Teams Overdue For A World Series Appearance

A team is overdue if the number of years since their last appearance is greater than the number of teams in their league. The table below lists all such teams as of now in no particular order. Once we get into 2012, the Indians will be 15 years from their last appearance.



Some are very overdue. Some not only have not been making it to the World Series, but they have been doing poorly otherwise, too. This may seem like alot of teams, but at the conclusion of the 1958 season, 11 of the 16 teams were overdue.

We have always had hapless teams. The Phillies went 35 years without a pennant before finally getting one in 1950 but then went another 30 years. The original Senators did not win one in their last 27 years in Washington. The St. Louis Browns went only once to the Series in over 50 years before moving to Baltimore. The White Sox went 40 years without one until 1959 and then went another 46 years.

It is probably hard to quantify "overdueness" over baseball's history to accurately assess how bad things are now. In the pre-1960 years, you could be overdue in just 8 years so it may not have felt so bad to the fans. Now it means a longer time period. Right now, it would take 7 years to clear out the back log of teams overdue and it would require all of the hapless teams to get in over this stretch (it does not seem likely).

The following table shows the teams that are at least half way to being overdue.

OPS Differential Gives Big Edge To Rangers

The Rangers hitters had an OPS of .800 during the season and their pitchers allowed a .698 OPS. So that is a .102 differential.

The comparable numbers for the Cardinals are .766-.717-.049.

The following equation gives a good estimate of winning percentage.

Pct = .5 + 1.3*OPSDIFF

That gives the Rangers a winning percentage of .633 and the Cards .564. Using the Log5 method for predicting the probability of winning by Bill James and Dallas Adams (and posted by Tangotiger)

W%(A v. B) = W%(A)*(1 - W%(B))/(W%(A)*(1 - W%(B)) + (1 - W%(A))*W%(B))

we get the Rangers having a 57% chance of winning any given game (this leaves out home field advantage).

The Rangers were even better in September, with a differenital of .298 (.916 - .618). The Cards had .125 (.807 - .682).

The Rangers, however, have a negative differential in the playoffs so far of -.017 (.764 - .781) while the Cards have .096 (.793 - .699). Combining the September differential and the playoff differential in a weighted average by games gives the Rangers a differential of .208 and the Cards .116.

Not The Year Of The Pitcher In The Playoffs

In all playoff games, the AL teams averaged 4.87 runs per game. The AL runs per game this year was 4.46 during the regular season.

The NL average so far is 4.63 (not counting tonight's game with the Cards leading 11-6 in the bottom of the 7th). If it ends up with that score, the NL average will be 4.88. If the Brewers could win 12-11 and tomorrow's game ends up 1-0, the NL average will be 4.82. The NL runs per game this year was 4.13 during the regular season.

Only 10 of the 30 games so far had both teams scoring 4 or fewer runs. Only 5 games had both teams scoring 3 or fewer runs.

Carl Yastrzemski's GDP Rate In 1967? 3%

That was by far the lowest of his career. So another reason why that season was so great. I did not see very much on this. See The Great Forgotten Season: Carl Yastrzemski, 1967 by Cody Swartz of "Bleacher Report."

Yastrzemski's only season when he had a higher AVG against lefties was 1967. He also hit especially great after August 31. He batted .417 (40 for 96). He ended August with a .3085 AVG. He slugged .760 after Aug. 31. Through that date it was .594. See Was The Left Hand Of God Responsible For The Red Sox Miracle In 1967?.

That season was also one of the most indispensable seasons ever, meaning his team really needed him to have a great year. See Indispensable Seasons Go To WAR!

The table below show's his GDPs and GDP rate for each year of his career. 1967 was much lower than any other year. I also show his SO rate for each year (using PA - IBB - SH). Data from Baseball Reference. I thought maybe if his strikeout rate had been alot higher that year it would account for the lower DP rate. But it does not look that way. The one thing Yaz did that year that he never did before was hit alot of HRs, 44. His previous high had been 20. So maybe putting the ball in the air more helped. Baseball Reference does have his FB/GB ratios for any year. But in other years when he hit 40+ HRs, the GDP rate was not so low (1969 & 1970). Maybe he was just faster that year.

How many runs did he save by hitting into fewer DPs? Averaging his rate over 1966 and 1968, I get about 9 DPs saved. What was it worth to not hit into a DP? Using Tangotiger's Run Expectancy Matrix, 1950-2010, my guess is that it would be worth between .122 and .198 runs in each case. Using the 1950-68 matrix, with a man on 1st and 2 outs, the run expectancy is .264. With 2 outs and none on, it is .066. So if there is a man on 1st and no outs and Yaz strike's out or beats the throw to first, you save .198 runs. Doing something similar with a man on 1st and 1 out gets us .122 runs saved.

The average of those two is .16 and over 9 DPs avoided, it is just 1.44 runs. That may not be much but when the Red Sox and Twins played the last game of the season tied for first, the lower DP total might have mattered.

If I used run values from the 1999 Big Bad Baseball Annual, a GDP was -.37 runs and other outs were worth -.09. So not hitting into a DP and making another kind of out saves .28 runs for a total of 2.52 runs over 9 DPs avoided.

Now maybe Yaz got hits instead of hitting into DPs. But the two other years when he hit over .320 he had about a 10% GDP rate, still much higher. So we can't simply say he hit better that year and that caused the lower GDP rate.

"Data guys" More Important In Business Due To "Moneyball"

See When Data Guys Triumph by CADE MASSEY and BOB TEDESCHI, NY Times business section, 10-2-11.

Oakland A's general manager Billy Beane and author Bill James are entrepreneurs who created a whole new way of running baseball teams based on statistics and this creative spirit is starting to have an impact in the business world.

The Nobel prize winning physicist Richard Feynman said that "science is the belief in the ignorance of the experts." By challenging the experts in baseball, Beane and James were true scientists, asking questions and looking at data in new ways. Excerpts:

"JOSHUA MILBERG has plenty of business cred: an M.B.A. from Yale, experience in the mayor’s office in Chicago, a job as a vice president for an energy consulting firm. But all of that, Mr. Milberg says, matters less than his reputation as “the data guy” — someone who can offer insights through statistical analysis. And for that, he and a growing number of young executives can credit none other than “Moneyball: The Art of Winning an Unfair Game,” by Michael Lewis."

The book "...examines how the Oakland Athletics achieved an amazing winning streak while having the smallest player payroll in Major League Baseball. (Short answer: creative use of data.)

These managers are savvier with data and more welcomed in business circles in part because of the book."

"At its heart, of course, “Moneyball” isn’t about baseball. It’s not even about statistics. Rather, it’s about challenging conventional wisdom with data."

"This evangelism has created opportunities for the analytically minded."

The article calls this work "creative empiricism."

"But “Moneyball” dramatized the principles behind these forces: a reliance on data to exploit inefficiencies, allocate resources and challenge conventional wisdom — and thus broadened their appeal.

“Moneyball” traces Billy Beane’s use of unorthodox analytics to the work of Bill James. Working as a baseball outsider, Mr. James began self-publishing his analysis and commentary in 1977 and built a passionate following."

"Once people see the value of a batter’s O.P.S. — on-base plus slugging percentage, a key measure in the book — it’s a short step to applying similar principles in their own organizations."

"Generation Moneyball isn’t yet in charge. But as the Nobel laureate Max Planck once said, “A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.”"

OPS vs. 1.8*OBP + SLG

And people say I shy away from the controversial topics.

This analysis is at the team level. Let's start with runs scored. The following regression equation shows the relationship between team runs per game and team OPS:

R/G = 13.02*OPS - 5.04

I used all teams from 1996-2009. For OBP I used (H + BB)/(AB + BB). The r-squared was .897 and the standard error was .1608. That works out to 26.05 runs per season.

Now when I used 1.8*OBP + SLG (call it adjusted OPS or ADJOPS) instead of OPS, the equation was

R/G = 10.26*ADJOPS - 5.68

The r-squared was .907 and the standard error was .153. That works out to 24.77 runs per season. So using 1.8*OBP + SLG is a bit better. The standard error is 5% lower. It is also 1.28 runs lower. That would be worth about a tenth of a win.

I have also used a team's OPS differential to predict winning percentage. That is, its hitting OPS - the OPS it allows its opponents. Here is the regression equation:

Pct = .5 + 1.26*OPSDIFF

The r-squared was .798 and the standard error was .0311. That works out to 5.04 wins per season. I used all teams from 1989-2002.

Now the same analysis with the differential using 1.8*OBP + SLG (call it the ADJOPS differential):

Pct = .5 + .986*ADJOPSDIFF

The r-squared was .815 and the standard error was .0298. That works out to 4.83 wins per season. So again, as in the analysis of runs scored, 1.8*OBP + SLG does just a bit better.

One reason why 1.8*OBP + SLG only does slightly better is probably that the range of OBP and SLG across teams is not that great. But for individual players, the range varies much more. So it might make more sense to use 1.8*OBP + SLG instead of OPS in those cases.

Do Diamondbacks have stats to match Brewers stars?

Click here to read the AP article by Chris Jenkins. He writes:

"The Diamondbacks might not have the Brewers’ marquee names. But the numbers, and the results, show two teams that are surprisingly similar going into Saturday’s Game 1 of the NL division series."

This sounds like an interesting question yet very few numbers are presented in the article. Actually no numbers that statistically compare the two teams. It turns out, that by luck, the Diamondbacks over achieved with runners on base, a trend that no team can keep up.

It looks like the Brewers are much better. Their hitters had an OPS of .750 while their pitchers allowed a .689. That gives them a differential of .061.

The Diamondbacks hitters had an OPS of .736 while their pitchers allowed a .725 OPS. That gives them a differential of .011. Well below the Brewers.

Based on some regression analysis I have done, we can project winning pct with the following equation:

Pct = .5 + 1.3*OPSDIFF

This gives the Brewers a pct of .579 or 93.85 wins. The Diamondbacks get .514 or about 83.32 wins. This seems like a very big difference.

Yet the Brewers actually only won 2 more games (96 vs. 94). And the Brewers runs differential (721 - 638 = 83) is only slightly higher than the Diamondbacks run differential of 69 (731 - 662).

What allowed the Diamondbacks to match the Brewers, at least on the surface? Some very good luck. They over achieved with runners on base. The Diamondback hitters had an OPS of .770 with runners on base (ROB) while their pitchers allowed .731. That gives them a differential of .039.

The Brewer hitters had an OPS with ROB of .745 while their pitchers allowed .719 for a differential of .026.

This seems to be something in favor of the Diamondbacks, but it really isn't.

Doing better with runners on base will improve your chances of winning. You will score more runs than expected and give up fewer runs than expected. Yet, in the long-run, individual players and pitchers (and teams) end up performing about the same in clutch situations (like ROB) as they do overall. Even the best clutch hitters and pitchers do just a little bit better in any clutch situation than they normally do given a large enough number of games.

For the Diamondbacks to to even look like they are as good as the Brewers, they had to be lucky. We cannot expect them to continue to over achieve so much with runners on base.

September Second Best Month For OPS

Each league had its second highest monthly OPS. The numbers for each league are in the table below. The NL's scoring was not that great but the AL had its best month.

Did Branch Rickey Subscribe To The Same S**t As Billy Beane And Bill James?

I am reposting this entry from April 2010 since the Moneyball movie just came out.

Some sportswriters still like to make fun of the statheads or sabermetricians who never played the game and still live in their mom's basement. But to those writers I say "read the 1954 LIFE magazine article where Branch Rickey discusses some very modern looking formulas." This article is online and was called GOODBY TO SOME OLD BASEBALL IDEAS: The 'Brain' of the game unveils formula that statistically disproves cherished myths and demonstrates what really wins. Some of the new stats he proposed were "on-base average" and "isolated power." The article even shows many formulas, some of which are complex.

Rickey is in the Hall of Fame for his work as an executive. But he also played and managed. I think if you ridicule statheads, you would probably ridicule Rickey. Here is the introductory paragraph:

"Baseball people generally are allergic to new ideas. We are slow to change. For 51 years I have judged baseball by personal observation, by considered opinion and by accepted statistical methods. But recently I have come upon a device for measuring baseball which has compelled me to put different values on some of my oldest and most cherished theories. It reveals some new and startling truths about the nature of the game. It is a means of gauging with a high degree of accuracy important factors which contribute to winning and losing baseball games. It is most disconcerting and at the same time the most constructive thing to come into baseball in my memory."

That is followed by a fairly complex formula. Then Rickey asks "Can this bizarre mathematical device be put to any practical use?" And his answer? "It can indeed! It can be applied to any major league club for any season or part of a season to diagnose points of weakness and strength."

So Rickey, perhaps one of the most influential men ever invovled in baseball, saw the need for new and complex ways of analyzing the game. How can some writers, and some GMs, not see this today?

But what about intangibles? Rickey says:

"But somehow baseball's intangibles balance out. They reflect themselves in other ways. Over an entire season, or many seasons, individuals and teams build an accumulation of mathematical constants. A man can work with them. He can measure results and establish values. He can then construct a formula which expresses something tangible, and that is why this formula was devised."

After compiling many stats and data, what did Rickey do? "We took the figures to mathematicians at a famous research institute. Did they know baseball? No, but that was not essential."

Did RBIs' figure in Rickey's formula? No. "As a statistic, RBIs were not only misleading but dishonest."

There is much more to read in this article that is of interest. Near the end of the article he mentions getting his scouts involved in finding players with power, guys who will improve the ability of his team (the Pirates) to bring runners home. But that is based on the formula. Imagine that. Rickey was going to tell his scouts what to look for based on a formula.

If you have never read the article, I think you are in for a treat since it is so well written and it was written so long ago.

Has Mariano Rivera statistically separated himself from his peers?

That is the issue raised by an article in yesterday's NY Times Mr. Young, Mr. Ryan, Mr. Rivera Will Be Joining You By DAVE ANDERSON.

He compares Rivera to Cy Young and Nolan Ryan. Young won 511 games and the next highest is Walter Johnson at 417. Ryan struck out 5,714 batters, 839 more than Randy Johnson. Does Rivera dominate his peers in a similar way?

It is hard to argue against his 0.71 ERA in 139 post-season IP. I doubt any other closer can come close to that. Probably no other has had a chance to pitch so much in the playoffs. But the article offered no comparisons. No other pitcher's post-season performance was discussed.

Rivera now has 603 saves and the only other guy with 500+ saves is Trevor Hoffman with 601. So let's see how those two compare in their regular season stats (Hoffman only had 13 post-season IP). The table below summarizes some of their stats.



Their save percentages are almost identical. I thought that maybe Rivera got into tougher situations because he has such low HR% and his ERA is so much better than Hoffman's (2.22 vs. 2.87) that it seemed like maybe he came in when the score was closer. But they each have about the same average leverage index. The 1.92 for Hoffman, for example, indicates that his typical game had nearly twice the pressure as average in terms of inning and score.

So these two guys pitched a similar number of innings under the same pressure and were equally successful in what they were asked to do. Now maybe Rivera was in more pennant races or playoff chases but the Yankees usually made it in fairly easily. Maybe the competition was a little tougher in the AL.

ERA+ is adjusted for league average and park effects. Rivera's means that his ERA so adjusted is a little less than half the league average while Hoffman is about 30% lower. So big edge for Rivera (another closer, Billy Wagner, in about 900 IP had a 187, not too far from Rivera). Wagner had a career save % of 86%.

They are close in WHIP. FIP or fielding independent ERA takes walks, HBP, SO, and HR into account (with IBBs taken out). Hoffman is not too far off. This comes from Fangraphs and I don't think it is park adjusted. A rough estimate is that Hoffman's parks were about 7.2% better than average for pitchers while for Rivera just about average. If I raised Hoffman's FIP ERA by half of that 7.2% I get 3.19.

When I do walk% and SO/BB ratio, IBBs are taken out and HBP are in. IBBs are also taken out when doing HR%. This edge for Rivera seems very large. Maybe it is even bigger being a righty in Yankee Stadium and other teams would have tended to send lefties up to face him.

Rivera is not too far ahead of Hoffman in AVG and OBP allowed. But the edge in SLG seems big, probably due to the low HR%. The edge is even bigger in road games.

One other closer, Dennis Eckersley is worth looking at. I found his best 6 seasons in FIP ERA and the simple average of them was 2.13. For Rivera it was 2.15. If I park adjust Eckersley here, he goes up to 2.19. Still not too far from Rivera. But that has to be adjusted for the league average. Those years for Eck around 1987-93. It looks like the league average has been about .44 higher in those years than it was over Rivera's years. Rivera's FIP ERA is about .474 of the league average while for Eck it is .535. If Eck pitched in those years of Rivera he would get 2.42. Not too far off (also recall that for Rivera, those are his best six years and but I just used his entire career as an approximation). Eckersely came to the closer well after the age of 30 (and maybe before that we did not really have closers). Eckersley had a career save % of 85%.

What is probably the amazing thing is for how long Rivera has been consistently great. He is almost 42 and is having another outstanding season.

Update: David Pinto points out that Rivera had 116 "long saves" (4 outs or more) while Hoffman only had 55. I left a response.

Bill James vs. Richard Feynman

Cage match. Who would win? I think Bill James would have the size advantage, but I really don't know for sure.

Anyway, Nobel prize winning physicist Richard Feynman said “Science is the belief in the ignorance of the experts.” If that is true, then I think Bill James must be a great scientist.

I thought of this watching "Moneyball" today. It was good to see them mention James and show his picture. It is very entertaining, enough so that, in my opinion, people with just a passing knowledge of baseball can enjoy it.

I don't have anything insightful to say about it. Joe Posnanski has written two great articles.

Moneyball The Movie

Moneyball and the Ballad of Bill James

He gives the movie 3 stars out of 5. I think it is at least a 4. So far on IMDB it has an 8.0 rating out of 10. But that is in only 729 votes. It will probably come down, but my guess is that it will end up with at least a 7.0.

Update 9-25: The IMDB rating is now at 8.2 with 1395 votes.

Update 9-26: Art Howe isn’t happy about his portrayal in ‘Moneyball’

Update 9-26: The IMDB rating is now at 8.3 with 2212 votes.

Update 9-27: The IMDB rating is now at 8.3 with 2898 votes.

Update 9-30: The IMDB rating is now at 8.2 with 3599 votes.

Update 10-1: The IMDB rating is now at 8.2 with 3845 votes.

Update 10-2: The IMDB rating is now at 8.2 with 4382 votes.

Update 10-10: The IMDB rating is now at 8.2 with 6113 votes.

Verlander And Kershaw Are Leading All Three Pitching Triple Crown Categories

ERA
1. J. Verlander DET 2.29
2. J. Weaver LAA 2.41
3. J. Beckett BOS 2.50

Wins
1. J. Verlander DET 24
2. C. Sabathia NYY 19
3. J. Weaver LAA 18

Strikeouts
1. J. Verlander DET 244
2. C. Sabathia NYY 224
3. F. Hernandez SEA 220

ERA
1. C. Kershaw LAD 2.27
2. J. Cueto CIN 2.31
3. C. Lee PHI 2.38

Wins
1. C. Kershaw LAD 20
2. I. Kennedy ARI 20
3. R. Halladay PHI 18

Strikeouts
1. C. Kershaw LAD 242
2. C. Lee PHI 232
3. T. Lincecum SF 217

Click here to see all of the pitchers who won the triple crown at Baseball Almanac.

Only twice has a pitcher in both leagues won the pitching triple crown in the same year. 1918, Walter Johnson & Hippo Vaughn and 1924, Walter Johnson & Dazzy Vance.

Best/Worst Month for a Team's Pitchers (and the 1969 Mets allowed only 3 HRs in September)

Tom Ruane of Retrosheet looked into this after I asked him about it. Here is the link:

Best/Worst Month for a Team's Pitchers

Tom mentions "Since 1935, only the 1954 Orioles had a lower HRA rate than those 1969 Mets." Tom also looks at the best months in hits allowed and strikeouts.

Prior to Sept. that year, the Mets' HR rate was .023842 (using batters faced - IBBs - SH). In Sept. it was .002841. So the Sept. rate was only about 1/8 of what it had been before that year.

Using the cumulative binomial distribution and assuming the following:

Number of occurrences: 3
Trials: 1056
Rate: .023845

The probability of getting 3 or fewer HRs was about 1 in 36 million (I welcome any comments or corrections on this). Just cutting the HR rate in half or less that month (about 13 HRs allowed) has chance of only 1 in 183. 6 HRs or less is 1 in 225,000.

The Mets did allow 3 HRs in the last two days of the season in Oct. But by then they had clinched the division. They allowed no HRs from Aug. 30 to Sept. 18 in a total of 22 games (that is what a quick check of Retrosheet shows).

On Sept. 19, game 2, Stargell of Pit. hit a 2-run shot in an 8-0 Pirate victory. But by then, the Mets already had a 5 game lead with 13 games to play (the Cubs had 11 left).

On Sept. 21, game 1, Pagan of Pit. hit a solo shot in the 4th inning. It made the score 4-3 but the Mets won 5-3

On Sept. 21, game 2, Stargell hit a solo shot in the 4th inning to make it 4-1 but the Mets won 6-1.

It seems like none of these HRs was significant. Only one even had a man on.

The Mets also allowed only about 31% of their HRs for the whole year with runners on while the rest of the league was about 43%. The Mets turned 30 DPs in Sept. Their next highest month was 25 and the next after that was 18. Don Cardwell had an ERA under 1.00 in Sept. It was .039 in 23 IP. It was 3.25 going into Sept.

Report On Hitting So Far In September

The table below shows some basic stats for each month in both leagues. Hard to sum up September so far. The AL so far has had a big drop in OPS but runs per game is up. The NL is about the same as it was in August.

Can Justin Verlander Win The Pitching Triple Crown?

He now leads the AL in wins, strikeouts and ERA.

Wins
1. J. Verlander DET 21
2. C. Sabathia NYY 19
3. J. Weaver LAA 16

Strikeouts
1. J. Verlander DET 224
2. C. Sabathia NYY 211
3. F. Hernandez SEA 204

ERA
1. J. Verlander DET 2.34
2. J. Weaver LAA 2.49
3. J. Beckett BOS 2.54

Weaver has seen his ERA rise quite a bit over his last two starts. After Aug. 24, Weaver's ERA was 2.03. He gave up 13 earned runs (ER) in 11 IP over those two starts. In fact, after his Aug. 5 shutout of Seattle, his ERA was 1.78. For all of August, his ERA was 4.28. He also gave up 8 ER in 4.2 IP against the Blue Jays on Aug. 13. Before the All-Star break his ERA was 1.86. Since then it has been 3.82.

Verlander seems to have been a little more steady. His ERA before the All-Star break was 2.15. Since then it is 2.75. Since June 15, his ERA has been no lower than 2.15 and no higher than 2.38. Verlander has only once given up more than 4 ER (a 6 ER game) and has always pitched at least 6 innings in every start. He has only given up 4 ER 3 times and has not given up exactly 5 runs even once. 22 of his 30 starts had both 3 ER or less and 7 IP or more.

Click here to see all of the pitchers who won the triple crown at Baseball Almanac

Hitting And Scoring Picked Up In August

So far this year, the AL is averaging 4.41 runs per game with an AVG-OBP-SLG of .257-.322-.405 and an OPS of .727. 1992 was the last year the AL had a lower runs per game with 4.32. Same for OPS, .713. Last year the AL R/G and OPS were 4.45 and .734. So not too big of a drop off. Of course, things can change with Sept.

So far this year, the NL is averaging 4.15 runs per game with an AVG-OBP-SLG of .253-.319-.392 and an OPS of .710. The last time the NL had a runs per game lower was in 1992 at 3.88. That was also the last time they had a lower OPS, at .684. Last year the NL R/G and OPS were 4.33 and .723.

The table below shows how each league has done, month-by-month, this year. April includes March data. Both leagues had their best power month measured by SLG and ISO.

Players Who Led The League In Triples And Home Runs At Least Once Each

With Curtis Granderson currently tied for the AL lead in HRs while leading in triples, I thought I would find all of the players who had led the league in both in the same year as well as the others who did it but not in the same year. Some guys led one league in HRs one year and another league in 3Bs another year, like Dick Allen. They are all below, linked to Baseball Reference. If I missed anybody, let me know. They are in no order except the guys who did it in the same year are listed first. There are alot of Hall of Famers here. There are 33 in all.

Harry Stovey (twice in the same year)
Tip O'Neill (once in the same year and lead in 2Bs, too)
Harry Lumley (once in the same year)
Jim Bottomley (once in the same year)
Tommy Leach (once in the same year)
Willie Mays (once in the same year)
Mickey Mantle (once in the same year)
Jim Rice (once in the same year)
Roger Connor
John Reilly
Bid McPhee
Oyster Burns
Sam Crawford
Harry Davis
Home Run Baker
Johnny Mize
Ty Cobb
Lou Gehrig
Rogers Hornsby
Buck Freeman
Dan Brouthers
Dick Allen
Ed Delahanty
Joe DiMaggio
Sam Thompson
Wally Pipp
Frank Schulte
Buck Ewing
Jim O'Rourke
Jimmy Sheckard
Joe Medwick
Ryne Sandberg
Walt Wilmot

The record for most consecutive games versus over and under .500 teams

A guest post by Tom Ruane of SABR and Retrosheet

I thought it might be interesting to look at four groups:

1) under .400,
2) under .500,
3) over .500 and
4) over .600.

Here's what I found:

1) Starting on August 11, 1885, the Chicago White Stockings
played a record 23 straight games against opponents with
a winning percentage under .400. During the streak, they
played only Buffalo, Detroit and St. Louis. It ended when
they faced Boston (which entered the game with a
none-too-impressive winning percentage of .406). Chicago
went 20-2-1 during the streak.

The longest such streak since 1900 is nineteen and it was
done four times:

2) The Chicago White Sox played 51 straight games against
losing teams from May 27 to July 10, 1966. The streak ended
when they hosted the third-place Indians in the first game
following the All-Star break. Ironically, the Sox went only
22-28-1 while playing losing teams, and 45-32 afterwards.
No teams are close to their streak, the second longest
being a run of forty straight games by the San Francisco
Giants in 1986. It ran from July 3rd to August 17th and,
like the White Sox, the Giants had a losing mark (19-21)
while it lasted.

3) The top five teams with the most consecutive games
played against winning teams:

At the end of the streak by the 1916 Senators, the only
other team in the AL with a losing record was the 27-94
Philadelphia Athletics. And the three streaks from 1908 are
due to the practice of scheduling long road and home trips
between the eastern and western teams. In 1908, all of the
western teams had winning records.

4) The longest stretch of games against teams with a
winning percentage higher than .600 was 27 by the
Philadelphia Quakers in 1884. From May 20th to June 19th,
they went 6-21 against Boston, Providence and New York.
Entering the games of May 20th, those three teams had a
combined record of 37-5. Philadephia had been in fourth
place at the start but was in seventh place at the end of
the run.

The record since 1900 is 21, by the 1998 Tigers from
April 3rd (which was the first game of the second series
of the year) to 30th. Given how early in the season
it was, a few more wins here and there might have
short-circuited the streak, but Detroit went 5-16 in the
games.

Hitting Has Picked Up A Bit So Far In August

The table below shows the OPS and runs per game for each league by month for 2011.

Should Thurman Munson Be In The Hall Of Fame?

I'm looking at this because it was discussed at Baseball Think Factory. That discussion was inspired by a new website that is trying to get Munson in called VoteThurmanIn.com.

Munson is 14th in career WAR among catchers. Here is the top 22 from Baseball Reference (I went to 22 so I could include Campanella). It also shows their best three consecutive seasons (which I just eyeballed to find) and the number of times they finished in the top 5 and 10. These guys played at least 50% of their games at catcher.



Now Munson is only 240th among position players in career WAR. That probably is not enough for the Hall. But catchers don't have the longevity of other players, so being in the top 15 is impressive. If he had not died at age 32 in 1979, he might have made the top 10. He was on a pace to get about 3.6 WAR in 1979. He also had over 3 the previous year.

His best 3 straight years is not near the elite like Bench, Carter, Piazza or Mauer (does he have the record for best 3 straight by a catcher?-although some games at DH may have helped). But Munson's best 3 straight years beat Lombardi, Bresnahan and Hartnett. He also has more top 10 finishes than Lombardi and Hartnett.

Tenace is ahead of him in career WAR but only about 58% of Tenace's innings were at catcher (Munson is about 97%).

Munson also is 144th in MVP shares (at 1.50). That is good considering that catchers don't do that great in the voting. See my post called MVP Awards And Award Shares By Position. So his contemporary observers liked him. He also won three Gold Gloves.

Fangraphs has him at 21st in career WAR among catchers. But some of the guys ahead of him played less than half their games at catcher: King Kelly, Joe Torre, Brian Downing, Buck Ewing. Tenace and Bresnahan are both ahead of him, too. Bresnahan played about 70% of his games at catcher (this all points out something problematic with the position regarding the Hall of Fame-many guys who played there got moved to other positions). And again, don't forget that Munson died young. He could have moved up in the rankings.

Just what I have done so far is probably not enough. But I think we should be looking at him as a serious candidate.

July Hitting Picked Up A Bit In The AL, Still Sluggish In the NL

He are the monthly OPS figures for the AL starting in April:

April .713
May .720
June .719
July .731

For the whole season, it is .721. But just last year, for the whole season, it was .734. July should be one of the strongest months. From 1994-2009, the AL had an OPS of at least .750 every year with a high of .795 in 1996.

He are the monthly OPS figures for the NL starting in April:

April .709
May .702
June .699
July .709

For the whole season, it is .705. In 2009, for the whole season, it was .739. From 1994-2008, the NL had an OPS of at least .740 every year with a high of .773 in 1999.

Is Ryan Howard A Clutch Homerun Hitter?

This was inspired by a discussion at Baseball Think Factory about an article at Fangraphs called Ryan Howard and the RBI by Steve Slowinski (there is no shortage of great Polish baseball bloggers).

Some people say that Howard is a good "RBI guy" and that he is paid to drive in runs so maybe his overall stats and/or his OBP don't matter that much. But a good "RBI guy" would tend to hit better with runners on. In my opinion that means a higher AVG with runners in scoring position (RISP) than he normally gets and a higher SLG with runners on base (ROB) than normal

But this year Howard is only 47th in SLG (.463) with runners on base in all of baseball with guys with 150+ PA in that situation. Teixeira leads with .667.

Howard is 20th in AVG (.304) with runners in scoring position this year in all of baseball with guys with 100+ PA in that situation. Votto leads with .424.

So overall, nothing special on Howard's part.

But somehow Howard over his career has managed to hit better with ROB and RISP. His AVG/SLG with none on is .266/.528. With ROB it is .285/.593 and .281/.561 with RISP. The one difference that seems pretty big is the SLG with ROB.

From 1991-2000, ROB SLG was .422 in all of baseball and .411 with none on. Since 2006, it looks like SLG with ROB is about .009 higher than with none on. So Howard is way above that being .063 higher. Some of that might be because he is a lefty. But whether it is luck or some real clutch talent is hard to say.

So I thought I would try a statistical test on his HR% with none on (NONE) vs. his HR% with ROB. Here we calculate something called a "Z-score." To be significant at the 5% level (meaning there is less than a 5% chance of getting the difference between the two HR%s) the Z-score has to be at least 1.96 (plus or minus, since a guy could do worse with ROB, the clutch situation I am looking at). HR% will be highly correlated with SLG (also, it does not look like Howard hits very many more 2Bs or 3Bs with ROB than NONE). Some technical details on this are below.

Howard's HR% with NONE in his career is 6.857% while with ROB it is 8.221%. That may not seem like a big difference, but the ROB HR% is 19.9% higher (8.221/6.857 = 1.199). The question is whether or not it is statistically significant. This is where the Z-score comes in.

The Z-score takes into account the number of ABs and HR% in each situation (ROB, NONE). It also takes into account the normal major league difference (I used +.0009, the approximate difference from 2007-10). This is important because if the normal HR% was .01364, then Howard would not be clutch at all since this is the difference between his two percentages (.08221 - .06857). When I did this calculation for Howard, I got a Z-score of 1.655. That is significant at about the 10% level. I guess I would like to see it at the 5% level before considering that he is clutch in hitting HRs with ROB. But even if he had reached 1.96 or more in his Z-score, it is possible he got there by luck and not skill because 2.5% of the hitters will have a Z-score of +1.96 or more.

Z = (CLUTCH AVG – NONCLUTCH AVG + EXPECTED DIFFERENCE)/SD

NORMAL DIFFERENCE FOR CL = +.0009 (which is added in this case)

SD = STANDARD DEVIATION =

{[CLUTCH AVG*(1-CLUTCH AVG)]/CLUTCH AB + [NONCLUTCHAVG*(1-NONCLUTCH AVG)]/NONCLUTCH AB}

(FROM PETE PALMER, BY THE NUMBERS 3/90. He called it a “pooled” standard deviation)

In a normal distribution, 5% of the players would have a Z-score of at least +1.96 or less than –1.96.

Ubaldo Jimenez Home And Away, 2009-2011

I guess he is the subject of trade rumors. Here are some of his numbers

Home:

IP-265.67
H-254
HR-20
BB-103
SO-233
ERA-3.79
H/9IP-8.60

Away:

IP-291
H-201
HR-13
BB-119
SO-287
ERA-2.94
H/9IP-6.22

So his ERA has been about .85 better on the road. But, of course, home ERA is usually better. Here are the differentials the last three years for all of baseball: .46-.54-.24.

Not all no-decisions are created equal: Evaluating a little-examined pseudo statistic

That was the title of Gilbert Martinez's presentation at the recent SABR convention. Gilbert is president of the Rogers Hornsby Chapter of SABR in Austin, TX.

Click here to get the power point slides. It has alot of neat graphs.

Here is the abstract:

"In 2009, two pitchers recorded 16 no-decisions. The Houston Astros’ Roy Oswalt set a franchise record for no-decisions and was 8-6 in 30 starts. The L.A. Dodgers’ Randy Wolf was 11-7 in 34 starts.

Research shows that 2011 Hall of Fame Inductee Bert Blyleven holds the record for most no-decisions in a season with 20 after a 12-5 record in 37 starts with the Pittsburgh Pirates in 1979.

While Oswalt and Wolf didn’t set a record, they were among the most in a single season and they did receive some attention by the media and fans. Little analysis has been done to understand the nature of these no-decisions. Statistics abound in baseball, and especially with pitchers. Statistics capture games started, wins, losses, saves, earned run average, pitch counts, walks, hit batsmen, ground-ball outs, fly-ball outs, innings pitched, homeruns given up, strikeouts per nine innings, and so on. This project will focus on starting pitchers and no-decisions recorded as a result of starting a game.

The purpose of this project is twofold: 1) to evaluate the most no-decisions by a starting pitcher in a single season and in a career and 2) to determine which pitchers with the most no-decisions were unlucky or lucky.

A pitcher would be considered unlucky if he leaves the game with a lead, only to watch his team’s bullpen lose the game in the late innings. This would be considered a positive no-decision (positive because it suggests an effective pitcher). Likewise, a lucky pitcher would be one who leaves the game with his team trailing, only to be bailed out by a potent offense, thereby taking him off the hook. This would be considered a negative no-decision. If he leaves with the game tied, this would be a neutral no-decision.

These no-decisions are not equal, and some pitchers are more valuable to their teams than others. In other words, some pitchers saddled with numerous no-decisions but who have more positive no-decisions than negative no-decisions are more worthy of our sympathy than those with more negative no-decisions compared to positive no-decisions.

Initial review of the literature shows little on this subject, so it appears this research project would contribute to our understanding of lucky and unlucky pitchers in the context of no-decisions. In fact, this statistic is not readily recorded on Baseball-Reference.com.

The methodology includes running a formula in a pitchers database to determine no-decisions: (Games started) minus (wins + losses) = no-decisions. However, those results would need further review to eliminate no-decisions that come from relief appearances. The remaining results would be analyzed to determine the circumstances in which the pitcher was given the no-decision: Was his team leading or losing when he was removed? Was he lucky in receiving the no-decision or was he unlucky?

The result would be the number of positive, negative and neutral no-decisions, shedding new light on the pitcher’s effectiveness."

Has Jake Peavy Had Bad Luck This Year?

His ERA is 5.19. The league average is 3.87. Yet here are his AVG-OBP-SLG allowed

.262-.281-.341

The league averages are .252-.319-.392

So he appears to be much better than the league average in OBP and SLG allowed.

He is getting hit pretty hard with runners on base (ROB). Here are his AVG-OBP-SLG allowed in those cases

.344-.342-.439

Now with runners in scoring position (RISP)

.370-.347-.508

It is not the case that he can't pitch in the clutch. For his entire career, his AVG-OBP-SLG are .233-.271-.336. With ROB, they are .235-.275-.313 and with RISP they are .240-.283-.303.

Fangraphs shows his fielding independent ERA at 3.06. That is a stat that tries to predict a pitcher's ERA just based on strikeouts, walks and HRs. His xFIP ERA is 3.49. That makes a further correction by giving all pitchers the same HR rate on flyballs (or something like that). They have an even more sophisticated stat called SIERA which projects him to have 3.57. Anyway you look at it, his actual ERA of 5.19 is very unlucky.

Pitchers Duels That Turned Into Slugfests (and Vice Versa)

This is a guest post by Tom Ruane, based on a post to the SABR list.

While watching the two teams fail to score for most of the evening
during the recent SABR outing to Dodger Stadium, I got to wondering
about the highest scoring games that began with scoreless inning
streaks. Here is the list since 1918:



And here is the flipside, the most runs scored in a game that ended
with the longest scoreless streak:



Tom Ruane, a computer programmer in Poughkeepsie, N.Y., is a member of Retrosheet's board of directors. He has published articles in "The Baseball Research Journal" and "By The Numbers." He won SABR's highest honor, the Bob Davids Award, in 2009.

What Is Konerko Doing Differently? His OPS+ Is Up, His Strikeout Rate Is Down And So Is His GDP Rate

The table below shows these stats over the course of his career. Data from Baseball Reference.


These last two years his OPS+ has been well above anything he ever did before. He has his lowest strikeout rate in 8 years and his lowest GDP rate in 6 years (for strikeout rate it was K/PA with IBBs taken out-GDP rate is GDPs divided by opportunitites). He his making more contact which should make more GDPs a possibility but he is avoiding them more than in the past (see what I say below as to how his low 2005 GDP rate is another example of how lucky the Sox were that year).

The chart below shows Konerko's OPS+ over time.



A regression with OPS+ as the dependent variable and year as the independent variable yields an r-squared of .4 and the trend line is positive. He did not peak before 30 like most guys and then trend downwards

Now for the strikeout rate and the GDP rate.



Except for that wild fluctuation in the middle of his career, his GDP rate seems to be trending downward. He has always been slow but his GDP rate is not rising as he ages.

I think it is interesting that his GDP rate took such a big dip in 2005. He only grounded into 9 double plays that year. The year before it was 23 and the next year it was 25. Hitting into 10-15 fewer DPs must have really helped the Sox that year. This may be another way they were lucky that year. The Sox had to go down to the last week of the season before they clinched a playoff spot. It was not a sure thing. They beat their main competitor, the Indians something like 14 out of 19 that year and won a bunch of 1-run games that year against them. Konerko not hitting into DPs must have helped quite a bit. Click here to read about a bunch of other ways the Sox were lucky that year that I wrote about. For one, they got great years out of relievers Politte and Cotts who did not do much before or after that season.

All-Star Game Oddity?

I wonder if this is not that strange. The first 3 NL pitchers used in the game are former ALers (Halladay, Lee, Clippard). The first 4 hits by the AL were by former NLers (Adrian Gonzalez, Bautista, Josh Hamilton, and Adrian Beltre). The first two hits by the NL were by former ALers (Beltran and Berkman).

With free agency, maybe something like this has happened before. Here are the former NLers who played on the AL team:

Adrian Gonzalez
Miguel Cabrera
Jose Bautista
Carlos Quentin
Josh Hamilton
Adrian Beltre
Paul Konerko
Chris Perez

Here are the former ALers who played on the NL team:

Brandon Phillips
Carlos Beltran
Lance Berkman
Matt Holliday
Scott Rolen
Roy Halladay
Cliff Lee
Tyler Clippard
Jair Jurrjens

If It's The Year Of The Pitcher It Is Even More The Year Of The Phillies Pitcher

You might have heard of these guys. Halladay. Hamels. Lee. Here is where they rank in WAR among NL pitchers this year:

1. Halladay (PHI) 4.9
2. Hamels (PHI) 4.4
3. Jurrjens (ATL) 4.2
4. Lee (PHI) 3.8
5. Kershaw (LAD) 3.2
Chacin (COL) 3.2
7. Cueto (CIN) 2.9
8. Cain (SFG) 2.8
Vogelsong (SFG) 2.8
Kennedy (ARI) 2.8
Hanson (ATL) 2.8

(data from Baseball Reference).

But even more impressive is that these three are in the top 5 of all players in the NL:

1. Kemp (LAD) 5.7
2. McCutchen (PIT) 5.1
3. Halladay (PHI) 4.6
4. Hamels (PHI) 4.5
5. Lee (PHI) 4.3
6. Braun (MIL) 4.2
7. Reyes (NYM) 4.1
8. Jurrjens (ATL) 3.9
9. Votto (CIN) 3.7
10. Kershaw (LAD) 3.6

The last NL team to have 3 pitchers in the top 5 in WAR among all players was the 1925 Reds. (Sean Forman found and sent me the list of all teams that had 3 or more in the top 10 just among pitchers and I went through those teams to see how they did among all players). Going through Baseball Reference year by year, it seems like 3 pitchers from one team in the top 10 in WAR among all players is very rare.

The 1966 Indians and the 1942 Tigers each had 5 in the top 10 among pitchers but none among all players.

The table below shows where these three Phillies pitchers rank in the NL in key stats so far this year.



Lee's 32nd in HR per 9 IP is in the top half of the 65 pitchers with 80+ IP. He gives up .79 HR per 9 IP while the league average is .877. Also note that the Phillies park gives up about 4% more HRs than average over the years 2008-10 (from the Bill James Handbook).

The art of fiction is dead-Again

Derek Jeter got his 3000th hit today, only the 28th player to do so. It was a HR, at home, on what looked like a beautiful afternoon in NY, 84 degrees according to Yahoo Sports. He also went 5-for-5, the first player ever to do so in the game he got his 3000th hit (according to mlb.com). Then he drove in the go-ahead and what proved to be winning run in the 8th inning. And it was against one of the other contenders in the AL East, the Tampa Rays.

Here is what the great sports writer Red Smith said about Bobby Thomson's pennant winning HR in 1951:

"Now it is done. Now the story ends. And there is no way to tell it. The art of fiction is dead. Reality has strangled invention. Only the utterly impossible, the inexpressibly fantastic, can ever be plausible again"

See Red Smith on Baseball at the excellent Baseball Almanac site.

Angels Call Up Mike Trout

Alot of people are mentioning this on blogs. David Pinto mentioned that he is right up there with Bryce Harper as the top prospect in baseball.

Click here to see his minor league stats

Click here to see the Texas League batting leaders

You can sort them by different stats. He is 7th in the league in OPS. He is 2nd in SBs with 28 (just 3 behind the leader) and has only been caught 8 times. He is 5th in AVG and 4th in OBP. 8th in SLG. 2nd in triples (he bats right-handed). He will turn 20 on Aug. 7. Pretty impressive showing at AA.

If you look at all of his minor league stats (including 2009 and 2010) you see lots of 3Bs, SBs (with good percentages) and high OBPs. He hits alot better in away games this year. Does anyone know if he plays in a tough hitter's park?

Wikipedia says "...Trout was named 2010 J.G. Taylor Spink Award as the Topps/Minor League Player of the Year. At just 19 years and two months, Trout is the youngest player ever to win this award."

Hitting Picks Up In July, But Only Slightly

Here are the OPS levels in the NL by month starting in April:

.709
.702
.699
.714

For the whole season, the NL has .704. For all of last year it was .723. In the first half it was .729.

Now the AL:

.713
.720
.719
.732

For the whole season, the AL has .719. For all of last year it was .734. In the first half it was .741.

So quite a drop off for both leagues this year.

Yes, It Is Easy To Explain Why McCutchen Did Not Make The All-Star Team

It seems like alot of people are wondering how a guy who is 2nd in WAR in the NL at both Baseball Reference and Fangraphs is not on the team. Here is why:

1. His value comes from non-traditional stats. He has a .389 OBP and 1.3 in defensive WAR (2nd in the league). The sabermetric revolution has only had so much influence and alot of people in baseball, including players and managers, don't know about them or don't think they are useful.

2. He has done poorly against the Giants, who are managed by the guy who picks the reserves, Bruce Bochy. The Giants have only played the Pirates 3 times this year, back in late April and McCutchen went 0 for 13. He has only a .180 career AVG with just 1 HR in 61 ABs against the Giants. So maybe that is why Bochy does not recognize how good he is.

3. He is not a standout in the traditional stats. McCutchen is not in the top 10 in HRs, RBIs or AVG or SBs. He has not won a Gold Glove and is only in his 3rd year. He has never batted .300, hit 30 HRs nor had 100 RBIs. So I guess he just does not have a great reputation (even though he should).

4. He also got off to a slow start, batting just .219 in April. Then he hit .275 in May and .347 in June (not witnessed by Bochy). So his name has not been on people's minds the whole season.

I could throw in that he plays on a team in a small market that has not had a winning season since 1992 and they have finished last in their division the last 4 years.

Is AROD In Serious Decline This Year?

Last week on the ESPN2 show "First Take," one of the commentators said something like "AROD is in serious decline this year." Those may not have been the exact words, but it was words to that effect.

Well, AROD has a 131 OPS+ this year, while last year it was 123. Even in 2009, it was 138, so this year is not too much worse than that. He did have 176 in 2007 and 150 in 2008. So any decline he had was before this year. And he is 35 (and turns 36 on 7-27). So this is not surprising.

He is also 7th in the league in WAR and the last year he was in the top 10 was in 2008. So the commentators of "First Take" could just as easily have said he was having a good comeback season. But they never mentioned WAR or OPS or any stats like that.

This brings me to my point: There is still not much use of sabermetrics in the mainstream media. Some complain about the new statistics ruining baseball. But the mass media, which alot more people are exposed to than stats blogs, keeps saying things that don't make sabermetric sense. So no, the new stats are not taking over and ruining baseball. They have made only a slight dent.

When the show discussed who the Yankees MVP was so far this year, they said Mark Teixeira. But here are Yankee leaders in WAR:

Curtis Granderson 3.8
Alex Rodriguez 3.3
Brett Gardner 2.8
Robinson Cano 2.5
Nick Swisher 2.5
Mark Teixeira 1.8

Teixeira is 2nd on the team in OPS+. But Granderson has 157.

Another example of this is Hawk Harrelson on the game today talking about how the leadoff walk always scores. But no one on national TV or a super station like WGN ever mentions the work of Retrosheet head Dave Smith who showed that leadoff walks only score about as often as leadoff singles. See Leadoff walks.

Great Post By Rich Lederer At Baseball Analysts

Rich has been cited for showing "you can move around the traditional gatekeepers and centers of power" because of his great campaign to get Bert Blyleven elected to the Hall of Fame. See The Declaration of Independents by Rich Lederer.

Phillies Send Starting Pitcher To Minors-His ERA Was Too High At 2.20

See Worley, Phils beat Marlins 1-0.

One anonymous source said "The guy clearly was not pulling his weight." Another said "We couldn't allow him to put our season in jeopardy."

If you look at the numbers I posted yesterday, 3 of the top 7 in WAR in the NL were Phillies pitchers (that is among everyone, position players included). This has got to be very rare.

Player Tied For NL Lead In WAR Not On The All-Star Team

Bill Gilbert pointed this out to me. Here are the leaders from Baseball Reference:

1. McCutchen (PIT) 5.1
Kemp (LAD) 5.1
3. Halladay (PHI) 4.6
4. Braun (MIL) 4.3
5. Reyes (NYM) 4.2
6. Hamels (PHI) 4.0
7. Lee (PHI) 3.8
8. Jurrjens (ATL) 3.7
9. Bourn (HOU) 3.5
10. Kershaw (LAD) 3.4

At Fangraphs, McCutchen is 2nd to Jose Reyes. Anyone know how often this happens, that the leader in WAR does not make the All-star team?

The Pirates have one all-star, Hanrahan, a reliever. Maybe Bochy thought that is what the NL needed. But McCutchen is having a better year than Beltran (not to pick on him) at least according to WAR, 5.1-2.7. And McCutchen has been good the last two years and had more WAR last year than Beltran. The Mets have at least one all-star anyway, Reyes. So McCutchen could have easily been picked within the current rules.

McCutchen gets alot of his value from a high OBP (.393) and his defensive WAR (1.4), which is 2nd in the league. The Giants have only played the Pirates 3 times this year, back in late April and McCutchen went 0 for 13. He has only a .180 career AVG with just 1 HR in 61 ABs against the Giants. So maybe that is why Bochy does not recognize how good he is.

McCutchen is not in the top 10 in HRs, RBIs or AVG. He has not won a Gold Glove and is only in his 3rd year. He has never batted .300, hit 30 HRs nor had 100 RBIs. So I guess he just does not have a great reputation.

His Baseball Reference page shows him with 4.0 WAR last year, which is very good. Yet when I used the Play Index to find the leaders in WAR, it shows him with just 3.7 (good for 26th) among position players.

He also got off to a slow start, batting just .219 in April. Then he hit .275 in May and .347 in June. He is 7th in OPS+ at 150.

White Sox 31-20 Since Starting 11-22

They had the worst record in baseball on May 6 at 11-22. They were the only team below .400 at that point.

In April, they had a batting OPS of .664 while allowing .739. In May it was .754/.695 and June was .721/.659. So after a bad
-.075 In April, they were a positive .059 and .062 the last two months.

My rough formula for winning pct is

Pct = .5 + 1.25*OPSDIFF

So they should have been .575 over May and June while they were actually 30-24 or .556. A .575 pct would give them 31 wins.

Through May 6, they were outscored 158-123, slightly more than 1 run per game. Since then, including beating the Cubs today 1-0, they have outscored their opponents 219-186. That gives them a Pythagorean winning pct of .581 while 31-20 is .608.

So Far, Phil Humber Has Resembled Greg Maddux

A pleasant surprise for the White Sox, although it is only for half a season. Humber is not striking out alot of guys, but he is not walking many and he is not giving up many HRs. That is what Maddux did. Humber stats are close to Maddux's career averages.

The table below shows how Humber this year compares to Maddux's career numbers. Of course, Maddux pitched until he was 42. But even if I only went up to age 37, Humber would still be close and Maddux had a 143 ERA+, just a bit better than what Humber has this year.

This Year's Low Scoring In Recent Historical Perspective

The NL OPS in each of the first 3 months has been: .709-.702-.699. The declines seem as surpising as the low levels. And in June the NL has had some games with the DH. So it might have been lower without the inter-league games. The AL has gone .713-.720-.719.

David Pinto of "Baseball Musings" had a good post a couple of days ago about hitting this year vs. last year. See Halfway Point. He shows how HRs, hits, etc. have fallen.

The graph below shows AL runs per game from 1960-2011



It is pretty clear that this year is pretty low (4.26). The last time the AL was lower than 4.26 was in 1981, when it was 4.07. That was a strike year. Taking that out, we need to go back to 1978, when the average was 4.2.

The graph below shows NL runs per game from 1960-2011



The average this year is 4.1. The last time it was lower was in 1992 when it was 3.88.

Sad Story: Ricky Vaughn Admits He Used Steroids In 1989 To Help Indians Win Division Title

I guess there is nothing left to believe in. It was a great Cinderella story that year and now it is ruined.

Click here to read the story,

Rich Gossage vs. Mariano Rivera

...“I wasn’t a closer, I was a relief pitcher,” Gossage said. He made a great point that he was not just the closer, but the seventh and eighth inning man. He pointed out that he came on with inherited runners in the seventh or eighth inning many times. Some of those situations required that he keep the ball out of play.

Gossage went on to say that “Mariano doesn’t come in with inherited runners. He gets to start out the ninth with nobody on… Easy? It is a piece of cake compared to what we use to do.”

From Baseball Think Factory, quoting an article by Mike Silva.

Yes, relievers were used differently in Gossage's time. From 1977-1985, one of the time periods I will look at for Gossage, most of the top 50 seasons in both saves and games finished were by pitchers who pitched over 100 innings (with only a couple of cases of even 1 game started). From 1997-2005, the period I will look at for Rivera, there were no 100+ IP seasons and even 90+ IP was rare (less than 5 for both stats).

So I want to compare both Gossage and Rivera to the average relievers of their times. I picked Gossage's 1977-1985 years since that seems to be his prime years and he was very good throughout the period. It does leave out his great 1975 season as a reliever (he was a starter in 1976). So for Rivera, I look at his first 9 years as a closer, 1997-2005 (which leaves out a very good 1996 seaon). The fact that Rivera has continued to pitch great since then is a plus in his favor. Gossage supporters might say that Rivera's relatively low IP totals have helped his longevity. Gossage was just average after 1985.

The average relief pitcher from 1977-1985 had an ERA of 3.68 while Gossage had 2.10. If we turn that into a winning pct. using the Pythagorean formula created by Bill James to estimate team winning pct. using runs and runs allowed, we get .754. From 1997-2005, Rivera's years, he had an ERA of 2.04 while the league average was 4.31. That gets us a pct of .817. So Rivera edges Gossage .817-.754. (I checked park factors for each pitcher and the simple average of their teams pitching park factors was the same, 97.56, meaning that they each got a little help from their parks, which were about 2.5% lower than average in scoring). All the data I use here is from Baseball Reference or The Lee Sinins Complete Baseball Encyclopedia.

I also found the top 10 pitchers in saves in each era and then calculated the combined ERA of the other 9 (taking out Gossage and Rivera). The best 9 in Gossage's years had 2.87. That gets a .651 pct. The best 9 in Rivera's years had 3.07, getting us a pct of .694. Again, edge to Rivera.

So far, when being compared to contemporaries with a similar role, Rivera is ahead. But ERA can be misleading, since the fielders play a role here (and ERA may not be the best way to judge relievers who are supposed to come in and put out fires).

To avoid this problem, I am going to look at how each guy comapared to his peers in the fielding independent stats (HRs, BBs, SOs). Then I will convert that into a run value using the values below

HR: 1.40
BB: .33
SO: -.22

Those are the values used in what is called "Fielding Independent ERA" formulas. The table below shows how each guy compared to the average reliever of his time in these stats per 9 IP. For example, Gossage allowed .508 HRs per 9 IP while the average reliever allowed .724. So he was .216 better. Multiplying that by 1.4 we get .3024 (it is negative in the table, meaning how much below average Gossage was). Then this is done for the other stats and for Rivera. The last line shows the combined run value each guy was below average using all three sats.



So Rivera is farther below average than Gossage. If I use the average reliever ERAs from each period, then Gossage gets 2.49 (3.68 - 1.19). Rivera gets 2.76 (4.31 - 1.55). The Pythagorean winning pct for Gossage is then .686 and for Rivera it is .709. The next table does the same thing but only for the other 9 pitchers in the top 10 in saves in each period.



Going right to the bottom line, we can see that they are almost even. Gossage would get a Pythagorean pct of .620 and Rivera would get .611. Very close. Now Gossage may have been better than Rivera, but I think the evidence shows that he should not belittle his greatness. Rivera seems to be at least close to Gossage as measured by how good they were relative to their peers.

One weakness of looking at the others in the top 9 is that park effects and fielders might play a big role since they don't represent the entire league. It is possible that the other 9 guys Rivera gets comapred to pitched in great hitters parks so they look weak in comparison to him. Or maybe Rivera had much better fielders behind him. I have not checked that. And when I did the top 10, it included both leagues whereas when I used the league average, it was just the league they pitched in (for Gossage it was the NL from 1977 and 1984-5 and the AL from 1978-83).

Who Did Yankee Opponents Have To Fear In The Late Innings During The Late 1970s?

A couple of weeks ago on a White Sox game, Ken Harrelson said something like "back in the late 70s, when you were facing the Yankees, Reggie Jackson wasn't the guy you had to worry about. Other teams worried about Munson and Piniella in the late innings."

So I looked at how each of them hit in innings 7-9 from 1977-79 using Baseball Reference. The table below summarizes the data.



If you were afraid someone would get a hit, Piniella was the problem. But if power was the concern, Jackson was still definitely the guy doing the damage. And his average was not much lower than Munson's.

Here is the AVG/SLG/ISO for each guy combined for the three years:

Jackson 0.275/0.543/0.268
Munson 0.280/0.361/0.081
Piniella 0.328/0.452/0.124

Notice that if you add up the isolated power of both Munson and Piniella it is still less than Jackson's, meaning that he had more extra bases per AB than those two combined.

June Hitting Up Slightly In The AL, Down Slightly In The NL

With hitting pretty low already this year, not much good news for fans who like offense. The AL OPS by month so far

April .713
May .720
June .723

But for isolated power (ISO) we have

April .145
May .141
June .140

Runs per game in June 4.4

The NL OPS by month so far

April .709
May .702
June .700

But for isolated power (ISO) we have

April .137
May .132
June .131

Runs per game in June 3.83

Seasons With 15 Or Fewer HRs And SLG > .600

The PA minimum was 400. This is inspired by “Roll Projector!” Jose Reyes *is* on an Historic Pace from the Baseball Reference blog. They mention that Jose Reyes has a chance to set the Mets record for total bases in a season without hitting many HRs.

The table below shows all of the players who fit my criteria.



Those all happened a long time ago. The table below shows all the players who did it since 1946 with less than 30 HRs.

June Hitting Off To A Slow Start

The NL is averaging 3.89 runs per game with a .689 OPS. Their ISO is just .125. The AL is scoring 4.16 runs per game with a .712 OPS and a .139 ISO. Data from Baseball Reference. These numbers are even lower than they were in April and May. See my earlier post May Hitting About As Bad As April.

Last night there were 7 games with a total runs scored of 5 or less. That is between both teams. In 98 games so far in June, the NL has hit just 73 HRs. That would be about 120 per team for a whole season. The AL was a little better with 82 HRs in 88 games.

The table below shows the hitting stats in each month for both leagues in each of the last two years. The June numbers for 2010 are for the entire month.



The next table shows how each of those stats has changed.


Not sure if there is any kind of pattern other than that everything is down. It looks like the NL's power decline is even bigger than the AL's when you look at ISO.

May Hitting About As Bad As April

The MLB OPS for each month was .711. The NL fell to .702 from .709 while the AL rose to .720 from .713. But each league saw runs per game drop off. The AL went 4.33-4.29 while the NL went 4.25-4.02. Isolated power fell just a bit in each league. The AL declined from .145 to .142 while the NL slid to .132 after .137 in April.

The run scoring was probably helped over the last two days of the month which had 5.28 per game for all of MLB. I looked at April vs. May hitting a few weeks ago with May Hitting So Far Has Been Even Worse Than April Hitting and May OPS: AL .705, NL .699.

I also noted, as so many others have, that Albert Pujols is off to a slow start. See Albert Pujols' Slow Start from May 23. His OPS+ in each of the first two months so far have been 112 & 113. It is the first time in his career that he has had two straight months under 120. He has only had under 150 in back-to-back months twice before this and never had back-to-back months below 140. In 48 of his first 60 months his OPS+ has been 150 or higher. His ISO in May was .099, well below the league average of .132.

Paul Konerko had the highest May OPS of his career, .902. The next highest is .846. So given that hitting is down in MLB this year compared the rest of his career, this is pretty interesting. In fact, Konerko's May OPS in every year of his career has been less than the full-season OPS. See May Day, May Day! Throw Konerko A Life Preserver. So it looks like he has overcome his May jinx.

The table below shows his OPS in every month starting in 1999. April actually includes March and Sept includes Oct.



In only 3 seasons has his May OPS been greater than his April OPS (1999, 2007 and 2001). In only 3 seasons has his May OPS been greater than his June OPS (1999, 2003, and 2009). In six seasons his May OPS fell by 100 or more points compared to April and then rose 100 or more points in June compared to May.

In six seasons his overall OPS was 100 or more points better than his May OPS. Three others were 50 or more points better. The closest his May OPS has gotten to his full season OPS is 22 points. He has had 8 months with an OPS under .600 and 4 of them have come in May. No other mont has more than one and the one from Sept was .599.

Going into this year his career May OPS was .713. So he beat that by nearly 200 points.