It's been a long disappointing season with few pleasant memories for Tigers fans but there might be some consolation prizes if players end the season on high notes. First, Magglio Ordonez has a chance to be the only Tiger other than Ty Cobb to win back to back batting titles. He's a bit of a long shot with three batters ahead of him but is only seven points behind the leader and coming strong:
Dustin Pedroia .328
Milton Bradley .327
Joe Mauer .323
Magglio Ordonez .321
Miguel Cabrera has a chance to be the Tigers first home run leader since Cecil Fielder hit 44 in 1991. With Cabrera on a roll and Carlos Quentin out for the season, he has a legitimate shot:
Carlos Quentin 36
Miguel Cabrera 33
Alex Rodriguez 33
Jermaine Dye 32
With 80 RBI in his last 82 games, Cabrera also has a shot at the RBI crown:
Josh Hamilton 124
Justin Morneau 119
Miguel Cabrera 116
With Carlos Crawford out for the season, Curtis Granderson has the triples title pretty much sewn up for the second straight year. He has the most triples (36) in back to back seasons for any Tiger since Sam Crawford in 1913-1914 (49) since Sam Crawford in 1913-14. These are the 2008 leaders:
Curtis Granderson 13
Carlos Crawford 10
Alex Rios 9
Brian Roberts 9
Thursday, September 11, 2008
Sunday, September 07, 2008
Offense versus defense again
Yesterday I examined the importance of offense versus defense (pitching/fielding) in getting into the playoffs. Today, I'll take an even simpler approach to the same question. Once again, I ranked each team by how many runs they scored (offense) and how many they allowed (defense). Then I looked to see how often they ranked better offensively/ defensively. Here are the results for 128 playoff teams since 1988:
offense 47
defense 68
ties 13
Now for the World Series teams those years:
offense 8
defense 25
ties 5
So, the conclusions are the same as before:
Pitching/fielding is a little more important than offense in getting into the playoffs but it is not at all uncommon for teams with better offenses to make the playoffs.
Pitching/defense becomes more important for World series teams but it's still possible for a better offensive team to win the pennant.
offense 47
defense 68
ties 13
Now for the World Series teams those years:
offense 8
defense 25
ties 5
So, the conclusions are the same as before:
Pitching/fielding is a little more important than offense in getting into the playoffs but it is not at all uncommon for teams with better offenses to make the playoffs.
Pitching/defense becomes more important for World series teams but it's still possible for a better offensive team to win the pennant.
Saturday, September 06, 2008
Good pitching beats good hitting all the time?
You've heard it before: Good pitching beats good hitting all the time. Pitching and fielding wins pennants. Pitching is 90% of the game. So, I wanted to examine the relative importance of offense and pitching/fielding in getting into the playoffs. This sort of thing has been done before by Bill James, Pete Palmer, Baseball Prospectus and others but I haven't seen it done for a while so I wanted to revisit the question.
I didn't want to do a complicated analysis involving multiple regression or anything like that . I wanted to keep it simple and intuitive. What I did was rank every team each year since 1988 (except the strike year of 1994) based on offense (runs scored) and defense or pitching/fielding (runs allowed). I then classified each team's offense as good, OK or bad based on their rank. If they finished in the top third of the league, then they were good. If they finished in the middle third, then they were OK. If they were in the bottom third, they were classified as bad. I classified team pitching/fielding the same way based on runs allowed.
Crossing the offense classification (good, ok, bad) with the defense classification (good, ok, bad),
I got the nine categories (good offense and good defense, ok offense and good defense, etc) shown in Table 1 below. For example, the 2007 Indians were sixth in the American League in offense in 2007 and third in defense so they went into the OK offense/good defense category.
There were 128 playoff teams since 1988 and 47 of them had both strong offense and defense. The next most frequent categories were OK offense and good defense (35) followed by good offense and OK defense (25). The other combinations were less common.
What can we conclude from this data? More than a third of the teams which made the playoffs had both good hitting and pitching/fielding so it's important to try to build both components. Second, it IS more common for an OK offense/good pitching and fielding team to make the playoffs than a good offense/OK pitching and fielding team but it's not THAT much more common. There is more than one way to build a team for post-season. What about teams that have bad offense/good defense or good offense/bad pitching. Well, neither is a particularly good way to build a team but one is not worse than the other.
Table 1: Offense and Defense of playoff teams (1988-2007)
The next question you may have is whether good pitching/fielding was more important for teams that made the World Series. Table 2 below is the same as Table 1 except it only includes teams that made the World Series. Again, the most common classification was the good/good category - 18 of the 38 teams. The defensive side of the ball did seem a bit more important for World Series teams as 13 teams had OK offense and good defense as opposed to just 5 teams with good offense and OK defense.
So, we can conclude that a lack of pitching/fielding is worse than a lack offense for teams aspiring to get into the World Series. However, being strong in both offense and pitching/fielding is even more important for winning pennants than it is for getting into the playoffs.
Table 2: Offense and Defense of World Series teams (1988-2007)
I didn't want to do a complicated analysis involving multiple regression or anything like that . I wanted to keep it simple and intuitive. What I did was rank every team each year since 1988 (except the strike year of 1994) based on offense (runs scored) and defense or pitching/fielding (runs allowed). I then classified each team's offense as good, OK or bad based on their rank. If they finished in the top third of the league, then they were good. If they finished in the middle third, then they were OK. If they were in the bottom third, they were classified as bad. I classified team pitching/fielding the same way based on runs allowed.
Crossing the offense classification (good, ok, bad) with the defense classification (good, ok, bad),
I got the nine categories (good offense and good defense, ok offense and good defense, etc) shown in Table 1 below. For example, the 2007 Indians were sixth in the American League in offense in 2007 and third in defense so they went into the OK offense/good defense category.
There were 128 playoff teams since 1988 and 47 of them had both strong offense and defense. The next most frequent categories were OK offense and good defense (35) followed by good offense and OK defense (25). The other combinations were less common.
What can we conclude from this data? More than a third of the teams which made the playoffs had both good hitting and pitching/fielding so it's important to try to build both components. Second, it IS more common for an OK offense/good pitching and fielding team to make the playoffs than a good offense/OK pitching and fielding team but it's not THAT much more common. There is more than one way to build a team for post-season. What about teams that have bad offense/good defense or good offense/bad pitching. Well, neither is a particularly good way to build a team but one is not worse than the other.
Table 1: Offense and Defense of playoff teams (1988-2007)
| Offense | Pitching/Fielding | Number | Percent |
| Good | Good | 47 | 36.7 |
| OK | Good | 35 | 27.3 |
| Good | OK | 25 | 19.5 |
| OK | OK | 7 | 5.5 |
| Good | Bad | 6 | 4.7 |
| Bad | Good | 7 | 5.5 |
| Bad | OK | 1 | 0.8 |
| OK | Bad | 0 | 0.0 |
| Bad | Bad | 0 | 0.0 |
The next question you may have is whether good pitching/fielding was more important for teams that made the World Series. Table 2 below is the same as Table 1 except it only includes teams that made the World Series. Again, the most common classification was the good/good category - 18 of the 38 teams. The defensive side of the ball did seem a bit more important for World Series teams as 13 teams had OK offense and good defense as opposed to just 5 teams with good offense and OK defense.
So, we can conclude that a lack of pitching/fielding is worse than a lack offense for teams aspiring to get into the World Series. However, being strong in both offense and pitching/fielding is even more important for winning pennants than it is for getting into the playoffs.
Table 2: Offense and Defense of World Series teams (1988-2007)
| Offense | Pitching/Fielding | Number | Percent |
| Good | Good | 18 | 47.4 |
| OK | Good | 13 | 34.2 |
| Good | OK | 5 | 13.2 |
| OK | OK | 2 | 5.3 |
Thursday, September 04, 2008
What's Right with Curtis Granderson?
In the middle of June, I wrote an article entitled "What's wrong with Curtis Granderson?". On June 14, he was batting .240/.297/.431 and some feared that 2007 might have been a career year. I looked at the stats and concluded that he was being less aggressive than he had been in 2007. He was also hitting fewer line drives and had a very low batting average on balls in play (which I guessed was just bad luck). I thought he would improve as the season went along and he has - even more than I expected.
Table 1 shows that he has now caught up to his 2007 pace in most areas. His batting average (.306) and OPS (.903) are similar to last year and his OBP is higher (.389 in 2008 vs. .361 in 2007). The only area where he is a little behind last year's pace is slugging average (.514 vs .552) but I'll trade some slugging for OBP especially for a lead off hitter.
Table 1: Curtis Granderson's standard stats
Table 2 (abstracted from Fan Graphs) shows that his walk rate has dramatically improved - 11.5% in 2008 vs. 7.8% in 2007. That, of course, is a great thing for a lead off hitter. His strikeout rate (17.8%) is the best of his career by a significant margin. The next three columns indicate that he might be taking a somewhat different approach this year. He has averaged 4.24 pitches per plate appearance this year compared to 3.98 in in 2007. He is also swinging at fewer balls outside the zone (OSWING%) and inside the zone (ZSWING%) this year than last. This all indicates that he may be less aggressive at the plate this year compared to 2007. That can be a good thing or a bad thing but it seems to be working for him. The most positive result here is that his contact rate is at about league average this year (80.4%) after being 70.8% two years ago. It's very rare to see that kind of improvement on that particular stat.
Table 2: Curtis Granderson's plate discipline stats
A look at his batted ball data in Table 3 shows that his BABIP (.344) has gone back up to a normal level (He was at .250 earlier in the season). His ground ball rate (40.7) is still up and line drive rate (18.8) still down from last year which probably explains his decrease in power.
Table 3: Curtis Granderson's batted ball data
His hit charts on MLB.COM for 2007 and 2008 show that, although he is still pull hitter, he hitting the ball to the opposite field a little more this year. Just based on memory, I think that he is less of a pull hitter the last couple of months than he was earlier in the season and I believe that's one of the reasons for his second half surge.
Finally, the most important improvement for Curtis this year is that he is no longer hopeless against left-handers. After batting .160 against southpaws in 2007, he is up to .277 this year.
So, all is well for Granderson offensively. There will be no quadruple twenty this year but he has become a more disciplined and complete hitter which bodes well for the future.
Table 1 shows that he has now caught up to his 2007 pace in most areas. His batting average (.306) and OPS (.903) are similar to last year and his OBP is higher (.389 in 2008 vs. .361 in 2007). The only area where he is a little behind last year's pace is slugging average (.514 vs .552) but I'll trade some slugging for OBP especially for a lead off hitter.
Table 1: Curtis Granderson's standard stats
Year | PA | BA | OBP | SLG | OPS | OPS+ |
| 2005 | 174 | .272 | .314 | .494 | .802 | 113 |
| 2006 | 679 | .260 | .335 | .438 | .773 | 98 |
| 2007 | 676 | .302 | .361 | .552 | .913 | 136 |
| 2008 | 526 | .306 | .389 | .514 | .903 | 137 |
Table 2 (abstracted from Fan Graphs) shows that his walk rate has dramatically improved - 11.5% in 2008 vs. 7.8% in 2007. That, of course, is a great thing for a lead off hitter. His strikeout rate (17.8%) is the best of his career by a significant margin. The next three columns indicate that he might be taking a somewhat different approach this year. He has averaged 4.24 pitches per plate appearance this year compared to 3.98 in in 2007. He is also swinging at fewer balls outside the zone (OSWING%) and inside the zone (ZSWING%) this year than last. This all indicates that he may be less aggressive at the plate this year compared to 2007. That can be a good thing or a bad thing but it seems to be working for him. The most positive result here is that his contact rate is at about league average this year (80.4%) after being 70.8% two years ago. It's very rare to see that kind of improvement on that particular stat.
Table 2: Curtis Granderson's plate discipline stats
| Year | BB% | K% | P/PA | OSWING% | ZSWING% | Contact% |
| 2005 | 5.8 | 26.5 | 4.07 | 21.4 | 59.3 | 77.4 |
| 2006 | 10.0 | 29.2 | 4.08 | 20.4 | 63.2 | 70.8 |
| 2007 | 7.8 | 23.0 | 3.98 | 23.4 | 62.4 | 77.8 |
| 2008 | 11.5 | 17.8 | 4.24 | 19.0 | 58.2 | 80.4 |
A look at his batted ball data in Table 3 shows that his BABIP (.344) has gone back up to a normal level (He was at .250 earlier in the season). His ground ball rate (40.7) is still up and line drive rate (18.8) still down from last year which probably explains his decrease in power.
Table 3: Curtis Granderson's batted ball data
| Year | BABIP | GB% | LD% | FB% | HR/FB |
| 2005 | .324 | 45.4 | 18.5 | 36.1 | 11.7 |
| 2006 | .337 | 38.9 | 22.2 | 38.9 | 10.9 |
| 2007 | .362 | 34.2 | 21.0 | 44.8 | 12.5 |
| 2008 | .344 | 40.7 | 18.8 | 40.5 | 10.5 |
His hit charts on MLB.COM for 2007 and 2008 show that, although he is still pull hitter, he hitting the ball to the opposite field a little more this year. Just based on memory, I think that he is less of a pull hitter the last couple of months than he was earlier in the season and I believe that's one of the reasons for his second half surge.
Finally, the most important improvement for Curtis this year is that he is no longer hopeless against left-handers. After batting .160 against southpaws in 2007, he is up to .277 this year.
So, all is well for Granderson offensively. There will be no quadruple twenty this year but he has become a more disciplined and complete hitter which bodes well for the future.
Tuesday, September 02, 2008
WPA Leaders
Fans often complain that stats like OPS and runs created don't take into account the game situation. For example, a walk-off home run is more valuable to a team than a home run when they are up by 12 runs but they both count the same in the statistics. The Win Probability Added (WPA) statistic does consider game situations and gives hitters credit based on the effect their at bats have on their team's probability of winning. These probabilities vary depending on the game score, the runners on base and the number of outs before and after each play. They are based on the results of thousands of games worth of data looking at every possible situation over and over.
More concretely, WPA works as follows. Suppose the Tigers are down by one run with a runner on second and two out in the bottom of the ninth. Using the win expectancy finder, created by the site walkoff balk, they have a .129 (or 12.9%) expectancy of winning. Now suppose, Curtis Granderson singles to tie the game. The probability of winning is now .570. So, Granderson increased the probability of the Tigers winning the game by .570-.129 = .441 with his single.
In another game, the Tigers are up 5-0 with the bases empty and nobody out in the bottom of the eight. Theoretically, this means that they have a probability of .997 of winning the game. In this situation, Gary Sheffield hits a solo homer to make it 6-0. The win probability is now .998 meaning that the home run added only .001 to the win probability. So Sheffield's homer counts a lot less than Granderson's single.
A player can also decrease his team's probability of winning. For example, the Tigers are losing 2-1 in the bottom of the ninth with a runner on first and nobody out. In this case, they have a .320 probability of winning. Then Edgar Renteria hits into a double play which makes probability of winning to .035. So, the double play decreased the probability of winning by .320-.035=.285.
If you add up all the gains and losses for all of a player's at bats, you get his WPA. The good thing about WPA is that is may give a more accurate measure of a player's value to his team during a season. The drawback is that it is not predictive. Thus, if you want to determine how well a player will do in the future, a situation independent statistic such as runs created would be more appropriate.
Table 1 lists the American League WPA leaders as of September 1. The Tigers are listed in Table 2. These data were abstracted from the Fan Graphs web site.
Table 1: American League WPA leaders
Ramirez Bos. 3.94
Quentin, Chi 3.89
Morneau, Min 3.77
Mauer, Min 3.48
Hamilton, Tex 3.43
Sizemore, Cle 3.29
Pena, TB 3.12
Bradley, Tex 2.99
Pedroia, Bos 2.79
Cabrera, Det 2.68
Table 2: Tigers WPA leaders
Cabrera 2.68
Granderson 2.42
Guillen 1.61
Joyce 1.27
Thames 0.26
Polanco -0.11
Median -0.20
Ordonez -0.32
Inge -0.58
Sheffield -1.21
Renteria -2.26
Tables 3 and 4 below present the Runs Created Per Game leaders for the American League and the Tigers respectively. Looking at Tables 2 and 4 for the Tigers, we can see that Magglio Ordonez has been below average according WPA but above average according to runs created. This indicates that he has not performed as well in high leverage situations as he has in lower impact spots. Since this has not been the case for him in the past, I would say it's just a case of bad luck rather than a lack of ability to perform in the clutch. Conversely, Miguel Cabrera ranks higher on WPA than he does on Runs Created.
Table 3: American League Runs Created Per Game leaders
Bradley, Tex 10.31
Rodriguez, NY 8.40
Huff, Bal 8.15
Quentin, Chi 8.06
Sizemore 8.03
Youkilis, Bos 8.02
Drew, Bos 8.00
Markakis, Bal 7.77
Ramirez, Bos 7.71
Granderson, Det 7.58
Table 4: Tigers Runs Created Per Game leaders
Granderson 7.58
Joyce 7.12
Cabrera 6.38
Guillen 6.02
Ordonez 5.94
Polanco 5.40
Thames 5.16
Median 4.80
Inge 4.58
Sheffield 4.04
Renteria 3.76
More concretely, WPA works as follows. Suppose the Tigers are down by one run with a runner on second and two out in the bottom of the ninth. Using the win expectancy finder, created by the site walkoff balk, they have a .129 (or 12.9%) expectancy of winning. Now suppose, Curtis Granderson singles to tie the game. The probability of winning is now .570. So, Granderson increased the probability of the Tigers winning the game by .570-.129 = .441 with his single.
In another game, the Tigers are up 5-0 with the bases empty and nobody out in the bottom of the eight. Theoretically, this means that they have a probability of .997 of winning the game. In this situation, Gary Sheffield hits a solo homer to make it 6-0. The win probability is now .998 meaning that the home run added only .001 to the win probability. So Sheffield's homer counts a lot less than Granderson's single.
A player can also decrease his team's probability of winning. For example, the Tigers are losing 2-1 in the bottom of the ninth with a runner on first and nobody out. In this case, they have a .320 probability of winning. Then Edgar Renteria hits into a double play which makes probability of winning to .035. So, the double play decreased the probability of winning by .320-.035=.285.
If you add up all the gains and losses for all of a player's at bats, you get his WPA. The good thing about WPA is that is may give a more accurate measure of a player's value to his team during a season. The drawback is that it is not predictive. Thus, if you want to determine how well a player will do in the future, a situation independent statistic such as runs created would be more appropriate.
Table 1 lists the American League WPA leaders as of September 1. The Tigers are listed in Table 2. These data were abstracted from the Fan Graphs web site.
Table 1: American League WPA leaders
Ramirez Bos. 3.94
Quentin, Chi 3.89
Morneau, Min 3.77
Mauer, Min 3.48
Hamilton, Tex 3.43
Sizemore, Cle 3.29
Pena, TB 3.12
Bradley, Tex 2.99
Pedroia, Bos 2.79
Cabrera, Det 2.68
Table 2: Tigers WPA leaders
Cabrera 2.68
Granderson 2.42
Guillen 1.61
Joyce 1.27
Thames 0.26
Polanco -0.11
Median -0.20
Ordonez -0.32
Inge -0.58
Sheffield -1.21
Renteria -2.26
Tables 3 and 4 below present the Runs Created Per Game leaders for the American League and the Tigers respectively. Looking at Tables 2 and 4 for the Tigers, we can see that Magglio Ordonez has been below average according WPA but above average according to runs created. This indicates that he has not performed as well in high leverage situations as he has in lower impact spots. Since this has not been the case for him in the past, I would say it's just a case of bad luck rather than a lack of ability to perform in the clutch. Conversely, Miguel Cabrera ranks higher on WPA than he does on Runs Created.
Table 3: American League Runs Created Per Game leaders
Bradley, Tex 10.31
Rodriguez, NY 8.40
Huff, Bal 8.15
Quentin, Chi 8.06
Sizemore 8.03
Youkilis, Bos 8.02
Drew, Bos 8.00
Markakis, Bal 7.77
Ramirez, Bos 7.71
Granderson, Det 7.58
Table 4: Tigers Runs Created Per Game leaders
Granderson 7.58
Joyce 7.12
Cabrera 6.38
Guillen 6.02
Ordonez 5.94
Polanco 5.40
Thames 5.16
Median 4.80
Inge 4.58
Sheffield 4.04
Renteria 3.76
Subscribe to:
Posts (Atom)
