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Just The Sports: 2006-07-09

Just The Sports

Saturday, July 15, 2006

Yankees Pitchers vs. Red Sox Pitchers

With the Yankees and the Red Sox duking it out for AL East supremacy and the playoff berth that comes along with it, it is worth looking at how their pitching staffs stack up against each other since pitching will partly determine who walks away with the division title. For the most part, the two teams' records will be determined by their best three starters so those are the only ones I examined. I chose the three top starters from each team based on SNLVAR, or support-neutral lineup-adjusted value over a replacement level pitcher. SNLVAR is a Baseball Prospectus statistic that measures how many wins above a replacement level pitcher a pitcher adds if he receives league average run support.

The SNLVAR leaders for the Boston Red Sox are as follows: Curt Schilling (3.6), Tim Wakefield (2.2), and Josh Beckett (2.1). For the Yankees, the three starters are Mike Mussina (3.7), Chien-Ming Wang (2.7), and Jaret Wright (2.1). Yankee fans may wonder where Randy Johnson is on this list, but he has been outpitched by Wright this season. Now, let's compare the pitchers to their counterparts.

In the ace department, we have Curt Schilling and Mike Mussina. Since we already know Mussina has a higher SNLVAR, we could just stop there and anoint him the ace of the aces, right? Of the two, Schilling has the higher strikeout rate and the lower walk rate. The higher strikeout rate is to be expected from a power pitcher like Schilling, but the lower walk rate shows just how good Schilling is at what he does. Sometimes it is unfair to label him as a power pitcher or a finesse pitcher because he takes the best of both of those words (high strikeout rate, low walk rate) and uses them on the mound as his 7.67 strikeout-to-walk ratio indicates.

Mussina has the lower home run rate of the two. Mussina also has a slightly lower WHIP (Walks and Hits per Inning Pitched), but a slightly higher fielding-independent ERA. As for their profiles, each is a flyball pitcher up to today with Schilling being a more extreme version of one. As expected from their home run rates, Mussina has a lower HR/FB% and also a higher infield fly ball percentage, but Schilling bests Mussina in allowing a lower percentage of infield hits. Basically, the battle between these two pitchers is a push. However, Mussina may find himself hard pressed to keep up his absurdly low (for him) batting average allowed on balls in play of .271, his lowest such mark since 1995.

The second match-up pits the Yankees' Chien-Ming Wang against the Red Sox's knuckleballer Tim Wakefield. Comparing Wakefield to Wang is almost criminal, as their SNLVAR's suggest. Almost. Still, for the disparity in SNLVAR, Wakefield does have an advantage over Wang in both strikeout rate and strikeout-to-walk ratio. This advantage is largely because Wang is an extreme groundball pitcher and relies on his defense to get outs for him. Wakefield also has a lower WHIP than Wang, again understandable considering Wang allows a higher percentage of balls put in play.

Overall, though, Wang is better than Wakefield. He has a significantly lower fielding-independent ERA (4.02 to 4.64) even if his regular ERA is only marginally better than Wakefield's. Here, the Yankees have an advantage over the Red Sox.

Some may be dubious of whether Jaret Wright can continue to perform well, but it is what it is, and he has been the third best starter for the Yankees this year in terms of SNLVAR.

His counterpart on the Red Sox, and a player who matches him in SNLVAR, is Josh Beckett. Beckett is having one of his worst seasons as a major league pitcher, with career highs in ERA, fielding-independent ERA, and home run rate, all categories you do not want to post a career high in if you are a major league pitcher. Also, his strikeout rate is the lowest it has been for his career (7.48 K/9).

For the season, Beckett has certainly lived up to his reputation of being a pitcher who occasionally dazzles on the mound, but in the end ultimately leaves the observer dissatisfied. Beckett has certainly been the least consistent Red Sox starting pitcher.

Still, I am comparing Beckett to Wright and not Beckett to what his potential is. Beckett has the edge over Wright in a few categories: strikeout rate, strikeout-to-walk ratio, and WHIP. However, Beckett's 2.13 HR/9 is absolutely killing him and the Red Sox and makes Wright's .50 HR/9 look positively sublime. Beckett is also second to Wright in fielding-independent ERA (3.84 to 5.82). Once again, I have to give the edge to the Yankees, at least until Beckett can decrease his home run rate or Wright turns back into a pumpkin.

So far, it looks like you have to give the edge to the Yankees' three best starters over the Red Sox's three best starters, when ordered by SNLVAR.

Friday, July 14, 2006

Reds-Nationals Trade

Since I know you have been on pins and needles regarding my thoughts on the Reds-Nationals trade that occurred, here they finally are. The eight-player trade was dangerously one-sided in favor of the Washington Nationals, which may be the first trade where Jim Bowden came out on top. Even though there were eight players involved in the trade, the trade was really about five players: Royce Clayton, Gary Majewski, Bill Bray, Felipe Lopez, and Austin Kearns. This is nothing the other players, but it would be much less interesting if I included them in this discussion.

From a Cincinnati Reds perspective, this was an awful move and reinforces that the Reds organization is only interested in hiring general managers who are incompetent when it comes to gauging a player's value. Rarely, if ever, is it a good idea to trade for middle relievers while trading away everyday players who actually provide value to your team. Even very good middle relievers pitch so infrequently and are so reliant on the context of the game, it makes no sense to trade anything but a poor starter for them.

One compliment which should be given to the Cincinnati Reds is they do a good job of deploying their better relievers in high leverage situations. For the first half of the season, the correlation between their relievers' WXRL and Leverage was .780, above average for major league teams. Since the bullpen was poor overall, it did not matter that much, but I'm just trying to make Reds fans feel better at this point. How Majewski is supposed to help be a savior to this bullpen is a conundrum.

Majewski had a good season in 2005, but he has not equalled that performance in 2006. Right now, he is sitting on .015 WXRL so he has been just a whisker above replacement-level. In addition, his home run rate has tripled from last year (.21 HR/9) to this year (.65 HR/9). It is still low, but there is no evidence to suggest 2005 was not a fluke year and 2006 is the pitcher he will be going into the future. There is no evidence to suggest it is either, though. His Fielding-Independent ERA of 4.32 is nothing to smile about either and is simply not worth trading for.

As for Bill Bray, he has been the Nationals' third best reliever in WXRL (Wins Above Replacement Level) with .399, but the Nationals have wasted his talent in ridiculously low leveraged situations for a reliever (.86 Leverage). With the Reds track record so far, I have no doubt they will use him in higher leverage situations. Hopefully, they will be ones that are higher in leverage than the one Majewski sees. For those who think Bray's higher WXRL is a result of pitching in lower leveraged situations than Majewski, just remember that they have faced about the same quality batter (.372 wOBA for Bray to .366 wOBA for Majewski).

Trading for Royce Clayton is also a surprise because I was unaware any team still wanted Royce Clayton on their team. In getting Clayton, the Reds trade away a player in Felipe Lopez who had the highest VORP among NL shortstops in 2005 and the 6th highest this year for a player in Royce Clayton who was 12th in VORP among NL shortstops in 2005 and 13th this year. The worst part about the trade is that Clayton is supposed to be a defensive upgrade over Lopez. Only he's really not and hasn't been an above-average defensive player since 2003.

Actually, the Reds got a below-average fielder to replace their below-average fielder. Only the new below-average fielder can't hit.

The Washington Nationals came out looking good after this trade and how could they not. Felipe Lopez has a career wOBA of .358, which even though I did not check it, I am willing to bet is better than Royce Clayton's. He also has the advantage of being 26 and entering the prime of his career. So far, Lopez has shown improvement in his plate discipline, seeing his strikeout percentage decrease and his walk-to-strikeout ratio increase. His slugging percentage has not been consistent for his career, but his on-base percentage has been on the rise since 2002 so I think the Nationals will be happy with the player they have gotten.

Austin Kearns is another very find pick-up for the Nationals, with a career wOBA of .395, right about what you want from a corner outfielder. It would probably be higher if not for the Reds jerking their outfielders around for a couple of seasons. Some may be scared off by his strikeouts, but give me strikeouts any day if the player is going to slug around .500 when he gets the at-bats. Especially when the player also has a .200 isolated power percentage.

Bowden gets his Reds players back and the Reds general managers continue to be incompetent.

Klinsmann As Next US Coach?

The stars are aligning quite nicely for Jurgen Klinsmann to take over for Bruce Arena as the US Men's soccer coach if he wants the job. Now if only the US could find a way to naturalize some of Germany's players.

Ponson An Improvement

For all the angst the signing of Sidney Ponson may have caused Yankee fans, it is for the most part unwarranted because the picking up of Sidney Ponson off waivers was an improvement out of what they were getting from Shawn Chacon. No, Ponson is not going to light the world on fire, but no one should expect him to. He is joining the Yankees as a fifth starter, not as the ace of the staff and as such should be compared not to pitchers overall, but to the man he is replacing since major league teams are still against going back to a four-man rotation which would give their best starters more starts.

What Ponson should give over Chacon for the rest of the year is a higher groundball/flyball ratio, a lower walk rate, a higher strikeout-to-walk ratio, and a lower home run rate. Also, he has averaged two more outs in his starts this year so that is two less outs the Yankees bullpen will have to struggle to record. But his 5.3 innings a start won't be worth writing home about.

A weird attribute of Shawn Chacon is he pitches better in odd years than he does in even years. Too bad for him and the Yankees, 2006 is an even year.

Maybe the Yankees will catch lighting in a bottle with this pick-up, but in a league where most fifth starters are below-average, there was no reason to not make a move to improve a team's pitching staff no matter how slight the improvement might seem.

Thursday, July 13, 2006

Looking Behind MLB Teams' Records

Partially in response to a commenter and partially because I never explained my reasoning earlier, I want to defend my use of variance as a way to explain why a team's record is what it is given their run differntial. For all of the accuracy the Pythagorean winning percentage formula gives in predicting a team's record, it is by no means a perfect measure. The flaw in the Pythagenport formula is that it is only concerned with the difference between runs scored and runs allowed. It does not care how the teams scores and gives up runs and that is why the formula can be and has been tricked by numerous teams.

One example of how the Pythagenport formula can be fooled is by the team whose wins are blowouts and whose losses are in close games. This team will have a very favorable run differential that the formula will love and will reward the team with a higher winning percentage than the team will actually end up with. Vice versa, the team whose wins are in close contests and whose losses are of the blowout variety will not be looked upon favorably by the Pythagenport formula because this team will have a low run differential when they are not as bad as their run differential suggests.

Variance, standard deviation squared, is also not something which can be presented in a vacuum and that is where I made my mistake. Variance is good for telling you how inconsistent a team is in scoring or allowing points, but variance is not something that can be compared uniformly across the board because each team has a different margin for error. What I call margin of error is actually a team's average run differential (differential between average runs scored and average runs allowed) and displays how inconsistent a team can be without it hurting too much. A team with a high postive average run differential can afford to be more inconsistent than a team with a zero net average run differential can.

In order to provide a comprehensive look behind each MLB team's first half records, I included every team's actual winning percentage, Pythagorean winning percentage, average runs scored, average runs allowed, offensive variance, defensive variance, average margin of victory, and average margin of defeat. I also included each team's win-loss record in 1-run contests because that usually evens out to .500 over the course of the season so a team that is doing really well in the first half will usually find themselves doing really poorly in the same 1-run games in the second half. Even so, there will be some teams for which these stats will not paint a clear picture for why a team is doing well or poorly.

Since I am looking at every team in the major leagues, you may just want to find the team or teams you are most interested in and read what the numbers say about them. Teams will be compared to each other within the same division.

AL East

Boston Red Sox
Actual Winning Percentage: .616 (53-33)
Expected Winning Percentage: .574 (49-37)
Average Runs Scored: 5.7
Average Runs Allowed: 4.8
Offensive Variance: 10.1
Defensive Variance: 8.0
Average Victory Margin: 3.7
Average Defeat Margin: 3.7
1-Run Win Loss Record: 13-6

Looking at the numbers, it is easy to tell why the Red Sox have outperformed their expected winning percentage. Couple their consistency with their high positive average run differential and you will usually get a team that is going to outperform their expected winning percentage. The Red Sox are also consistent in terms of their average victory and defeat margins.

Where they have been helped out so far is their win-loss record in 1-run games. This record will probably not repeat itself in the second half.

New York Yankees
Actual Winning Percentage: .581 (50-36)
Expected Winning Percentage: .575 (49-37)
Average Runs Scored: 5.6
Average Runs Allowed: 4.7
Offensive Variance: 14.3
Defensive Variance: 11.5
Average Victory Margin: 4.0
Average Defeat Margin: 3.5
1-Run Win-Loss Record: 14-12

The Yankees actual record is marginally better than their expected winning percentage, but compared to the Red Sox, who they are chasing for the AL East lead, they are not doing so well. They have the same average run differential as the Red Sox, but they have been much more inconsistent, having higher offensive and defensive variances.

How they will rectify their inconsistency is up for debate. Either a good hitter or a good pitcher will do just like it would do for every team in the major leagues.

Toronto Blue Jays
Actual Winning Percentage: .557 (49-39)
Expected Winning Percentage: .540 (48-38)
Average Runs Scored: 5.4
Average Runs Allowed: 4.9
Offensive Variance: 8.8
Defensive Variance: 9.3
Average Victory Margin: 3.8
Average Defeat Margin: 3.8
1-run Win-Loss Record: 7-2

Toronto sports the most consistent good team in the AL East. If they could manage a higher average run differential and a higher actual run differential, then they would lead the AL East division. However, that is easier said than done and the Blue Jays will probably finish third in this division.

Their consistency has really helped them outperform their expected winning percentage along with their 1-run win-loss record of 7-2.

Baltimore Orioles
Actual Winning Percentage: .456 (41-49)
Expected Winning Percentage: .437 (39-51)
Average Runs Scored: 4.8
Average Runs Allowed: 5.6
Offensive Variance: 12.0
Defensive Variance: 9.4
Average Victory Margin: 3.4
Average Defeat Margin: 4.1
1-Run Win-Loss Record: 12-7

Baltimore is outperforming their winning percentage for two reasons. The first is because of their inconsistency. It may sound counterintuitive, but inconsistency for an under-.500 team actually helps the team because inconsistency brings teams closer to .500. In this case, inconsistency is bringing Baltimore up to .500 level.

Also, as I alluded to earlier, that there is such a disparity between their average victory and defeat margins (in favor of defeat margin), it has helped the Orioles do better than their run differential suggests.

Tampa Bay Devil Rays
Actual Winning Percentage: .438 (39-50)
Expected Winning Percentage: .420 (37-52)
Average Runs Scored: 4.3
Average Runs Allowed: 5.1
Offensive Variance: 6.7
Defensive Variance: 10.8
Average Victory Margin: 2.9
Average Defeat Margin: 3.8
1-Run Win-Loss Record: 10-9

Conceivably, the Devil Rays should be doing better in outperforming their expected winning percentage than Baltimore is doing at outperforming theirs. They are getting more blown out in their losses as compared to their winning close games than Baltimore is, but the problem with the Devil Rays is their consistency. If they were less consistent, then they would probably be closer to .500 then their actual winning percentage.

AL Central

Detroit Tigers
Actual Winning Percentage: .670 (59-29)
Expected Winning Percentage: .645 (57-31)
Average Runs Scored: 5.2
Average Runs Allowed: 3.7
Offensive Variance: 12.0
Defensive Variance: 8.4
Average Victory Margin: 3.8
Average Defeat Margin: 3.3
1-Run Win-Loss Record: 15-10

Do not be tricked by the high offensive variance the Tigers have because this is no mere mortal team. With the amazingly high positive average run differential of 1.5, they are very consistent in comparison to other teams because how much variance affects a team is relative. If they were not winning a large number of their games in blowouts, they would probably be outperforming their expected winning percentage even more.

Chicago White Sox
Actual Winning Percentage: .648 (57-31)
Expected Winning Percentage: .602 (53-35)
Average Runs Scored: 5.9
Average Runs Allowed: 4.7
Offensive Variance: 12.4
Defensive Variance: 11.1
Average Victory Margin: 3.9
Average Defeat Margin: 3.8
1-Run Win-Loss Record: 15-10

The White Sox do not have as high a positive average run differential as the Detroit Tigers, are less consistent, but they are still outperforming their expected winning percentage to a greater degree. Why is that, you ask? The answer: because their average victory and defeat margins are basically the same while being consistent enough given their average run differential.

Minnesota Twins
Actual Winning Percentage: .547 (47-39)
Expected Winning Percentage: .529 (45-41)
Average Runs Scored: 4.9
Average Runs Allowed: 4.6
Offensive Variance: 11.2
Defensive Variance: 10.7
Average Victory Margin: 3.8
Average Defeat Margin: 3.9
1-Run Win-Loss Record: 11-5

The Minnesota Twins are largely doing better than expected based on their 11-5 record in games decided by one run. They are certainly not overly consistent given such a low margin of error. Look for this team to struggle repeating their success in 1-run contests in the second half of the season.

Cleveland Indians
Actual Winning Percentage: .460 (40-47)
Expected Winning Percentage: .544 (47-40)
Average Runs Scored: 5.7
Average Runs Allowed: 5.0
Offensive Variance: 15.0
Defensive Variance: 14.3
Average Victory Margin: 5.3
Average Defeat Margin: 3.6
1-Run Win-Loss Record: 7-13

There is no nice way to put this; the Cleveland Indians are a trainwreck in every way. They are the most inconsistent team in the major leagues and they also have the highest run differential between average victory margin and average defeat margin. Combine those things with a horrible win-loss record and you can understand why their actual winning percentage is .084 lower than their expected winning percentage.

Something that bears mentioning is that when a team has more than their fair share of one run losses, it skews the results of their average victory and average defeat margins. Even when taking that into account, Cleveland still gets too many wins in blowouts to go by their expected winning percentage. Losing in closer contests than you win in is a sign of a poor bullpen.

Kansas City Royals
Actual Winning Percentage: .356 (31-56)
Expected Winning Percentage: .371 (32-55)
Average Runs Scored: 4.5
Average Runs Allowed: 6.1
Offensive Variance: 11.6
Defensive Variance: 10.1
Average Victory Margin: 3.1
Average Defeat Margin: 4.1
1-Run Win-Loss Record: 10-12

It is no secret that the Royals are the worst team in the majors. Everyone knows it. Even people who don't follow baseball know it. The only reason I even computed their statistics is because I promised to look at every major league team.

By the way, their -1.6 average run differential is the lowest in the majors. No surprise there.

AL West

Texas Rangers
Actual Winning Percentage: .511 (45-43)
Expected Winning Percentage: .522 (46-44)
Average Runs Scored: 5.1
Average Runs Allowed: 4.9
Offensive Variance: 9.3
Defensive Variance: 10.4
Average Victory Margin: 3.4
Average Defeat Margin: 3.0
1-Run Win-Loss Record: 8-16

The Rangers are only doing marginally worse than their expected winning percentage, but that extra game would give them the lead in the AL West division. So far, they have been the second most consistent team in this division and have the highest average run differential. Their undoing has been their abysmal record in 1-run contests, which I am sure will even itself out in the second half.

Oakland Athletics
Actual Winning Percentage: .511 (45-43)
Expected Winning Percentage: .483 (43-45)
Average Runs Scored: 4.3
Average Runs Allowed: 4.5
Offensive Variance: 7.8
Defensive Variance: 8.9
Average Victory Margin: 2.9
Average Defeat Margin: 3.3
1-Run Win-Loss Record: 17-15

The Oakland Athletics have done everything right besides actually outscoring their opponents on a consistent basis. They have needed every bit of their consistency because they have absolutely no margin for error at all. This team has also been helped out by the fact they are more likely to win a close contest and lose a game by a higher number of runs.

Los Angeles Angels
Actual Winning Percentage: .489 (43-45)
Expected Winning Percentage: .490 (43-45)
Average Runs Scored: 4.6
Average Runs Allowed: 4.7
Offensive Variance: 10.0
Defensive Variance: 12.2
Average Victory Margin: 3.8
Average Defeat Margin: 3.8
1-Run Win-Loss Record: 11-13

Since the Angels are performing the same as expected, there is no reason to devote much time to what they have done on the field. So I won't.

Seattle Mariners
Actual Winning Percentage: .483 (43-46)
Expected Winning Percentage: .505 (45-44)
Average Runs Scored: 4.8
Average Runs Allowed: 4.7
Offensive Variance: 11.6
Defensive Variance: 9.9
Average Victory Margin: 3.5
Average Defeat Margin: 3.2
1-Run Win-Loss Record: 8-12

The Mariners have the other positive average run differential in the AL West, but unfortunately for them, they do not have the consistency of the Texas Rangers so they are unable to overcome their 8-12 record in 1-run games.

What all those 1-run contests have done is to drive down the average defeat margin and give the Mariners more credit than they deserve.

NL East

New York Mets
Actual Winning Percentage: .596 (53-36)
Expected Winning Percentage: .572 (51-38)
Average Runs Scored: 5.3
Average Runs Allowed: 4.5
Offensive Variance: 11.3
Defensive Variance: 9.2
Average Victory Margin: 3.6
Average Defeat Margin: 3.4
1-Run Win-Loss Record: 20-9

The Mets have been a good team so far this season, but they have in no way been spectacular. They have been fairly consistent relative to their average run differential, but they have been extremely lucky in games decided by one run, having the highest winning percentage in the majors in those types of games. Too bad it is not success which is likely to last.

Philadelphia Phillies
Actual Winning Percentage: .460 (40-47)
Expected Winning Percentage: .464 (40-47)
Average Runs Scored: 4.8
Average Runs Allowed: 5.2
Offensive Variance: 6.8
Defensive Variance: 8.8
Average Victory Margin: 3.0
Average Defeat Margin: 3.3
1-Run Win-Loss Record: 9-15

A mass of contradictions surrounds this Phillies team. They are doing as well as expected, but the way they have gotten there is odd. Their high level of consistency has no doubt taken their record down because they are already a below .500 team to begin with. But losing worse than they win has brought their record back up, only to have it taken down again by a poor win-loss record in 1-run games.

Atlanta Braves
Actual Winning Percentage: .449 (40-49)
Expected Winning Percentage: .491 (44-45)
Average Runs Scored: 4.9
Average Runs Allowed: 5.0
Offensive Variance: 10.4
Defensive Variance: 10.7
Average Victory Margin: 3.4
Average Defeat Margin: 2.9
1-Run Win-Loss Record: 12-21

Atlanta's frittering away of their run differential can be directly attributed to the disparity between their average victory and average defeat margins. Their 1-run win-loss records in no way has helped them, either.

Florida Marlins
Actual Winning Percentage: .442 (38-48)
Expected Winning Percentage: .488 (42-46)
Average Runs Scored: 4.8
Average Runs Allowed: 4.9
Offensive Variance: 11.2
Defensive Variance: 11.3
Average Victory Margin: 4.1
Average Defeat Margin: 3.5
1-Run Win-Loss Record: 9-18

See: Atlanta Braves

Washington Nationals
Actual Winning Percentage: .422 (38-52)
Expected Winning Percentage: .435 (39-51)
Average Runs Scored: 4.5
Average Runs Allowed: 5.2
Offensive Variance: 9.4
Defensive Variance: 11.1
Average Victory Margin: 3.5
Average Defeat Margin: 3.8
1-Run Win-Loss Record: 9-14

Here is another example of why it is not always advisable for a team to be consistent. The Nationals are just as consistent as the Mets, but when you are already worse than your opponent, it does you no good to be consistent and perform the way you always perform because it will result in you being worse than you could be.

With a higher average defeat margin, you would expect the team to do better than their expected winning percentage, not worse. Such is the case with the Washington Nationals. Their 1-run win-loss record provides the key for this unexpected turn.

NL Central

St. Louis Cardinals
Actual Winning Percentage: .552 (48-39)
Expected Winning Percentage: .516 (45-42)
Average Runs Scored: 5.1
Average Runs Allowed: 4.9
Offensive Variance: 7.8
Defensive Variance: 11.5
Average Victory Margin: 3.3
Average Defeat Margin: 3.6
1-Run Win-Loss Record: 13-13

This team should consider themselves very lucky to be in the NL Central, probably the worst division in MLB this season. To the Cardinals' credit, though, they have been the most consistent team in baseball, which has helped them outperform their expected winning percentage. Also, providing aid to the Cardinals in their attempt to circumvent their unimpressive run differential is that they lose worse than they win.

Cincinnati Reds
Actual Winning Percentage: .506 (45-44)
Expected Winning Percentage: .485 (43-46)
Average Runs Scored: 5.0
Average Runs Allowed: 5.2
Offensive Variance: 11.1
Defensive Variance: 10.5
Average Victory Margin: 3.4
Average Defeat Margin: 3.8
1-Run Win-Loss Record: 16-11

As has been the case for many of the teams in the majors, the Reds are helped by a higher average defeat margin than average victory margin and also having a fairly good record in 1-run games.

Milwaukee Brewers
Actual Winning Percentage: .489 (44-46)
Expected Winning Percentage: .425 (38-52)
Average Runs Scored: 4.6
Average Runs Allowed: 5.4
Offensive Variance: 8.5
Defensive Variance: 12.4
Average Victory Margin: 2.8
Average Defeat Margin: 4.3
1-Run Win-Loss Record: 19-10

Once again, we have an example of a team outperforming their expected winning percentage based on a higher average defeat margin and a good record in 1-run contests. Maybe a lot of this is attributable to luck, but if that is the case, then a lot of teams have been getting lucky in the first half of the season.

For the Brewers, however, who have the highest differential in the majors between average defeat margin and average victory margin, the expected winning percentage can be thrown out of the window in lieu of these other statistics.

Houston Astros
Actual Winning Percentage: .483 (43-46)
Expected Winning Percentage: .471 (42-47)
Average Runs Scored: 4.6
Average Runs Allowed: 4.9
Offensive Variance: 9.2
Defensive Variance: 11.4
Average Victory Margin: 3.5
Average Defeat Margin: 3.8
1-Run Win-Loss Record: 15-9

I am in danger of sounding like a broken record, but the Houstron Astros have slightly bettered their expected winning percentage by having an average defeat margin slightly higher than their average victory margin coupled with a 15-9 1-run record.

Chicago Cubs
Actual Winning Percentage: .386 (34-54)
Expected Winning Percentage: .394 (35-53)
Average Runs Scored: 4.0
Average Runs Allowed: 5.1
Offensive Variance: 11.5
Defensive Variance: 10.9
Average Victory Margin: 3.7
Average Defeat Margin: 4.1
1-Run Win-Loss Record: 6-14

Looking solely at Chicago's average defeat and average victory margins, you would think the Cubs would be outperforming their expected winning percentage like the Cincinnati Reds, but that is not the case. Why is that? Well, having a higher average defeat margin only helps a team when the team also does well in games decided by a single run. Since Chicago has only gone 6-14 in such contests, any advantage they had was canceled out, leaving them where they started.

Pittsburgh Pirates
Actual Winning Percentage: .333 (30-60)
Expected Winning Percentage: .438 (39-51)
Average Runs Scored: 4.6
Average Runs Allowed: 5.2
Offensive Variance: 10.7
Defensive Variance: 9.5
Average Victory Margin: 3.8
Average Defeat Margin: 2.9
1-Run Win-Loss Record: 9-25

Even if you are not a Pittsburgh Pirates fan, you have to feel bad for this team because they have had such miserable luck so far this season. Their 9-25 record is the worst in the majors and is the main culprit behind tricking the Pythagorean formula. Hopefully, the luck for the Pirates will change and they will play the real below .500 ball they should be playing.

NL West

San Diego Padres
Actual Winning Percentage: .545 (48-40)
Expected Winning Percentage: .529 (47-41)
Average Runs Scored: 4.5
Average Runs Allowed: 4.2
Offensive Variance: 9.2
Defensive Variance: 8.1
Average Victory Margin: 3.1
Average Defeat Margin: 3.2
1-Run Win-Loss Record: 18-11

San Diego have outperformed their run differential because of their consistency and having a very respectable 18-11 record in 1-run games.

Los Angeles Dodgers
Actual Winning Percentage: .523 (46-42)
Expected Winning Percentage: .557 (49-39)
Average Runs Scored: 5.4
Average Runs Allowed: 4.7
Offensive Variance: 9.7
Defensive Variance: 9.2
Average Victory Margin: 4.0
Average Defeat Margin: 3.1
1-Run Win-Loss Record: 8-12

Los Angeles are not underperforming their expected winning percentage because of any lack of consistency, but because they have such a disparity between their average victory margin and average defeat margin. Their 8-12 record does not help matters either.

Colorado Rockies
Actual Winning Percentage: .506 (44-43)
Expected Winning Percentage: .514 (45-42)
Average Runs Scored: 4.7
Average Runs Allowed: 4.6
Offensive Variance: 11.4
Defensive Variance: 9.9
Average Victory Margin: 3.5
Average Defeat Margin: 3.3
1-Run Win-Loss Record: 13-15

Because of their average victory margin being slightly higher than their average defeat margin, the Rockies are doing slightly worse than their expected winning percentage.

San Francisco Giants
Actual Winning Percentage: .506 (45-44)
Expected Winning Percentage: .513 (46-43)
Average Runs Scored: 4.7
Average Runs Allowed: 4.6
Offensive Variance: 10.7
Defensive Variance: 9.1
Average Victory Margin: 3.7
Average Defeat Margin: 3.5
1-Run Win-Loss Record: 13-9

See: Colorado Rockies

Arizona Diamondbacks
Actual Winning Percentage: .489 (43-45)
Expected Winning Percentage: .478 (42-46)
Average Runs Scored: 4.9
Average Runs Allowed: 5.1
Offensive Variance: 9.0
Defensive Variance: 12.4
Average Victory Margin: 3.3
Average Defeat Margin: 3.7
1-Run Win-Loss Record: 14-14

Like many other teams, the Diamondbacks are exceeding expectations by having a higher average defeat margin. With so many teams tricking the Pythagorean formula, it may be time to tweak it just a bit.

*Any errors in the numbers are due to my human error.

Wednesday, July 12, 2006

Seriously, FIFA, You're Embarrassing Yourself

In case you had your head under a rock for the past few days, you know that Zinedine Zidane was given a red card for headbutting Italian defender Marco Materazzi, being sent off in the World Cup final, which France eventually lost to Italy won on penalty kicks. You also know that Zidane was given the Golden Ball award, given to the best player at the World Cup. What you may not know is that FIFA may want to strip Zidane of this honor.

FIFA president Sepp Blatter says Zinedine Zidane could be stripped of his Golden Ball award for the best player at the World Cup due to violent conduct.


Then why the fuck did you give it to him in the first place?

"The winner of the award is not decided by FIFA, but by an international commission of journalists," Blatter said in Wednesday's La Repubblica. "That said, FIFA's executive committee has the right, and the duty, to intervene when faced with behavior contrary to the ethic of the sport."


If the FIFA executive committee can just waltz in and strip a player of an award when the award is not even decided by them, then why doesn't the executive committee just pick the winner in the first place? That way there will be no controversy and you can stop pretending to give journalists power only to strip it away later when you don't agree with their decision.

And Blatter, in case you didn't know, there are few things ethical about soccer/football. There are few things ethical about any sport.

"I was told that at the end of the game the French federation executives asked Zidane to go and receive his medal, and he replied that he didn't deserve any medal," Blatter added.


And? What does that mean?

Listen, you can't ask an athlete anything after he or she suffers a crushing defeat. The athlete is still much too emotional to be rational.

In addition, it doesn't matter if Zidane does not think he deserves the medal. He is not voting on it. The journalists are. Lots of athletes don't deserve their awards. Bartolo Colon didn't deserve his AL Cy Young last year. Steve Nash didn't deserve his 2006 MVP award. Karl Malone didn't deserve his 1997 MVP trophy. But they didn't deserve their awards based on merit. Zidane does.

Just let Zidane keep the award. The football world will not spin off its axis if he is allowed to keep what is rightfully his.

Tuesday, July 11, 2006

Isiah Thomas The Coach

This article is a little old, being written six days ago, but it is still worth writing about and adding a few details to it that the author Dave D'Alessandro left out. In the article, D'Alessandro makes the claim that Isiah the coach will save Isiah the GM, which is probably right. The Knicks certainly won't get any worse so there is a high probability Dolan will not fire Thomas right away. Actually, just by virtue of the team suiting up for all 82 games next year, the Knicks can be expected to improve their winning percentage by 9% which would give them thirty wins next season.

That will be the summer focus in New York, which is to basketball what Islamic fundamentalism is to Iran.


I highly doubt it. Highly. Plus your analogy is backwards if you want it to make sense. If you don't, then it makes perfect sense.

As an executive, Isiah Thomas is a human pratfall. But coaching always has been his passion, and when you take an objective look at his track record in Indiana, he is good at it.


Following D'Alessandro's advice, I took an objective look at Isiah Thomas's coaching career. When he took over the helm of the Indiana Pacers in 2001, he was taking over a franchise who had gone to the NBA Finals the previous year. Not only had the Pacers done that, but they also led the NBA in offensive efficiency. In Thomas's first year, there was a huge drop-off in offensive efficiency going from 108.6 in 2000 to 103.0 in 2001, which was good for 13th out of 29 teams. The Pacers finished with a 41-41 record. So Isiah did a horrible job, right? Not so fast.

The roster stability for the 2001 Indiana Pacers was only .75. What this means is 75% of the minutes in each season were played by the same players. This is the equivalent of losing 1 1/2 positions, not at all an insignificant ordeal to face. Still, he managed to take the Pacers back to the playoffs, where they bowed out to the Philadelphia 76ers that went on to the NBA Finals.

In 2002, the roster stability for the Pacers was even lower than it had been in 2001, coming in at .73. Despite that, Thomas led the Pacers to the playoffs, losing again in the first round. That time it was the New Jersey Nets who ended the Pacers' season. Like the 76ers, the Nets went on to the NBA Finals.

The year 2003 was a different beast altogether for Isiah Thomas and the Indiana Pacers. With a roster stability of .92, they basically had the same roster in 2003 that they had in 2002. As expected, the Pacers rewarded Thomas with posting a high in offensive efficency and a low in defensive efficiency over the three years of Thomas's coaching tenure. They also had a 48-34 record, again a high for an Isiah Thomas-led Pacers team. Based on point differential, the Pacers should have been 51-31, which could be used as a mark against Thomas, but could also be chalked up to bad luck.

However, the season for the Pacers ended in disappointing fashion because they lost again in the first round of the playoffs. What made this first round loss different than the others is they lost to an inferior team in the Boston Celtics. How much more improvement Thomas could have squeezed out of the Pacers if they had maintained a high level of roster stability for another year, but Thomas was fired by Larry Bird after this season and replaced by Rick Carlisle.

It's [leadership's] about imparting a vision (think Phoenix East), infusing some affinity, settling on a rotation and restoring the confidence Brown methodically shattered.


If anyone wants to get a handle on how hard a roster this was for Larry Brown to coach, the roster stability for the 2006 Knicks was .39, the equivalent of losing three positions from the 2005 Knicks. I haven't looked at the other NBA teams' roster stability, but I am pretty sure the Knicks have the lowest stability in the league.

Yes, Brown could have settled on a rotation, but this Knicks team was doomed from the start by all of Thomas's ill-conceived moves in the offseason and during the season.

Monday, July 10, 2006

Ryan Howard Spotlight

In light of his winning the All-Star Home Run Derby, I decided to do a little research into the player who is Ryan Howard. I already knew he was a very good hitter, but I had never really taken the time to look at his stats or pay much attention to the Phillies games. Some of this I blame on being in the New York sports market and being inundated with Yankees and Mets games and the rest of this I blame on the Phillies being a bad team. What I did find out about Ryan Howard was a little surprising to me.

At the All-Star Break, Howard ranks fourteenth in the major leagues in slugging percentage. Out of the top fifteen sluggers, there are only three players who have a groundball/flyball ratio of more than one: Matt Holliday (1.48 GB/FB), Ryan Howard (1.27 GB/FB), and Nomar Garciaparra (1.14 GB/FB). The other two hitters get their slugging percentages as a result of their high number of doubles; Howard is quite simply a home run hitter and one of the purest home run hitters playing right now.

While his GB/FB ratio is pretty high for a person of his home-run caliber, he more than makes up for it with a 35.9% HR/FB%, the highest among the top 15 sluggers. He also has a pretty low IFFB% of 5.1%. Howard may arrive at his slugging percentage in an odd way for his skill set, but he gets there nonetheless.

Do Managers Properly Use Their Relievers? (Pt. II)

As promised, I have updated my findings on how well managers use their relievers and if they use their best relievers in the highest leverage situations. Instead of including every single reliever, I only included relievers who had pitched at least ten innings this season.

With the added relievers, there is a small amount of good news about the overall correlations. The correlation between WXRL and Leverage increased from .499 to .522 and the correlation between WXRL and the opposing batters' season WOBA increased from -.052 to .135. While there was an increase in both correlations, neither increase was high enough to get excited about. Also, neither inspires confidence in me that managers really care about shifting their bullpen around after the games start. Yes, there are some teams who may demote a closer, but no evidence suggests that the majority of managers understand how to utilize their bullpens. Since baseball is now in an era where bullpens are used more than they ever have been, this is pretty troubling.

Unfortunately, the updated data did not treat the single teams as well. When I looked at just five relievers for teams, there were nine teams with a correlation between WXRL and Leverage over .800. With the added pitchers, there were only five teams that matched that level of success: Boston Red Sox, Minnesota Twins, Los Angeles Angels, New York Mets, and San Diego Padres.

Still leading the way are the San Diego Padres. Once again, you can chalk this up to luck if you want and say that it will even itself out over the course of the season, but let's discuss the San Diego Padres a little further. Their closer, Trevor Hoffman, has the higest leverage score (2.48) of any reliever in the majors, meaning the Padres have used him only when the game has mattered the most. Their second-best reliever has a leverage score of 1.95, which is higher than several closers for other ballclubs. Without a question, the Padres understand how to use a bullpen.

However, the Padres are not the only team that uses their relievers well. The New York Mets and the Oakland Athletics also do a good job.

Sunday, July 09, 2006

Do Managers Properly Use Their Relievers?

The question of how well managers use their relievers is one I have been asking myself for a while and a question I finally tackled. I alluded to my perception of a manager misusing his bullpen when Joe Torre sent out Kyle Farnsworth in the 8th inning to face the heart of the Boston Red Sox lineup and let Mariano Rivera, his best reliever, face the bottom of the Red Sox lineup in the 9th inning because he had to get Rivera another save.

Since I wanted to know if managers really put their best relievers against the best hitters, I did a little research. I decided to not only look at if the best relievers were pitching against the best hitters, but to also include if managers put their relievers in the highest leverage situations. The statistics I used to determine this were WXRL (Win Expectation Added Over Replacement Level), Leverage, and the collective faced batters' wOBA. wOBA is weight on-base average and is a statistic developed by Tom Tango, Michael Lichtman, and Andrew Dolphin and is a more accurate statistic than OPS because it does not treat OBP and SLG equally. For the purposes of my research, I used the approximate formula of OBP*2+SLG/3 to get wOBA.

Then I took five relievers from each of the thirty MLB teams. To choose the relievers, I used their saves, holds, and as a tiebreaker innings pitched. Relievers who had also started were excluded from the data. Hopefully, the one hundred fifty pitchers were enough to overcome any sampling errors, but during the All-Star Break I will go back and look at all the relievers in the majors, but for right now, I think the one hundred fifty relievers will do.

Getting a handle on how good managers use their bullpens required me to do a correlation between WXRL and Leverage and also WXRL and wOBA. The higher the positive correlation, the more the two variables are linked in the same direction. In simpler terms, a high positive correlation would tell us that the managers put their best relievers in the highest leverage situations and also put their best relievers against the opponents' best hitters.

The results are sobering indeed. For the one hundred fifty pitchers studied, the correlation between their WXRL and their Leverage scores is .499. The correlation between WXRL and wOBA is -.052, which is basically zero which is basically no correlation at all.

There are a few explanations for the low correlation between WXRL and Leverage. Bad luck could be the culprit or as I mentioned earlier, there could be a sampling error which we will find out when I look at all the relievers in the major leagues. Another explanation could be it takes half of a season for a manager to realize what he has in his bullpen and what his pitchers are capable of. If that is so, then it does not speak highly of managers.

Another explanation, and the one I am most likely to believe, is that managers really have no idea how to incorporate a game's leverage into selecting which reliever to call from the bullpen or they are unwilling to make minor changes in the bullpen to keep in line with their pitchers' performances. Because a player is being paid to be an 8th inning set-up man does not mean he should be left in the role if he is struggling. More imagination is necessary from baseball managers in this respect.

As for wOBA, the correlation of -.052 makes it pretty obvious that managers do not care which batters are coming up in a particular half of the inning. Instead, their only focus is on which inning it is.

Still, there is a bright side. Although overall, MLB teams use their relievers horribly, there are nine teams with a correlation above .800 in terms of WXRL and Leverage. Leading the way with a .981 correlation are the San Diego Padres. The other eight teams are the Boston Red Sox, Minnesota Twins, Los Angeles Angels, Florida Marlins, New York Mets, Washington Nationals, Cincinnati Reds, and the Houston Astros. As you can see, this list has both good teams and bad teams on it so just because a team is doing well does not mean they deploy their bullpen properly.

If the overall low correlation between WXRL and Leverage and WXRL and wOBA holds up when I extend the sample to include all receivers, then it will indicate that looking at Leverage alone to tell how managers use their bullpen is not enough. Who cares how well a manager puts his closer in high leverage situations if his set-up man is the best reliever on the team?

Stay tuned for the updated list and correlations.

Why Arroyo Has Gotten Worse

This post will be in direct contrast to the one I wrote earlier about why Bronson Arroyo is better this year because his better will not last much longer. His performance today against the Atlanta Braves where he gave up six runs in 4.3 innings pitched and threw 105 pitches is more likely to be a harbinger of bad things to come than an outlier start when this season is over for Arroyo.

One indicator of why his performance on the mound is likely to digress, and one I ignored earlier is his fielding-independent ERA, a stat created by Tom Tango to achieve a truer sense of how good a pitcher is doing. Arroyo's fielding-independent ERA is 3.73 while his "real" ERA is 2.79, an indicator that his "real" ERA will be "real(ly)" regressing.

The second red flag for Arroyo is the stress he has endured in his starts. His 2006 stress of 28 is the most he has had in three years. In 2005, he had a stress of 8 and in 2004, it was 7 so you can see just how large of a jump it has taken. The problem with Arroyo's handling by the Cincinnati Reds are the nine category 3 starts (110-121 pitches thrown) he has had this year. That is more category 3 starts than he had the last two years combined. For a pitcher who is not used to such abuse, he will no doubt see a decline in production.

Lest you think every pitcher who has a high level of stress will suffer from the effects of it, there are a number of major league pitchers who can hold up to high stress levels. The other pitches who are leading the league in pitcher abuse points (Livan Hernandez, Carlos Zambrano, Jason Schmidt, and Barry Zito) have been in the top 15 over the past 3 seasons and have still had a reasonable amount of success. The concern I have is that Arroyo will not be able to hold up.

Bill Simmons Doesn't Know The NBA

One of the most entertaining games I play is "take a sports writer's words out of context in order to poke fun at him/her." No, the game is not mature and neither is it very clever, but it amuses me and that is all that matters sometimes. The victim for today is Bill Simmons who wrote his annual NBA trade value index article. There was two errors in particular I would like to clear up lest anyone actually take Simmons's thoughts to be a reflection of reality.

You know my ongoing "I should be running an NBA team" joke? As it turns out, I'm overqualified -- I watch basketball and have common sense. Looks like the dream is dead.

Richard Jefferson (31) doesn't seem to be getting better and might want to consider changing his first name to "Ricky" or "Rico" to spruce things up...


The first sentence actually occurred later in the article than the second, but my reason for taking them out of context will become clearer by the end of this post.

For someone to suggest Richard Jefferson is not getting any better is ludicrous. It is absolutely insane especially when you consider that he is the Net who is the best at his job.

Jefferson has been a good player four of the five years he has been in the NBA, excluding his 2004-05 season. Three of his five years (minus aforementioned season and rookie season), Jefferson has been a great player, posting player win-loss percentages of .785, .819, and .838. The .838 player win-loss percentage is from the 2005-06 season where he shot his way to an amazing 117 offensive rating, the highest of his career. So much for not getting any better. His defensive rating also tied for the highest of his career at 104, but that is still below the league average (106) and when someone has an offensive rating of 117, he or she can afford to give up a few more points. Looking at the 10.8 player wins he contributed to the Nets last year compared to only 2.1 player losses, there is no reason to suggest Richard Jefferson is a legitimate superstar.

The one awful season Jefferson did have in 2004-05 was also the one where he played in only 33 contests, losing the other 49 to a wrist injury. When he did come back, he tried to do way too much, using more possessions and taking more shots than he could handle, and as a result posting the lowest offensive rating of his career (100). Last year, he returned to a more advisable usage rate and showed both himself and the Nets just how efficient a player he is.

26. Ray Allen
Props to anyone who reels off a monster contract year, signs a monster contract, then submits an even BETTER season the following year.


Ray Allen did not have a better season after he signed his monster contract. Yes, he upped his scoring average and shot even better from the field, but his 2005-06 season was still worse than his 2004-05 one, mainly because he quit playing the little defense he had played. His defensive rating went up four points from 112 to 116, even more comfortably above the league average. His player winning percentage also decreased (.657 to .579) along with his win shares (32 to 23).

Using such poor measuring tools as his eyes and common sense, Bill Simmons would no doubt be an awful NBA GM.