL.

Schell's estimates for Shibe Park suggest the same for 1938-1954. Shibe was a better batting park in the AL because the other AL parks were not so good for batting as the other NL parks.

It should be easy to study the matter by using a consistent series of park factors as a resource, eg the Total Baseball park factors.

Schell's estimates for Shibe Park suggest the same for 1938-1954. Shibe was a better batting park in the AL because the other AL parks were not so good for batting as the other NL parks.

Isn't this also true for Sportsman Park?

Polo Grounds 1913-1922; Sportsman's Park 1921?-1952. Informal studies I've done of their park factors during the teens and twenties show that the AL was the "pitchers league" while the NL was the "hitters league"; both of those parks would play as better for hitters in the AL.

Isn't this also true for Sportsman Park?

Yep. See above.

Yep. See above.

Sorry, Jim. I missed that post.

I doubt error rates as a basis for judging quality in competing leagues. That is how participants probably viewed errors, so liberal scoring may have been a means of competition.

(By eye and mind) Error rates seem to show that NL fielding was significantly better than AL and FL in 1914; that NL and FL fielding improved significantly in 1915.

BTW, the FL signed many more NL regulars than AL.

That's enough for me, since someone else probably has an electronic database with the relevant data for every league-season. (IP, SO and E, I think)

jimd supposes or estimates that Babe Ruth is 16+ wins above replacement; call it 49 win shares.

OK, if I understand correctly:
Suppose that a replacement-level full-time player is worth 6.5 win shares (thus 78 WS or 26 wins for a team of replacement-level players). 6.5 is someone's estimate.

Ruth joins one of 16 teams, which increases the MLB average talent by 3 WS per team on the old scale, or 0.25 per full-time player-position (8 regulars, 4 pitchers). Because the number of wins is fixed, that decreases measured talent by 0.25 per full-time player-position for all slots but his own. Because he joins one team in one league, his impact on the talent scale is 0 in the other league and -0.5 per full-time player-position in his own league. After his entry, the measured talent of replacement-level players is 6.5 WS in the other league, 6.0 in his own league.

Right?

Paul, my original argument was made using WARP. It looks like you've constructed the Win Shares version of it here. Adding Ruth to the league cost every regular about 0.5 Win Share per year; having a 7-2 imbalance of super-stars (Johnson, Cobb, Speaker, Collins, Jackson, Baker, Ruth vs Alexander, Hornsby) could cost each regular in the stronger league about 2.5 Win Shares per year or 40 Win Shares over the course of a 17 year career.

For Wheat vs Hooper, they start at 385-330 (all seasons adjusted to 154 G), and this narrows the gap to 385-370 (or 345-330). I don't see them as being that different. Maybe the line between being barely in and being barely out passes between them, but not the line between being first ballot and having no chance at all.

having a 7-2 imbalance of super-stars (Johnson, Cobb, Speaker, Collins, Jackson, Baker, Ruth vs Alexander, Hornsby) could cost each regular in the stronger league about 2.5 Win Shares per year or 40 Win Shares over the course of a 17 year career.

jimd, I know these are back-of-the-envelope estimates, but looking at the careers of these players, I don't think the imbalance was typically 7-2, or that each superstar had the effect of Ruth at the top of his game. If my modeling of great-player effects is correct, pitchers pull more WS from other pitchers than from position players, and vice versa. So let's have Johnson and Alexander cancel each other out, and look at the hitters.

Superstar years
Cobb, 07-19
Speaker, 09-23
Collins, 09-20
Jackson, 11-13, 16-17, 19-20
Baker, 11-14
Ruth, 16-32

Hornsby 17, 20-29

Prior to 1911, there's another set of superstars to deal with, so let's start in 1911.

1911-13 5-0, AL
1914 4-0 AL
1915 3-0 AL
1916 5-0 AL
1917 5-1 AL
1918 4-0 AL
1919 5-0 AL
1920 4-1 AL
1921 2-1 AL

After 1920 we also would need to look at a different set of players in both leagues. On average, from 1911-1920 there's a 4.3 AL advantage in superstars. If we estimate that these superstars average 40 ws/season as a group (which is generous), each one drops a regular in his own league about .33 ws. 4.3 superstars together is 1.4 ws/year during this period. Assuming the average superstar advantage for the AL remains constant throughout the Wheat/Hooper period (I doubt it would be wider), that would mean more like a 25 win-share cost to Hooper for better competition during his career, leading to a 385-355 edge for Wheat.

Maybe the line between being barely in and being barely out passes between them, but not the line between being first ballot and having no chance at all.

I see the gap as a bit wider than that, but remember 1933 was an odd ballot. It's not clear that players who finished 4th and 5th in that election, Jake Beckley and George Van Haltren, will manage election in, say, the next 20 years, so the barely in/barely out line was very close to the top of this ballot. The electorate saw Wheat as above the Beckley/Van Haltren line, Hooper as below it.

If the case for Hooper is to be made successfully, competition quality arguments need to be advanced to run him past George Van Haltren and Jake Beckley as the top career-value candidates from the backlog. I'm not ready to make that move (at least with respecct to Van Haltren) but I hope the electorate is paying attention to jimd's case on league quality differences; there's absolutely an issue here!

My case was not so much as pro-Hooper (he's not high on my ballot) as urging caution on Wheat. Obviously, it's too late for that now.

I believe that Win Shares overrates OF'ers from this era because of the fixed ratios for allocating Win Shares to positions. It makes no sense to me to see this long-term evolution that converts defensive plays by the infielders into strikeouts and to then assert (as Win Shares does) that infielders were no more important then than they are now even though they were making many more plays per game.

Adding more meat to Chris's bones, the 7 AL superstars mentioned by jimd only played together for 3 years (1916-1918).

Nonetheless, I added up the WARP-1's for the 9 players mentioned in each year, from 1910-1925 (Hooper and Wheat's overlapping careers). The difference between the groups ran from 18.2 WARP-1 advantage in 1925 to an 84.5 WARP-1 advantage in 1912.

Now 84.5 certainly seems like a large gap, but that's what you get when you compare 6 AL stars (all but Ruth) to 1 NL Star (Alexander). Left out of the calculation are that the ACTUAL stars of 1912 were Honus Wagner, Heinie Zimmerman, Chief Meyers, Johnny Evers, and Christie Mathewson, (one could also include Rube Marquard and Larry Doyle here, but I won't). So that's 3 HoMers, plus at least Meyers and Evers, who are out of the HoM due to short careers, not to any challenge of how good they were in their primes.

Compare THOSE 6 to the AL 6, and the AL's WARP-1 advantage in 192 drops to 23.5.

The fact that the NL may have had fewer All-Time Greats does not mean that it had fewer stars in any given year.

It's only a first step to say 7 is more than 2, and assume a difference of 5. If you look year by year, the actual difference in quality between each league's Top X players (for that year) will be relatively small.

Good discussion.

What do we do with Gavvy Cravath? Even with the park adjustments, he's putting up big numbers. We mentally discount him, but does he act like a "superstar" for the purposes of this discussion?

Here are some tables:

1000 PA to make the lists:

<pre>
AMERICAN LEAGUE
CAREER
1911-1920

RUNS CREATED RATE PLAYER LEAGUE
1 Babe Ruth 277 498 180
2 Ty Cobb 248 1299 525
3 Joe Jackson 214 1141 532
4 Tris Speaker 211 1239 588
5 George Sisler 178 587 330
6 Eddie Collins 176 1076 613
7 Sam Crawford 168 641 381
8 Home Run Baker 159 771 486
9 Jack Fournier 149 240 161
10 Birdie Cree 148 301 203
11 Wally Schang 144 414 288
12 Bobby Veach 143 735 512
13 Harry Wolter 141 161 114
14 Braggo Roth 139 441 318
15 Joe Judge 131 362 275
16 Sam Rice 130 308 236
17 Happy Felsch 129 428 331
18 Baby Doll Jacobson 129 272 211
19 Eddie Murphy 128 336 262
20 Harry Heilmann 128 388 304


NATIONAL LEAGUE
CAREER
1911-1920

RUNS CREATED RATE PLAYER LEAGUE
1 Rogers Hornsby 184 485 264
2 Gavvy Cravath 181 723 399
3 Ross Youngs 169 280 165
4 Edd Roush 158 399 252
5 Joe Connolly 154 216 140
6 John Titus 152 194 128
7 Heine Groh 146 653 448
8 Benny Kauff 144 316 219
9 Bill Hinchman 144 223 155
10 Zack Wheat 143 792 552
11 Sherry Magee 142 632 445
12 Johnny Bates 141 238 169
13 George Burns 139 718 516
14 Larry Doyle 138 749 541
15 Honus Wagner 137 506 368
16 Chief Meyers 136 347 255
17 Hal Chase 136 254 187
18 Charlie Hollocher 135 190 141
19 Beals Becker 134 290 217
20 Heinie Zimmerman 133 692 521

Here are some tables:

1000 PA to make the lists:

AMERICAN LEAGUE
CAREER
1911-1920

RUNS CREATED RATE PLAYER LEAGUE 
1 Babe Ruth 277 498 180 
2 Ty Cobb 248 1299 525 
3 Joe Jackson 214 1141 532 
4 Tris Speaker 211 1239 588 
5 George Sisler 178 587 330 
6 Eddie Collins 176 1076 613 
7 Sam Crawford 168 641 381 
8 Home Run Baker 159 771 486 
9 Jack Fournier 149 240 161 
10 Birdie Cree 148 301 203 
11 Wally Schang 144 414 288 
12 Bobby Veach 143 735 512 
13 Harry Wolter 141 161 114 
14 Braggo Roth 139 441 318 
15 Joe Judge 131 362 275 
16 Sam Rice 130 308 236 
17 Happy Felsch 129 428 331 
18 Baby Doll Jacobson 129 272 211 
19 Eddie Murphy 128 336 262 
20 Harry Heilmann 128 388 304 


NATIONAL LEAGUE
CAREER
1911-1920

RUNS CREATED RATE PLAYER LEAGUE 
1 Rogers Hornsby 184 485 264 
2 Gavvy Cravath 181 723 399 
3 Ross Youngs 169 280 165 
4 Edd Roush 158 399 252 
5 Joe Connolly 154 216 140 
6 John Titus 152 194 128 
7 Heine Groh 146 653 448 
8 Benny Kauff 144 316 219 
9 Bill Hinchman 144 223 155 
10 Zack Wheat 143 792 552 
11 Sherry Magee 142 632 445 
12 Johnny Bates 141 238 169 
13 George Burns 139 718 516 
14 Larry Doyle 138 749 541 
15 Honus Wagner 137 506 368 
16 Chief Meyers 136 347 255 
17 Hal Chase 136 254 187 
18 Charlie Hollocher 135 190 141 
19 Beals Becker 134 290 217 
20 Heinie Zimmerman 133 692 521 

Sorry for the double-post... maybe someone can clean that up... still doesn't really line up. ugh... sorry.

The AL does have more superstars, but the NL catches up in the second ten. There are 82 players at 100 RC+ or better in the NL and 65 players at 100 RC+ AL.

Its not clear to me how much of that is due to the averages shifting from the superstars.

Anyways, the proper way to do this is to examine what happens to players who switch leagues. Unfortunately, this was extremely rare in this era.

Leaving the players' names out and just speaking theoretically, if one league has 7 players who are multiple levels above the average player and another league has 2 such players, isn't it more likely that the second league has the better overall quality, not the first? Doesn't the number of outliers normally decrease as the overall quality of any group improves?

[Paul Wendt:]
jimd supposes or estimates that Babe Ruth is 16+ wins above replacement; call it 49 win shares.
. . .
Posted by jimd on September 01, 2004 at 09:05 PM (#832239)
Paul, my original argument was made using WARP. It looks like you've constructed the Win Shares version of it here. Adding Ruth to the league cost every regular about 0.5 Win Share per year

Thanks for the clarification.

Relying on someone's estimate of full season replacement level 6.5 win shares. (JoeD?)

Babe Ruth is 48-49 win shares above replacement only in 1923.
01 37 36 40 43 - 1915-1919
51 53 29 55 45 - 1920-1924
13 45 45 45 32 - 1925-1929
38 38 36 29 20 - 1930-1934 (finale, 2 in 1935)
Best 5-year record (a period much shorter than the career of anyone considered here), 233 win shares; annually 46-47 or 40 above replacement.
Best 10-year record, 419; p.a. 42 or 35-36 above replacement.
Best 15-year record, 608; p.a. 40-41 or 34 above replacement.

I don't know how the impact is distributed to pitchers and others, so that's all for now.

Andrew does have a point.

While on the one hand I completely understand how the addition of a Babe Ruth to one league could depress other players' Win Shares, I could also see how if the top two or three teams in terms of drafting marginal talent or making overlooked "finds" were all in the same league, the effect could be the same or greater.

Cravath has "found" by the NL at 31. So was George Suggs at age 27. I one league's teams are systematically replacing lost talent with higher quality "replacement players", that could be like spreading an All-Star throughout the lineup.

Put another way:

Win totals for last (8th) place teams, 1910-1920:

AL: 47 wins (range, 36 to 57 wins; 4 different teams finished last, but the A's finished last 6 consecutive years )
NL: 55 wins (range, 44 to 69 wins; 6 different teams finished last)

AL players got years of feasting on the 36 win Philly A's in 1916 -- with every other team finishing within one game of .500! (Lots more Win Shares to spread around), meanwhile the NL had enough parity that the Giants finished in last place in 1915 with 69 wins -- two years after and two years before winning the pennant.

Leaving the players' names out and just speaking theoretically, if one league has 7 players who are multiple levels above the average player and another league has 2 such players, isn't it more likely that the second league has the better overall quality, not the first? Doesn't the number of outliers normally decrease as the overall quality of any group improves?

It all depends. If we're comparing 1912 with 2002, I'm on your side Andrew. The fact that so many "all-time greats" are playing at the same time indicates to me that they probably weren't so great because the competition wasn't either.

But if we're comparing AL and NL in 1912, it's a different story. It could be that Cobb, Collins, Speaker, etc., are tearing up a minor league like Browning did in 1882, but there are other factors that indicate it isn't so. The NL All-Star team of 1882 is mostly HOMers, the NL All-Star team of 1912 is not close. The AL of 1912 has been in operation for over a decade; they'd pretty much have to deliberately run their league into the ground to turn it into a minor league quality operation. The AA of 1882 is just getting started and so highly likely to be full of replacement level players.

The hypothesis that the two leagues were basically equal but that the NL had had a bad run of luck at snagging their share of the high-impact superstars is much more plausible than the hypothesis that the NL had been quietly getting the huge majority of the mid-level players leaving the AL with the leftovers and a handful of inflated faux superstars.

Compare THOSE 6 to the AL 6, and the AL's WARP-1 advantage in 192 drops to 23.5.

24 WARP difference for 6 players is an average of 4.0 WARP each. That's pretty significant. Assuming the rest of the leagues are of equal quality, it's enough to say that a 77-77 NL team was equivalent to a 74-80 AL team. (3=24/8) It's enough to consider a 4% discount.

jimd, I know these are back-of-the-envelope estimates,

Agreed. They prove nothing, except that there is a plausibility to Davenport's calculations. A similar superstar imbalance will appear again in the 1950's, and his calculations will show a similar league imbalance, which will again corroborate the public opinion of the time.

A similar superstar imbalance will appear again in the 1950's, and his calculations will show a similar league imbalance, which will again corroborate the public opinion of the time.

Except the fifties imbalance can be corrobotated by year-to-year comparisons player by player, while the Deadball Era can't.

I'm more in the camp of "the AL had more of the stars, but overall was basically the same as the NL" camp for now.

I'm more in the camp of "the AL had more of the stars, but overall was basically the same as the NL" camp for now.

But John, if the AL had more of the stars, then it can't have been basically the same as the NL. The only way that the value of an average player in the two leagues could have been the same, with the AL having more stars, is if the NL had either more good players, or fewer bad players than the AL to offset the effects of the AL's stars.

If the AL and the NL were basically the same except for the superstars in the AL, then the next tier of above average players -- the Harry Hoopers and the Larry Gardners -- of the AL are going to have their totals suppressed relative to players of the same ability in the NL, because of the stiffer competition.

But John, if the AL had more of the stars, then it can't have been basically the same as the NL.

Overall, I think the two leagues were equal. If that hurts the lower tier of AL players, then that's the case until I'm proven wrong.

If the AL and the NL were basically the same except for the superstars in the AL, then the next tier of above average players -- the Harry Hoopers and the Larry Gardners -- of the AL are going to have their totals suppressed relative to players of the same ability in the NL, because of the stiffer competition.

Its possible that the NL had a tighter distribution of talent that the AL, yet still have the same average level of play. This way, the best AL teams would be better than the best NL teams (though the worst NL teams would be better than the worst AL teams).

This would explain why the AL had a larger stdev of talent yet still won the WS every year.

Its possible that the NL had a tighter distribution of talent that the AL, yet still have the same average level of play. This way, the best AL teams would be better than the best NL teams (though the worst NL teams would be better than the worst AL teams).

This would explain why the AL had a larger stdev of talent yet still won the WS every year.

That's exactly what I was trying to say.

Except the fifties imbalance can be corrobotated by year-to-year comparisons player by player, while the Deadball Era can't.

Don't know exactly what you mean by this, but I'll guess. Davenport builds those ratings by year-to-year comparisons player-by-player within each league so that each league-season is rated compared to the adjacent ones. Those ratings use the largest comparison set available, every player, and are much more solid than anything built on a handful of trades in any given season. All of the interleague movement over a hundred years would then calibrate the leagues relative to each other.

Just because it's harder to verify doesn't mean it doesn't exist. I bring up the topics of public opinion, and superstar imbalance, in an effort to find alternative approaches to verifying the disparity. If people have ideas on disproving it, those are welcome too.

Just because it's harder to verify doesn't mean it doesn't exist.

I'll agree with that, Jim.

Don't know exactly what you mean by this, but I'll guess. Davenport builds those ratings by year-to-year comparisons player-by-player within each league so that each league-season is rated compared to the adjacent ones. Those ratings use the largest comparison set available, every player, and are much more solid than anything built on a handful of trades in any given season. All of the interleague movement over a hundred years would then calibrate the leagues relative to each other.

I've pointed this out quite a few times, but the Dick Cramer study have both leagues as roughly equal during the Deadball Era. Either Davenport or Cramer is wrong. Which one it is I haven't a clue.

Yes, but the peripheral evidence favors Davenport. I remember first encoutering the Cramer study description in "Hidden Game of Baseball" nearly 20 years ago and being very surprised at the absence of a difference for this era, which contradicted my impression built up from much other reading about this period.

But both studies run parallel to each other using ostensibly the same comparisons except when the Deadball Era pops up. My question is: is Davenport altering his comparisons for that era so that it matches his perceptions of that period?

All things are possible, but my question would be "Why do that"? I don't remember the methodology described for the Cramer study, other than it uses his own quantitative metric, just like Davenport uses his own. The difference may lie in distortions of either metric. I also don't remember whether Cramer's metric is league-normalized. If it isn't, the difference may lie there, because during this period, the NL collectively is playing in a "hitter's park" relative to the AL collectively playing in a "pitcher's park" (this is revealed by comparing the park effects of the NY teams 1913-1922 and the STL teams 1921?-1952; the same park generally plays as a better hitters park and a better home-run park in the AL than the NL). Then again, this may be irrelevant; I just don't know enough about the Cramer study's details.

Batter Win Average, the metric that Cramer used as the base for his study, is normalized, Jim.

As for distortions with the metrics, they seem to agree for the rest of baseball history, so that's probably not the case (but who knows?)

Is the study available on-line somewhere?

during this period, the NL collectively is playing in a "hitter's park" relative to the AL collectively playing in a "pitcher's park" (this is revealed by comparing the park effects of the NY teams 1913-1922 and the STL teams 1921?-1952; the same park generally plays as a better hitters park and a better home-run park in the AL than the NL). Then again, this may be irrelevant; I just don't know enough about the Cramer study's details.

It may be relevant to demonstrating the existence of differences in levels of competition. If by comparing park factors, it can be convincingly demonstrated that the AL was a "pitcher's league" during this period, does then the following argument hold true?

I calculate estimated win shares for Negro League players by matching their translated batting statistics to major-league contemporaries and then using the batting win shares of the closest matching player (prorated by PA) as the total for the Negro-Leaguer. I have consistently found that the same batting totals will get you more win shares in the National League than in the American League, at least during the teens.

If the American League is demonstrably a pitchers' league by way of park factors, then one would expect to find just the opposite: American league players should get _more_ win shares for the same OPS than National League players would. Is there any explanation for this finding (if what I have observed can be systematically demonstrated) other than that the level of competition, at least for hitters, was higher in the American League than in the National?

Is the study available on-line somewhere?

I Googled, but no luck finding it, Jim.

An isolated example: 1915 (All stats from B-R.com)

The NL hit .248/.304/.331 and scored 3.62 runs/game.
The AL hit .248/.319/.326 and scored 3.96 runs/game.
The Polo Grounds played as an extreme pitcher's park in the NL (94/93).
The Polo Grounds played as an average park in the AL (100/100).

The Polo Grounds being a typical AL park but a pitcher's park in the NL implies that the rest of the AL parks (on average) would also be considered pitcher's parks in the NL.

If this is typical of other seasons in the vicinity, the implication is that the NL cannot hit or has fantastic defense (or the AL cannot pitch or has great hitting, or some mixture thereof).

If the American League is demonstrably a pitchers' league by way of park factors, then one would expect to find just the opposite: American league players should get _more_ win shares for the same OPS than National League players would.

The same batting line will get more Win Shares in 1908 or 1968 than it will in 1930 or 1894. That the same batting line gets more Win Shares in the NL than the AL indicates that the AL was the higher scoring league (see 1915 above for example). That they were the higher scoring league despite playing in parks that depressed scoring overall indicates a dramatically different balance between offense and defense than the NL. How this relates to overall league quality, beats me.

Which do people see overall evidence for? The AL having better hitters or the NL having better pitching/defense?

Which do people see overall evidence for? The AL having better hitters or the NL having better pitching/defense?

Or something else entirely. What about the sizes of the umpires strike zones? Did they use the same balls? Change them as often for the deadball years?

This doesn't pertain to our discussions, yet, but offense levels in the NL dropped quite a bit compared to the AL starting in 1931. This was a response to the record-breaking 1930 season. Offense levels in the AL stayed high until WWII. How did the NL manage to do that independent of the AL?

Is the study available on-line somewhere?

I have the Cramer batting numbers on a spreadsheet; I can post it to the Yahoo! group site a little later.

His averages are normalized and create the appearance of batters getting "worse" when BA & SA spike up, as in ~1911-13 and in the 20s.

This probably wasn't the right way to do it, but on one of the tabs, I tried subtracting out the differences between the real league BA & SA and those of the reference league, the 1976 NL. The picture looks a little different that way; whether it removes illusions or creates different ones, I can't say. My math skills are largely limited to the basic functions. I'm sure one of you smarter guys can do better.

You can probably also figure out how to carry the numbers forward from 1979 to the present.

The Cramer spreadsheet is now uploaded.

Dick Cramer's analysis has been criticized because it include no age data and thus attributes no differences in player performance across league-seasons to age differences.

That certainly matters in the intertemporal comparisons. There may be a systematic bias in the Cramer measure of general improvement (especially around large changes in the number of MLB teams, I think). It mattes to interleague comparisons if there interleague differences in age patterns.

How looks the population of players who change leagues? (That can't be said succinctly in English.) Is the subgroup that moves from AL to NL different from the subgroup that moves from NL to AL? If yes, that implies a bias in interleague comparisons a la Cramer. A significant YES is most likely around a disruptive event. 1891. 1901. 1915? (numerous Federal Leaguers moved from NL to AL, but not vice versa). 1977? (expansion in AL only).

That is my three cents. All I have today.

Dick Cramer's analysis has been criticized because it include no age data and thus attributes no differences in player performance across league-seasons to age differences.

Correct. Cramer admitted that he was wrong about this in the eighties.

That shouldn't matter, however, for inter-league comparisons. As I have pointed out, Cramer agrees with Davenport except for the Deadball Era. If Cramer's lack of age data was the culprit for the difference, I think we would be noticing the same problem throughtout Cramer's study (which we're not).

That shouldn't matter, however, for inter-league comparisons.

It's probably worth investigating. The local validity of the study assumes that league aging patterns are pretty similar through time. I do remember reading that the two greatest youth revolutions (good rookie crops over a period of a few years) occurred during the early 60's and the early 10's. Maybe that's a factor.

Another factor might be the disproportionate impact of superstars. A player with a 4 year career contributes 12 comparisons to the study, 3 for each of the 4 years he played. Ty Cobb contributes 476 comparisons to the study, 23 for each of the 24 seasons he played. He played 6 times longer but has an impact on the study 46 times greater. Since he peaked around 1915, those samples all say that the AL was weakest then when compared to the years when Cobb was younger or older. This is mitigated by other players in other stages of their career, but the point is that superstars are given disproportionate weight due to the lengths of their careers. Much better would be to only compare adjacent seasons, or to adjust the season weights some other way.

Did they use the same balls? Change them as often for the deadball years?

Each league had their own official baseball. Both leagues attempted to minimize the number used until the Chapman tragedy changed that attitude.

IIRC, the NL deadened their ball somewhat after the 1930 season.

Typo alert: 46 times greater should read 40 times greater

IIRC, the NL deadened their ball somewhat after the 1930 season.

That's what James says in NBJHBA, but he doesn't provide any details.

IIRC, the NL deadened their ball somewhat after the 1930 season.

It appears they juiced the ball in '34 to increase attendance.

jimd:
It's probably worth investigating. The local validity of the study assumes that league aging patterns are pretty similar through time.

Yes, and local is "far enough" from a disruption such as 1898-1903 or maybe 1913-1916. How persistent over time is a measured difference in league quality? If very persistent, then "far enough" is very far. (This point holds for any bias. Age pattern is merely a plausible source of bias re which we suppose a difference between Cramer and Davenport methods.)

Fewer league changes, as in the deadball era, implies more persistent measured differences. (Right?) Get it wrong in 1902 and that may have some impact even in 1912.

Another factor might be the disproportionate impact of superstars. A player with a 4 year career contributes 12 comparisons to the study, 3 for each of the 4 years he played. Ty Cobb contributes 476 comparisons to the study, 23 for each of the 24 seasons he played.

There may be a difference between C and D in the time span of the elementary intertemporal data. Eg, five years for Cramer(?): 1928 is compared with 1923,33 but not with 1922,34.

It appears they juiced the ball in '34 to increase attendance.

1933 looks like the outlier to me.

Anyhow, year-by-year micro-analysis of the variations of offense is not going to be too fruitful. The point I was trying to make was that the AL had a much higher offense levels from 1931-1941. The biggest differences were in 31, 33, 36-39.

This was following a period of 1922-1930 where the offense-levels of the two leagues more closely tracked each other. 1920-21 had the AL exiting the deadball era a little earlier than the NL. Then the two leagues tracked each other fairly closely for over a decade before that.

A plot would help here. :-)

1933 looks like the outlier to me.

I've been rereading The Dizziest Season lately and one of the big stories that year was the "rabbit ball" of '34 in the NL.

Offense did increase 17% that year, FWIW.

Offense did increase 17% that year, FWIW.

And it dropped 16-17% the year before. Attendance was down quite a bit in the NL, so they could have made some sort of correction.

Here is what I was talking about with the NL/AL:

year - NL - AL

19423.904.26
19414.234.74
19404.394.97
19394.445.21
19384.425.37
19374.515.23
19364.715.67
19354.715.09
19344.685.13
19333.975.00
19324.605.23
19314.485.14

19305.685.41
19295.365.01
19284.704.76
19274.584.92
19264.544.73
19255.065.20
19244.544.98
19234.854.78
19225.004.75

19214.595.12
19203.974.76
19193.654.09

19183.623.64
19173.533.65
19163.453.68
19153.623.96
19143.843.65

ACK! The pre-tag interpret's tabs as "no-space"?

OK... that's the second table I've messed up this week. I may give up. One more try... sorry guys...

year - NL - AL

1942---3.90---4.26
1941---4.23---4.74
1940---4.39---4.97
1939---4.44---5.21
1938---4.42---5.37
1937---4.51---5.23
1936---4.71---5.67
1935---4.71---5.09
1934---4.68---5.13
1933---3.97---5.00
1932---4.60---5.23
1931---4.48---5.14

1930---5.68---5.41
1929---5.36---5.01
1928---4.70---4.76
1927---4.58---4.92
1926---4.54---4.73
1925---5.06---5.20
1924---4.54---4.98
1923---4.85---4.78
1922---5.00---4.75

1921---4.59---5.12
1920---3.97---4.76

1919---3.65---4.09
1918---3.62---3.64
1917---3.53---3.65
1916---3.45---3.68
1915---3.62---3.96
1914---3.84---3.65

Anyhow, "Dizziest of Seasons" sounds like a cool book. I may put that one on my wish list.

Eg, five years for Cramer(?):

IIRC, Cramer used all possible comparisons (over some PA threshold), but that memory could be wrong, and IAC it's a memory of a summary, as I have never seen the original study.

If he did use all possible comparisons, then the fluke circumstance of having a number of long-career superstars peaking at around the same time in the same league would severely distort the league measurements at that peak.

OK, I found the 1980 BRJ. "Average Batting Skill" is six pages long, including the figure and table reproduced in The Hidden Game of Baseball.

Yes, Cramer used all pairs (one player, two league-seasons) with at least 20 PA each season.

Perhaps Davenport limits the comparisons. I was recalling a conversation that I initiated in the lobby at SABR34 this July. Dick Cramer observed that Davenport's method must be fairly close to his. He alluded to limiting the comparisons or the differences in some way. I am not sure that timespan of comparisons was the point, but I know I mentioned that Pete Palmer utilized only 1913-1916 data in his assessment of FL 1914-1915; only 1883-1885 data for UA 1884.

The approach should have been implemented many times. (Cramer agrees.) Does anyone know why that has not happened? Databases are widely available; computation is cheap; there are more sabermetricians. The empirical question is exceptionally interesting to many people.

Given any implementation of the approach, it should be trivial to vary the weights on observed differences according to timespan and number of BFP, and learn whether the results are robust. (Excluding all comparisons across time greater than some threshold is a special case using weight 0.)

Pete Palmer utilized only 1913-1916 data in his assessment of FL 1914-1915; only 1883-1885 data for UA 1884.

League-average performance, UA and FL.
Presuming contemporary NL=AA=1 and NL=AL=1.

UA 1884
OPS .76
ERA .875

FL 1914-1915
OPS .90
ERA .924

"League Performance" in the Glossary, Total Baseball 6 (1999).

Based on the Palmer study, old Total Baseball (Thorn & Palmer) incorporated a gross adjustment for league quality in OPS+ and ERA+ for players and teams (editions 6-7 only?).

UA 1884, stipulated league averages
OPS+ = ERA+ = 80

FL 1914-1915, stipulated league averages
OPS+ = ERA+ = 90

Average is 100 for every other MLB league-season.


How is league quality handled by TB7's descendants, Total Baseball 8 (Thorn) and The Baseball Encyclopedia (Palmer).

In one of the many discussions on this topic over the life of the HoM, I mentioned a conceptual difficulty I have with all measures of league quality that I've tried and seen discussed here:

Even if we can show, for example, that the NL has statistically better hitters in a particular year than the 1904 AL (whether by judging the average player using various methods, or by looking at standard deviations or through an analysis of the outliers), does that mean the NL was actually better than the AL that season? Couldn't that mean the NL pitching that year was worse than the AL pitching, thus reflecting better on the NL hitters? If so, then the NL wouldn't overall be a better league that season.

In other words, since all hitting stats are dependent not only on the quality of the hitters but also on the quality of the pitchers, and vice versa with respect to pitching stats, how can any hitting study (or pitching study) produce a conclusive result about league quality? Not to mention the fielding component.

Assuming that hurdle is overcome, quantifying it will be a separate thorny issue.

JeffM,
As you suggest, such intraleague analysis of batting and pitching statistics (not to mention one without the other) cannot support any interleague quality judgments. But Cramer (batters only), Palmer, and Davenport share a general interleague method, analysing only the records achieved in two leagues by the people who played in both.

There isn't much migration within a season, so the comparison of NL04 and AL04, for example, is mainly derived from comparisons of NL04 and AL03, AL04 and NL03, AL04 and NL02, and so on.

Paul:

I agree. But I see two lingering issues:

1. When I was looking at the NL vs. AA, the problem was there weren't a significant number of players who played in both leagues as regulars. That might be less of a problem with NL/AL, but you have to confine the analysis to a few years (maybe five years on either side), and that REALLY cuts down the sample size. You also have to make sure the average age of the sampled players is about the same, or you have other factors creeping in.

2. Even if you only analyze players who played in both leagues -- hitters for example -- you still have to know the level of pitching. So, it seems you'd need to know the records of hitters who played in both leagues during a specified time against the pitchers who pitched in both leagues during the same time. There is a hypothetical hybrid league in that scenario, but the sample size gets even smaller.

I'm not suggesting it not be studied; only that it is a very difficult problem.

Yes, the estimates for some league-season pairs is biased if the share of improving players who played in both league-seasons is different from the share of declining players.

The pitcher-batter simultaneity should not be a source of bias. Cramer, Palmer, and Davenport, at least, use batting statistics that are relative to league average, which incorporates the quality of league pitchers; and vice versa, except that Cramer does not look at pitchers.

--
By the way, Cramer and (I am practically certain) Davenport also use the data for NL04 and NL03, AL04 and AL03, etc, generated by those who play multiple years in the "same league" in the ordinary sense.

In effect, all of the interleague quality measures are estimated simultaneously. The estimated difference between NL09 and AL09 is not much influenced by the sparse data on NL08-AL09, AL08-NL09, etc, when there was little movement between NL and AL. Most of the data supporting relative quality in 1909 is ample data on NL03-NL04 ... NL08-NL09 and AL03-AL04 ... AL08-AL09 and ample data on NL00-AL01, AL00-NL01, ... AL02-NL03.

jimd and I alluded to this in #52 and #75, or something like that.

It's time to try posting this much.

C, P, and D use statistics that are relative to league average.

Eg, Pete Palmer's estimates for UA1884 mean that an average UA1884 pitcher, who also played in AA/NL/1883/1885, was 12.5% below average in the latter leagues (ERA+ .875). Sea-level in the UA was 12.5% below 1883/85 major league sea-level for pitchers; 24% below, for batters (OPS+ .76). Rolling hills in the UA pitchers box appear to be mountains. Molehills in the UA batters box appear to be mountains.

For those wondering about Davenport's 19th C. league adjustments, this is from his post to SABR-L in 2000. His methodology was similar to the study TomH describes in post 7, but comparisons are limited to two years (e.g. a player's 1883 performance is compared to his 1881, 1882, 1884, and 1885 numbers.)

These figures mean for instance that an AA player in 1882 with a .260 EQA would be equivalent to an NL player that year with a .196 EQA.


1882 AA 64.0
1883 38.6
1884 30.5
1885 22.0
1886 14.6
1887 12.1
1888 12.9
1889 11.5
1890 29.1
1891 20.4


1884 UA 70.9
1890 PL -3.0

OK, so if I'm understanding these numbers correctly, they would roughly be on the same scale that Davenport uses to gauge that the modern AAA is about 12.0 and 21st century Japanese Leagues are around 8.0, meaning that the AA was never, even at it's most talented point in 1889, as close to NL calibre as today's Japanese Central League or Pacific League are to the NL and AL?!

I think that's a reasonable comparison. The best players (H.Matsui, Ichiro!) would still be very good major leaguers, stars even, but the rank and file players were roughly of AAA quality, making it easier for the good players over there to dominate.

The system also shows the UA and PL about where I've eyeballed them in my head, so that gives it a little more credibility in my eyes.

His methodology was similar to the [The Hidden Game of Baseball] study TomH describes in post 7, but comparisons are limited to two years (e.g. a player's 1883 performance is compared to his 1881, 1882, 1884, and 1885 numbers.)

This is a very important difference in methodology.

When every available year comparison is used (as does the study cited in The Hidden Game of Baseball), the superstars receive a lot of extra weight, simply because they play so many years. A 5 year player contributes 4 samples to each of his 5 years, and a 21 year player contributes 20 samples to each of his 21 seasons. For his peak seasons, there are 10-15 samples implying that the league was "weak" those seasons, due to the assumption that the player's performance is constant over his career. Put a number of such stars in parallel in the same league (e.g. Cobb, Collins, Jackson, Baker) and there is most likely a noticeable impact on the results. In Davenport's study, most comparisons of peak seasons are only with other peak seasons or near-peak seasons; the problem is not completely eliminated, but it is greatly reduced.

Note: the total sample universe for each league season during the 1910's is around 500-600 samples from players that were full-time in both seasons plus a number of partial samples from non-regular players; Davenport's study has about half that number of full-time samples per season.

 Year   n0          n1          n2          n3          n4          n5          n6          
 ------ ----------- ----------- ----------- ----------- ----------- ----------- ----------- 

Testing.

 Year   n0         n1         n2         n3         n4         n5         n6         
 ------ ---------- ---------- ---------- ---------- ---------- ---------- ---------- 
   1930        263        187        165        149        124         95         84 
   1931        251        186        158        135        109         95         72 
   1932        263        202        163        133        114         98         74 
   1933        260        184        150        126        112         85         72 
   1934        261        185        158        133        105         96         75 
   1935        252        193        159        127        109         89         70 
   1936        256        181        149        132        107         86         66 
   1937        260        182        154        126        111         80         68 
   1938        257        189        158        134        102         80         58 
   1939        263        198        170        121         91         72         60 
   1940        274        202        157        114         82         69         95 
   1941        276        183        124         87         72        112         81 
   1942        269        155        100         77        123         99         82 
   1943        245        146        118        111         94         71         56 
   1944        242        150        106         88         70         52         37 
   1945        239         99         84         62         44         35         23 
   1946        283        195        156        130         94         81         64 
   1947        271        189        155        116        105         87         75 
   1948        286        192        151        137        120         93         72 
   1949        267        175        163        138        113         87         79 
   1950        249        187        157        130        109         98         77 
   1951        258        184        157        127        116         91         78 
   1952        262        180        142        135        111        100         83 
   1953        256        172        150        127        115        104         75 
   1954        277        201        169        150        128        105         89 
   1955        283        201        180        157        124        104         91 

n0: the number of regulars (my definition) in MLB that year
n1: the number of regulars that were also regulars the following year
n2: the number of regulars that were also regulars two years in the future
n6: the number of regulars that were also regulars six years in the future

The point of providing the 25 year span is to allow one to get an idea of typical turnover, and to then compare the effect of the WWII years on that typical turnover.

Some specific points: the transition from 1941 to 1942 (1941-n1) is not way out-of-line, though it is a little low. The war did not have a major impact on MLB in 1942. The following four years show significant turnover, culminating in the dramatic return in 1946 (1945-n1) when only about 40% of the 1945 regulars kept their jobs.

Look at the data points 1942-n4, 1941-n5, 1940-n6. These represent the number of players in these years who were regulars in 1946. They were MUCH more likely to have retained/regained their jobs than typical MLB regulars after the same time interval with no war situation. I don't know if this represented an effort on MLB's part to give the returning veterans every opportunity to regain their jobs, or the impact of the war on the development of the minor league players that would normally have replaced some of these players.

1882 AA 64.0
1883 38.6
1884 30.5
1885 22.0
1886 14.6
1887 12.1
1888 12.9
1889 11.5
1890 29.1
1891 20.4


1884 UA 70.9
1890 PL -3.0

Anyone off hand happen to have Davenport's Federal League adjustment on this same scale?

The Davenport adjustments are not simply a percentage. They are more complex, having an adjustment involving the league replacement levels as well.

The following table shows 3 Federal League CF'ers from 1915:

 W-1 W-2 Delt  AdjGm Name
13.2 9.4 (3.8) 136.3 Kauff
 7.0 3.4 (3.6) 145.9 Roush
 4.4 1.0 (3.4) 154.3 Oakes

As you can see, the amount of value lost going from WARP-1 to WARP-2 is fairly constant (though not completely). Kauff loses more absolute value, showing that there is also a percentage involved, but Oakes loses almost all of his value, presumably based on the notion that he was very close to AL/NL replacement level.

So some Federal League value is removed purely because it has no Major League value, because it is sub-replacement value. The residue from this adjustment is apparently then modified by applying a percentage.

FWIW, as I posted in the other thread, the 3-player example above gives a regression of a subtraction of about 3.25 WARP, and then a discount of about 4.3%.


This is obviously a system that is going to be much more forgiving to star players in an inferior league than a straight % discount.

This is obviously a system that is going to be much more forgiving to star players in an inferior league than a straight % discount.

And it should be. A typical Federal Leaguer had positive value in that league, but would be unable to land a Major League starting job after the collapse (near-zero real value). OTOH, Kauff moved into the majors and was a second-tier star (though not the Ty Cobb/Tris Speaker that his raw FL stats might indicate).

A straight discount does not capture this, and so doesn't correspond to the true situation.

A simple regression analysis of Jim's 3 player example:

Adjusted WARP = .957 * Raw WARP - 3.25

As you can see, after the subtraction takes place, the actual percentage adjustment is only 4.3.

Of course, it's more complicated than that, because batting and fielding are regressed separately.

jimd #96
Look at the data points 1942-n4, 1941-n5, 1940-n6. These represent the number of players in these years who were regulars in 1946. They were MUCH more likely to have retained/regained their jobs than typical MLB regulars after the same time interval with no war situation. I don't know if this represented an effort on MLB's part to give the returning veterans every opportunity to regain their jobs, or the impact of the war on the development of the minor league players that would normally have replaced some of these players.

Some right of return to a civilian job was provided by law. I don't know details.

For a time including the 1945 and 1946 seasons, MLB roster limits were increased by 20%, partly to make compliance easy.

Cliff Blau, "League Operating Rules"

Thanks for that WARP2 info jim!

I'm hating the Bob Caruthers induction more and more . . .

If your system says that Buzz Arlett should be in and Caruthers shouldn't, I'd junk the system, if I were you.

Thinking that this is the most appropriate thread for this.

I've calculated career league-adjusted Win Shares above replacement. Replacement level is defined as 1.27 WS per 100 plate appearances, a value determined empirically for the 1901-1940 2-league seasons.

League adjustments are only done when there are mulitiple leagues in a single season, and are done to "equalize" the leagues. No attempt is made to compare leagues across seasons. The parameters in the league adjustments are determined by comparing the performances of individual players, in between seasons. To prevent uncontrolled divergences, 9 average players are added to the data set as players who switched leagues between seasons without change of performance.

The league parameters are determined for each season. Rather than give the full set of data, I just give the 20th century decade-averaged factors that I use to convert actual performance to neutral-league performance.

1900s NL: 0.9473 * WS + 0.00043 * PA
1900s AL: 1.0530 * WS - 0.00044 * PA
1910s FL: 1.0576 * WS - 0.00631 * PA
1910s NL: 1.0037 * WS - 0.00206 * PA
1910s AL: 0.9849 * WS + 0.00332 * PA
1920s NL: 0.9994 * WS - 0.00287 * PA
1920s AL: 1.0007 * WS + 0.00286 * PA
1930s NL: 0.9940 * WS - 0.00126 * PA
1930s AL: 1.0061 * WS + 0.00126 * PA


In presenting the position player leaders in career LAWSAR, I divide players' seasons into 4 roles: C, 1B, "IF" (2B/3B/SS), "OF" (LF/CF/RF), according to the position where they played the plurality of their games. If a position player played some games in a season as a pitcher, I subtracted estimated pitching WS from their totals; if they played a plurality of games as a pitcher, I regretfully did not include that season. Recognizing that the following data is not appropriate for short-season 19th century players, I nonetheless give the top 100 career LAWSAR, 1876-1940 for each role, as well as grand totals for players with more than one role in their career, and the top 100 overall:

C
 Hartnet 214 Cochran 211 Dickey_ 195 Schang_ 161 Schalk_ 131 
 Ewing_B 124 Bresnah 114 Bennett 113 Ruel_Mu 104 McGuire 100
 O'Neill  99 Ferrell  96 Zimmer_  92 Clement  90 Kling_J  90
 Lombard  90 OFarrel  88 Severei  87 Farrell  86 Meyers_  83
 Carroll  80 Davis_S  78 McFarla  74 Bassler  73 Gowdy_H  72
 Snyder_  71 Hargrav  66 Sewell_  64 Grady_M  64 Mancuso  64
 Schreck  61 Hogan_S  60 Milliga  59 Danning  56 Miller_  56 
 Gibson_  55 Smith_E  54 Lopez_A  53 Peitz_H  53 Wingo_I  53
 Wilson_  52 Hemsley  52 Wilson_  50 Perkins  49 Criger_  49
 Nunamak  48 Carriga  48 Pytlak_  46 Phelps_  45 Rowe_Ja  45
 Lapp_Ja  45 Picinic  44 Flint_S  43 Kelly_K  43 Warner_  43 
 Rariden  42 Easterl  42 Robinso  42 Ainsmit  42 Snyder_  42
 York_Ru  41 Killefe  39 OConnor  38 Schrive  38 Moran_P  38
 OBrien_  37 Clarke_  36 Gharrit  36 Myatt_G  36 Hargrav  35
 Archer_  34 Collins  34 Clapp_J  34 McLean_  34 Ganzel_  33
 Clarke_  33 Dooin_R  32 Gonzale  32 Henry_J  32 Gross_E  32
 Keenan_  31 Bowerma  31 Mack_Co  30 Hayes_F  30 Sulliva  30
 White_D  29 Daily_C  29 McCarty  29 Gilliga  29 Thomas_  29
 Gooch_J  28 Brown_L  28 DeBerry  27 Doyle_J  27 Bushong  27
 Bemis_H  27 Sweeney  26 Jacklit  26 Todd_Al  26 Sugden_  26

1B
 Gehrig_ 388 Foxx_Ji 288 Brouthe 259 Anson_C 244 Connor_ 234
 Beckley 190 Sisler_ 187 Judge_J 178 Terry_B 172 Konetch 158
 Davis_H 155 Fournie 147 Chance_ 145 Bottoml 137 Daubert 132
 Chase_H 132 Burns_G 130 McInnis 129 Pipp_Wa 128 Greenbe 128
 Blue_Lu 126 Tenney_ 118 Mize_Jo 115 Trosky_ 110 Merkle_ 101
 Orr_Dav  99 McGann_  99 Camilli  90 Tucker_  90 Start_J  88
 Kuhel_J  88 Reilly_  87 Collins  87 Suhr_Gu  87 Gandil_  84
 Stahl_J  82 Luderus  81 Bonura_  81 Kelly_G  81 Hoblitz  79
 Sheely_  73 Grimm_C  71 Morrill  71 Doyle_J  63 Harris_  62
 Saier_V  62 Stovey_  62 Anderso  59 Morgan_  54 Larkin_  54
 Phillip  53 Bransfi  50 Hickman  49 Donahue  49 Alexand  47
 Hauser_  46 Jordan_  46 LaChanc  45 McCormi  45 Stovall  44
 Farrar_  43 Fletche  42 Foutz_D  41 Grimes_  41 Comiske  41
 Leslie_  41 Grantha  40 Miller_  38 Werden_  38 Bissone  36
 Hurst_D  36 Rossman  35 Ganzel_  35 Virtue_  34 Jordan_  33
 Gainer_  33 McKinno  30 Johnsto  30 Heilman  27 Lajoie_  27
 McQuinn  27 Hendric  24 Fonesca  24 Freeman  23 Ewing_B  23
 Unglaub  22 Griggs_  21 Jones_T  21 Isbell_  21 Kelley_  21
 Holke_W  21 White_D  20 Tebeau_  20 Powell_  20 Schmidt  19
 Bressle  18 Schombe  18 Clark_W  18 Jenning  18 Burns_J  18

IF
 Collins 454 Wagner_ 434 Lajoie_ 359 Hornsby 358 Gehring 267
 Davis_G 258 Dahlen_ 257 Baker_F 234 Frisch_ 213 Cronin_ 210
 Wallace 209 Vaughan 201 Sewell_ 193 Collins 185 Gardner 183
 Doyle_L 181 McPhee_ 178 Glassco 175 Lazzeri 173 Groh_He 169
 Myer_Bu 168 Pratt_D 168 Evers_J 165 Long_He 160 Peckinp 159
 Tinker_ 152 Childs_ 151 Traynor 150 Bush_Do 146 McGraw_ 144
 Nash_Bi 143 Bancrof 142 Maranvi 140 Dykes_J 138 William 136
 Appling 134 Cross_L 133 Fletche 131 Zimmerm 131 Kamm_Wi 130
 Pfeffer 128 McKean_ 127 Herman_ 126 Elberfe 125 Huggins 125
 Jenning 124 Bishop_ 124 McManus 123 Bradley 123 William 122
 Latham_ 122 Lyons_D 120 Devlin_ 119 Ward_Mo 118 Dunlap_ 118
 Steinfe 115 Ritchey 115 Jackson 114 Richard 111 Sutton_ 111
 Daly_To 111 Foster_ 110 Leach_T 109 Bartell 106 Bluege_ 105
 Hack_St 104 Chapman 103 Parent_ 102 Burns_T 102 Weaver_ 101
 Turner_  98 Rogell_  98 Corcora  95 Smith_R  94 Shindle  93
 Pinkney  92 Wise_Sa  92 Clift_H  91 Smith_G  90 Joyce_B  89
 Cuccine  89 Denny_J  88 Stock_M  87 Rolfe_R  87 Herzog_  86
 Lary_Ly  85 Crosett  84 Barry_J  83 Werber_  83 Lobert_  82
 Scott_E  82 Austin_  81 LaPorte  81 White_D  80 Harris_  80
 Travis_  77 Kress_R  77 Lowe_Bo  76 Murphy_  76 English  75

OF
 Cobb_Ty 590 Ruth_Ba 536 Speaker 509 Crawfor 335 Simmons 274
 Burkett 271 Clarke_ 263 Ott_Mel 254 Goslin_ 253 Waner_P 247
 Hamilto 242 Heilman 239 Jackson 237 Delahan 233 Wheat_Z 231
 Rice_Sa 221 Hooper_ 220 Flick_E 220 Keeler_ 217 Magee_S 216
 Sheckar 210 ORourke 204 Ryan_Ji 203 Averill 201 Jones_F 198
 Duffy_H 198 Manush_ 194 VanHalt 191 Veach_B 191 Carey_M 190
 Gore_Ge 189 Roush_E 189 Milan_C 185 Kelley_ 180 Cuyler_ 172
 Hines_P 170 Tiernan 169 Thomas_ 169 Burns_G 168 Hartsel 161
 Griffin 161 Thompso 160 Berger_ 159 Combs_E 159 Medwick 150
 Hoy_Dum 149 William 147 Stahl_C 142 Wilson_ 140 Beaumon 140
 ONeill_ 137 Kelly_K 137 Klein_C 137 Cravath 136 Schulte 134
 Dougher 132 Chapman 131 Selbach 129 Miller_ 126 Paskert 125
 Brownin 124 Seymour 123 Herman_ 123 Meusel_ 123 Youngs_ 122
 Waner_L 122 Stovey_ 121 Lewis_D 120 Kauff_B 120 Jacobso 120
 DiMaggi 120 Strunk_ 118 William 116 Titus_J 115 Smith_E 114
 Brown_T 114 Donlin_ 112 Johnson 111 West_Sa 110 Hafey_C 110
 Walker_ 109 Jamieso 109 Stone_G 108 Dalrymp 106 Jones_C 105
 Wood_Ge 104 Tobin_J 104 Seybold 103 Shotton 102 Mertes_ 101
 McIntyr 100 Donovan 100 Green_D  98 Slagle_  98 Falk_Bi  96
 Stone_J  94 Felsch_  92 Hanlon_  92 Brodie_  92 McCarth  92

multi-role
 Wagner_ 481 Lajoie_ 386 Hornsby 358 Foxx_Ji 306 Ott_Mel 284
 Davis_G 281 Brouthe 271 Connor_ 267 Anson_C 267 Heilman 266
 Delahan 256 Magee_S 227 ORourke 221 Keeler_ 219 Sheckar 211
 Kelly_K 209 Ryan_Ji 204 Kelley_ 201 Leach_T 199 Stovey_ 183
 Schang_ 182 Ewing_B 180 Hines_P 178 Richard 166 Chance_ 162
 Cross_L 158 Brownin 152 Bresnah 150 Dykes_J 150 Greenbe 149
 Murphy_ 149 Ward_Mo 145 Jenning 142 Chapman 141 Herman_ 139
 Daly_To 136 McInnis 133 White_D 132 Burns_G 131 Tenney_ 129
 Anderso 127 Burns_O 123 Lyons_D 121 Stephen 121 Devlin_ 120
 Mertes_ 113 Sutton_ 113 West_Sa 111 Joyce_B 107 Farrell 106
 Larkin_ 106 Wise_Sa 104 Grantha 104 Parent_ 103 Lindstr 103
 Freeman 103 McGann_ 102 Turner_ 102 Rowe_Ja  98 Smith_R  96
 Morrill  96 Lowe_Bo  95 Delahan  95 Doyle_J  94 Lange_B  93
 Kelly_G  93 Hickman  92 Harris_  91 Oldring  89 Mostil_  89
 Conroy_  89 Hofman_  86 Stahl_J  85 Martin_  85 Carroll  84
 Collins  82 Gessler  80 Strang_  79 Kress_R  78 Flagste  78
 McFarla  75 Robinso  74 Grady_M  74 Schaefe  73 Shanks_  73
 Cooley_  72 Gowdy_H  72 Radford  71 Johnsto  70 Miller_  69
 Richard  68 Ward_Aa  68 Galan_A  66 Miller_  66 Collins  66
 Milliga  65 Peitz_H  64 Rice_Ha  64 Swartwo  64 Foutz_D  62

overall
 Cobb_Ty 590 Ruth_Ba 536 Speaker 509 Wagner_ 481 Collins 454
 Gehrig_ 388 Lajoie_ 386 Hornsby 358 Crawfor 335 Foxx_Ji 306
 Ott_Mel 284 Davis_G 281 Simmons 274 Burkett 271 Brouthe 271
 Connor_ 267 Anson_C 267 Gehring 267 Heilman 266 Clarke_ 263
 Dahlen_ 257 Delahan 256 Goslin_ 253 Waner_P 247 Hamilto 242
 Jackson 237 Baker_F 234 Wheat_Z 231 Magee_S 227 Rice_Sa 221
 ORourke 221 Hooper_ 220 Flick_E 220 Keeler_ 219 Hartnet 214
 Frisch_ 213 Sheckar 211 Cochran 211 Cronin_ 210 Kelly_K 209
 Wallace 209 Ryan_Ji 204 Averill 201 Vaughan 201 Kelley_ 201
 Leach_T 199 Jones_F 198 Duffy_H 198 Dickey_ 195 Manush_ 194
 Sewell_ 193 VanHalt 191 Veach_B 191 Carey_M 190 Beckley 190
 Gore_Ge 189 Roush_E 189 Sisler_ 187 Collins 185 Milan_C 185
 Gardner 183 Stovey_ 183 Schang_ 182 Doyle_L 181 Ewing_B 180
 Judge_J 178 Hines_P 178 McPhee_ 178 Glassco 175 Lazzeri 173
 Cuyler_ 172 Terry_B 172 Tiernan 169 Thomas_ 169 Groh_He 169
 Myer_Bu 168 Pratt_D 168 Burns_G 168 Richard 166 Evers_J 165
 Chance_ 162 Hartsel 161 Griffin 161 Long_He 160 Thompso 160
 Berger_ 159 Combs_E 159 Peckinp 159 Cross_L 158 Konetch 158
 Davis_H 155 Brownin 152 Tinker_ 152 Childs_ 151 Traynor 150
 Bresnah 150 Medwick 150 Dykes_J 150 Greenbe 149 Murphy_ 149

This chart makes clear that we are doing an excellent job overall. We're really fighting over the borderline guys. While the above ratings are not exactly my system, they make clear why I rate Schang so highly. Rice and Hooper, as the top unelected players in career LAWSAR, post-Goslin, seem particularly underrated.

In the spirit of full disclosure, I give the career WSAR totals without league adjustments, 1876-1940. I do not endorse these numbers.

C
 Hartnet 228 Cochran 196 Dickey_ 186 Schang_ 145 Bresnah 122
 Ewing_B 116 Schalk_ 113 Bennett 103 McGuire 102 OFarrel 101
 Kling_J  97 Lombard  94 Ruel_Mu  89 Zimmer_  89 Meyers_  88
 Ferrell  88 Clement  87 Davis_S  85 O'Neill  82 Farrell  82
 Snyder_  81 Carroll  78 Gowdy_H  78 Hargrav  75 Severei  74
 McFarla  72 Mancuso  70 Grady_M  66 Hogan_S  66 Bassler  64
 Wingo_I  62 Smith_E  62 Milliga  61 Wilson_  61 Gibson_  61
 Lopez_A  60 Wilson_  59 Schreck  57 Danning  56 Peitz_H  54
 Sewell_  53 Miller_  53 Hemsley  52 Rariden  51 Snyder_  48
 Phelps_  48 Robinso  47 Criger_  46 Killefe  44 OBrien_  44
 Easterl  43 Pytlak_  43 Carriga  43 OConnor  42 Nunamak  41
 Moran_P  41 Picinic  41 Warner_  41 York_Ru  41 Kelly_K  41
 Lapp_Ja  40 Gonzale  40 McLean_  39 Clarke_  39 Archer_  39
 Dooin_R  38 Perkins  38 Rowe_Ja  38 Ainsmit  37 Flint_S  36
 Schrive  36 Gooch_J  35 Clapp_J  34 Keenan_  33 DeBerry  33
 Bowerma  33 Taylor_  32 Hargrav  32 McCarty  32 Gross_E  31
 Collins  31 Ganzel_  31 Todd_Al  30 Clarke_  30 Jacklit  30
 Myatt_G  29 White_D  29 Gharrit  29 Brown_L  29 Hayes_F  29
 Schmidt  29 Doyle_J  28 Henline  28 Grace_E  28 Schlei_  27
 Sulliva  27 Henry_J  27 Bushong  27 Miller_  26 Clemons  26

1B
 Gehrig_ 367 Foxx_Ji 277 Brouthe 247 Anson_C 229 Connor_ 222
 Terry_B 188 Beckley 187 Konetch 177 Sisler_ 169 Chance_ 156
 Fournie 154 Bottoml 154 Judge_J 154 Daubert 152 Davis_H 146
 Chase_H 130 Tenney_ 126 Greenbe 123 Pipp_Wa 116 Mize_Jo 115
 McInnis 114 Merkle_ 112 Burns_G 109 Trosky_ 107 Blue_Lu 106
 McGann_ 103 Orr_Dav 102 Kelly_G  97 Suhr_Gu  94 Camilli  94
 Collins  93 Luderus  92 Reilly_  91 Grimm_C  90 Tucker_  88
 Hoblitz  82 Kuhel_J  80 Start_J  79 Bonura_  76 Stahl_J  75
 Gandil_  70 Saier_V  67 Stovey_  64 Doyle_J  64 Sheely_  63
 Morrill  60 Harris_  58 Anderso  57 Larkin_  54 Comiske  54
 Bransfi  54 Jordan_  50 Phillip  49 Morgan_  48 Grimes_  46
 Hickman  46 Grantha  46 LaChanc  46 McCormi  45 Leslie_  45
 Donahue  44 Werden_  44 Fletche  43 Alexand  42 Stovall  42
 Hurst_D  42 Miller_  42 Bissone  41 Hauser_  40 Foutz_D  40
 Jordan_  37 Ganzel_  35 Farrar_  34 Virtue_  31 Rossman  31
 Holke_W  30 Gainer_  29 Hendric  28 Lajoie_  26 McKinno  25
 McQuinn  24 Heilman  24 Freeman  23 Ewing_B  23 Johnsto  22
 Hecker_  22 Bressle  21 Kelley_  21 Fonesca  21 Griggs_  20
 White_D  20 Tebeau_  20 Burrus_  20 Isbell_  20 Herman_  19
 Taylor_  19 Unglaub  19 Cartwri  19 Schmidt  19 Borton_  18


IF
 Wagner_ 458 Collins 422 Hornsby 383 Lajoie_ 339 Dahlen_ 262
 Davis_G 251 Gehring 250 Frisch_ 238 Baker_F 216 Vaughan 207
 Cronin_ 199 Wallace 196 Doyle_L 195 McPhee_ 186 Groh_He 183
 Collins 179 Evers_J 177 Sewell_ 171 Traynor 170 Tinker_ 167
 Glassco 166 Bancrof 165 Gardner 161 Maranvi 161 Lazzeri 159
 Long_He 157 Myer_Bu 154 Childs_ 152 Pratt_D 145 McGraw_ 145
 Fletche 142 Zimmerm 141 Nash_Bi 137 Huggins 136 Herman_ 135
 Peckinp 133 William 131 Cross_L 130 Jackson 130 Devlin_ 129
 Latham_ 127 Appling 127 Lyons_D 126 Jenning 125 McKean_ 124
 Steinfe 123 Bush_Do 122 Ritchey 120 Dykes_J 118 Elberfe 117
 Bradley 117 Bartell 117 Leach_T 115 Kamm_Wi 113 Pfeffer 112
 Dunlap_ 112 Bishop_ 111 William 110 Ward_Mo 110 Daly_To 110
 Hack_St 107 McManus 106 Stock_M 104 Smith_R 100 Richard 100
 Sutton_  99 Cuccine  98 Herzog_  98 Parent_  97 Corcora  95
 Pinkney  93 Foster_  91 Lobert_  91 Chapman  90 Rogell_  89
 Smith_G  89 Bluege_  89 Shindle  89 Burns_T  89 Joyce_B  87
 Clift_H  86 English  86 Weaver_  85 Turner_  85 Wright_  83
 Lindstr  82 Rolfe_R  82 Wise_Sa  80 Fennell  79 LaPorte  79
 Doolan_  78 Werber_  77 Lary_Ly  77 Mowrey_  76 Bridwel  76
 Crosett  76 Denny_J  75 Lowe_Bo  75 Frey_Lo  73 Travis_  73


OF
 Cobb_Ty 556 Ruth_Ba 508 Speaker 478 Crawfor 313 Clarke_ 276
 Ott_Mel 269 Waner_P 267 Burkett 266 Simmons 255 Wheat_Z 253
 Hamilto 241 Magee_S 233 Goslin_ 231 Delahan 228 Jackson 222
 Sheckar 222 Heilman 219 Carey_M 215 Keeler_ 212 Roush_E 211
 Flick_E 210 Duffy_H 196 Ryan_Ji 196 Rice_Sa 194 Hooper_ 191
 Jones_F 190 Cuyler_ 190 Averill 189 VanHalt 189 ORourke 187
 Burns_G 185 Kelley_ 181 Manush_ 179 Thomas_ 178 Gore_Ge 172
 Berger_ 169 Veach_B 169 Tiernan 166 Milan_C 164 Medwick 158
 Griffin 158 Hines_P 157 Thompso 154 Wilson_ 154 Hartsel 150
 Beaumon 149 Klein_C 149 Hoy_Dum 148 Schulte 145 Combs_E 144
 Cravath 143 ONeill_ 139 Stahl_C 138 Paskert 138 Youngs_ 138
 William 137 Waner_L 136 Seymour 134 Herman_ 133 William 131
 Kauff_B 130 Kelly_K 129 Titus_J 127 Selbach 125 Brownin 125
 Dougher 122 Chapman 122 Hafey_C 121 Donlin_ 120 DiMaggi 119
 Brown_T 118 Stovey_ 118 Smith_E 114 Jones_C 111 Miller_ 109
 Meusel_ 107 Johnson 106 Lewis_D 104 Slagle_ 104 Jacobso 104
 Mertes_ 103 Welch_C 102 Strunk_ 101 Donovan 101 Stone_G  99
 McCarth  99 West_Sa  99 Stephen  99 ODoul_L  99 Leach_T  98
 Seybold  98 Stengel  97 Dalrymp  94 Tobin_J  94 Green_D  94
 Meusel_  94 Moore_J  93 Wood_Ge  93 Walker_  92 McIntyr  92


multi-role
 Wagner_ 506 Hornsby 383 Lajoie_ 365 Ott_Mel 297 Foxx_Ji 294
 Davis_G 270 Brouthe 258 Anson_C 253 Connor_ 251 Delahan 248
 Magee_S 245 Heilman 243 Sheckar 223 Keeler_ 215 Leach_T 213
 ORourke 204 Kelley_ 202 Ryan_Ji 196 Kelly_K 196 Stovey_ 182
 Chance_ 172 Ewing_B 168 Hines_P 164 Schang_ 164 Bresnah 160
 Brownin 158 Cross_L 155 Richard 153 Herman_ 152 Greenbe 146
 Jenning 143 Murphy_ 139 Tenney_ 137 Daly_To 133 Chapman 132
 Devlin_ 131 Ward_Mo 129 Dykes_J 129 Lyons_D 127 Stephen 126
 Anderso 123 Burns_O 123 Grantha 118 White_D 118 McInnis 117
 Mertes_ 117 Lindstr 116 Kelly_G 111 Larkin_ 110 Burns_G 109
 McGann_ 106 Joyce_B 104 Smith_R 104 Farrell 104 Sutton_ 101
 Freeman 100 West_Sa  99 Hofman_  98 Parent_  97 Doyle_J  95
 Lange_B  93 Lowe_Bo  92 Martin_  92 Wise_Sa  92 Delahan  91
 Turner_  88 Hickman  87 Johnsto  86 Rowe_Ja  85 Harris_  85
 Morrill  84 Conroy_  82 Strang_  82 Carroll  81 Gowdy_H  79
 Stahl_J  78 Robinso  77 Swartwo  77 Grady_M  77 Mostil_  76
 Oldring  76 Gessler  75 Miller_  75 Cooley_  73 McFarla  72
 Galan_A  71 Kress_R  69 Bressle  68 Milliga  67 Hogan_S  67
 Schaefe  67 Collins  66 Radford  66 Peitz_H  65 Flagste  64
 Miller_  64 Collins  64 Foutz_D  62 Bigbee_  61 Stripp_  59


overall
 Cobb_Ty 556 Ruth_Ba 508 Wagner_ 506 Speaker 478 Collins 422
 Hornsby 383 Gehrig_ 367 Lajoie_ 365 Crawfor 313 Ott_Mel 297
 Foxx_Ji 294 Clarke_ 276 Davis_G 270 Waner_P 267 Burkett 266
 Dahlen_ 262 Brouthe 258 Simmons 255 Wheat_Z 253 Anson_C 253
 Connor_ 251 Gehring 250 Delahan 248 Magee_S 245 Heilman 243
 Hamilto 241 Frisch_ 238 Goslin_ 231 Hartnet 228 Sheckar 223
 Jackson 222 Baker_F 216 Keeler_ 215 Carey_M 215 Leach_T 213
 Roush_E 211 Flick_E 210 Vaughan 207 ORourke 204 Kelley_ 202
 Cronin_ 199 Ryan_Ji 196 Wallace 196 Cochran 196 Kelly_K 196
 Duffy_H 196 Doyle_L 195 Rice_Sa 194 Hooper_ 191 Jones_F 190
 Cuyler_ 190 Averill 189 VanHalt 189 Terry_B 188 Beckley 187
 Dickey_ 186 McPhee_ 186 Burns_G 185 Groh_He 183 Stovey_ 182
 Collins 179 Manush_ 179 Thomas_ 178 Konetch 177 Evers_J 177
 Gore_Ge 172 Chance_ 172 Sewell_ 171 Traynor 170 Berger_ 169
 Veach_B 169 Sisler_ 169 Ewing_B 168 Tinker_ 167 Tiernan 166
 Glassco 166 Bancrof 165 Hines_P 164 Milan_C 164 Schang_ 164
 Gardner 161 Maranvi 161 Bresnah 160 Lazzeri 159 Medwick 158
 Griffin 158 Brownin 158 Long_He 157 Cross_L 155 Fournie 154
 Thompso 154 Bottoml 154 Myer_Bu 154 Judge_J 154 Wilson_ 154
 Richard 153 Herman_ 152 Childs_ 152 Daubert 152 Hartsel 150

Hello! This is my first post here, although I have been following the Hall of Merit voting discussions for several months now.

It seems to me that the most essential piece of information, needed to fairly evaluate players from different leagues and eras, is the relative strengths of those leagues and eras. Without this information, we are reduced to little more than hand-waving when comparing statistics from differing league-seasons.

It seems to me that there is in fact a way to create a table of relative league-season strengths for each statistic being looked at (i.e. OPS+). This method utilises the year-to-year performances of the players who participated in a league for at least two years in a row.

I had found that when I compared the performance of all the individual players in a league in OPS+ from one year to the next, the percentage change in performance correlated strongly with age, in a linear fashion. The player's performance grew strongly in their early to mid twenties, leveled off at 29-30, and started to decline at later ages, with the rate of decline increasing with increasing age.

I was a bit surprised that the peak years were 29-30, since I had read Bill James's study suggesting that 27-28 are the peak years, but the difference is easily explained by the fact that I was looking at those players who remained regulars in both years, while James apparently included all plate appearances, including those players who, due to injuries or other causes, were no longer considered good enough to remain regulars. In other words, if a player remains healthy, they will generally peak at 29-30, but if you look at the players as a whole, including those who become injured, the peak years shift downward by about two years.

I have only done this for a few sets of league seasons, but I noticed that the SLOPE of the linear best-fit (LBF) barely changes, while the height of the best-fit at any given age does change. This means that for any given pair of consecutive league-seasons, the linear best-fit can be described by a constant (the slope of the LBF, which barely changes) and a variable (the height of the LBF at some specified age--say, 30 years old), which DOES change.

If we have two pairs of league-seasons, and one pair of league-seasons yields a LBF at age 30 of 0%, and the other pair yields a LBF at age 30 of -10%, then we can say that whatever change in league quality happened between the first and second league-seasons of the first pair (call it x%), the second pair showed a change of (x+10)% between the first and second league-seasons of the pair. The (x+10)% general change in the league, from one season to the next resulted in a -10% change in year-to-year OPS+ for the average player, in addition to the expected aging pattern, compared to the other pair of league-seasons.

This fact means that for each league, a table of year-to-year changes in OPS+ can be created, of the form (making these numbers up):

1901-02: +3%
1902-03: -1%
1903-04: +2%
.
.
.
2003-04: 0%

where we are measuring the LBF for that season pair at some particular player age (30.0 is a nice even number).

This in itself would not give an ABSOLUTE measure of year-to-year change in the league, but we have two leagues that span the twentieth century, the AL and the NL, and we can cross-reference them! By repeatedly running the full 1901-2004 AL and NL tables, with different constant year-to-year percentage changes added to the listed year-to-year percentage changes, we can generate numerous sets of yearly percentage differences between the AL and NL over the past century, the year-to-year differences varying by what constant year-to-year percentage is added. By comparing the known historical league-to-league differences (determined by looking at players who switch leagues) with the generated lists, we should be able to find out which constant year-to-year change best fits the data.

This would give us the ABSOLUTE league strengths (with respect to OPS+) of the AL and NL since 1901, and since we would now have the constant year-to-year change, we can extend the chain back into the nineteenth century, and cross-link with the other major leagues as well.

I am offering this idea to the members of this discussion forum, to pick apart and (hopefully) put back together in a workable form. I cannot see any problems myself, but if there are any, and if those problems can be fixed, I believe that this procedure will finally give us the absolute strengths of each major league season, allowing absolute comparisons of every player-season.

Bill

Seems like a good idea to me, but I'm not very good on these kinds of thing. I think the difficulty you'll face will be logistical: how long will it take you to put the study together?

As someone who isn't terribly well informed on the math side of things, how would be able to tell if 1902 is strong than 1997 without any players who played in both leagues? (The LBF and slope/height/intercept talk isn't so much scary or anethma to me as it is simply outside the boundaries of my education.)

In other words, the results may be listed as

1901 +1
1902 +2
1903 0
.
.
.
1997 -5

but what are those numbers saying and how do they relate to one another when they are not contiguous seasons? Or put another way, what's the baseline against which these absolute values are being measured?

This is a good time to address a few points that I forgot to include in my first post.

The first is: how can I use OPS+ as an example of changes from year to year when it is, by definition, normalised to the league? Wouldn't the LBF always be anchored to an average value of 0% change?

The answer is that no, it would not be. I am assuming that the aging patterns of the individual players follow (on average) a typical path of growth and then decline, with the peak absolute production, at age 29-30, determined by the player's intrinsic ability. This intrinsic ability would not change over the course of a particular player's career, although their production, as a percentage of their peak production, would change as they aged. The league as a whole would increase in strength when the intrinsic ability of the new full-time players exceeds the intrinsic ability of those full-time players that they are replacing. Similarly, if the intrinsic ability of the replacement players is lower than the intrinsic ability of those they replace (such as during WWII), the league as a whole would decrease in strength.

The key fact in this is that it is the first-time regular players (and departing regulars) who determine the change in the intrinsic league strength, and since I only include players with two consecutive full-time seasons, they are not included in my study. OPS+ measures how the players I include perform relative to the league as a whole, including the first-time regulars, and hence if the first-time regular players are stronger than those they replace, the rest of the full-time players will have an OPS+ lower than they would have otherwise, in inverse proportion to the change in intrinsic strength of the league as a whole.

In answer to your question, Dr. Chaleeko, on my own this study would take almost forever. I am limited to using a spreadsheet to reduce each league-season-to-league-season pair, entering each player's OPS+ by hand. It takes me the better part of a day to do each pair, so at one day per pair, to do all league pairs would take 250 days, with no days off.

To answer your second question, about how to compare seasons separated by decades or longer, we cannot directly compare them. We can only compare successive league-seasons. This is where the fact that the twentieth century had two recognised major leagues comes in. We have to find a value for the 'constant' year-to-year change that results in the observed year-to-year differences in strength between the NL and the AL, as measured by players switching leagues--for example, if a player (after adjusting for the player's expected aging pattern, and the player's expected adjustment time) drops from an OPS+ of 110 in the NL in 1950, to an OPS+ of 105 in the AL in 1951, then this suggests that the 1951 AL is 4.76% stronger than the 1950 NL. Of course we would need to look at all such league switches, in order to reduce the effects of random variation to a minimum.

Without being able to compare the two leagues, determining the absolute strength of each league-season would be impossible. By comparing them, the task is difficult but possible.

Bill

A quick study on league quality as used by the WARPians (WARPites?):

I looked at a few BP hitter's pages and compared EqA raw with EqA adjusted for league quality.

There is great similarity between hitters; for example, if Ted Williams in 1955 loses 6 points of EqA, then Mickey Mantle inthe same year will lose 6 or maybe 5 or 7. The reuslts are almost always within one pt.

Armed with the comforting info that the system is at least consistent within itself, I decided a smaple of 2 hitters for each league/year was enough to create a table of "BP league quality estimates from 1931 to 1960". Which follows.

What the numbers mean is that a NL player who hit .300 in 1931 is of the same quality as a player who hit .306 in the AL that year; assuming we have alreayd accounted for park facors and league offensive levels.

year AL NL
1931-10 -4
1932 -7 -1
1933-10 .0
1934 -7 .0
1935 -6 .1
1936 -7 -1
1937 .2 -1
1938 .3 .3
1939 .0 .0
1940 .4 .2
1941 .2 .1
1942 -5 .6
1943 -4 .1
1944 -9 -7
1945-14 -7
1946 .2 .0
1947 -1 .3
1948 .1 .1
1949 -1 .1
1950 -1 .0
1951 -1 -1
1952 -7 -1
1953 -9 -4
1954 -9 .0
1955 -6 .0
1956 -7 .4
1957 -7 .2
1958 -7 .4
1959 -3 .2
1960 -3 .3

conclusions from this data
NL was stronger thru 1936
AL caught up 1937 thru 1941
AL was weaker in 42 and 43
real 'war years' were only 44 and 45
small weakening effect during Korean conflict
AL thru mid-late 1950s was actually Weaker than it was in 1940.
NL strongest by late 1950s, but not by much over earlier years.

I don't buy all of this, but there is the data, and they certainly did more work to create it than I did.

Over the weekend maybe I can resurrect and post the old Cramer study from The Hidden Game to see how it compares.