Last year I did a two part series on plate discipline that delved into a few statistics that I thought better represented a batter’s actual plate discipline than your traditional metrics. The stats are in for the 2006 season, so I figured it’d be worth taking another look. Here’s a quick recap of last year’s findings:

Z% (Zone Percentage) – The percentage of pitches a batter sees inside the strike zone. Correlates with walk rate (BB%) and home runs per fly ball ( HR/FB). Batters with more power are pitched more cautiously resulting in a lower Z% and a higher BB%.

OSwing (Outside Swing Percentage) – The percentage of pitches a batter swings at that are outside the strike zone. Correlates with walk rate (BB%). This year, OSwing will be represented as OSwing above the MLB average.

Contact (Contact Percentage) – The percentage of times a batter makes contact with the ball when he swings the bat. Correlates with strikeout rate (K%) and home runs per fly ball (HR/FB). Batters who can’t make contact with the ball obviously strike out more often, and batters who swing “harder” often make less contact, resulting in higher HR/FB and more strikeouts.

So, with the recap out of the way, let’s look at some year to year correlations for all three for the first time.

They all correlate well from year to year, but Both OSwing and Contact correlate extremely well. I consider OSwing about the best measure of plate discipline since not swinging at pitches outside the strike zone is pretty much the definition of plate discipline.

Seeing that it correlates so well from year to year (at least in 2005 & 2006) suggests that players do not quickly develop plate discipline. Perhaps it’s a skill that can be learned over time, but there are few players who saw drastic changes in OSwing from 2005 to 2006. Less than 10% of all players with 300 at-bats in 2005 and 2006 saw more than a 5% change in OSwing from 2005 to 2006.

Name                Dif    Name                  Dif
Andruw Jones      8.09%    Jeromy Burnitz     -5.10%
Geoff Jenkins     7.13%    Dave Roberts       -5.34%
So Taguchi        6.97%    Mark Loretta       -5.38%
Willy Taveras     6.62%    Freddy Sanchez     -5.66%
Aaron Miles       6.16%    Vladimir Guerrero  -5.71%
Scott Hatteberg   6.08%    Jay Payton         -5.89%
Joe Crede         5.92%    Kevin Mench        -6.82%
Jorge Cantu       5.13%    A.J. Pierzynski    -7.50%
Eric Chavez       5.08%    Clint Barmes       -8.39%

Contact showed an even higher correlation from year to year than OSwing, also suggesting that players don’t really change their approach from year to year. In fact, there were only 10 players who had more than a 5% change in Contact from 2005 to 2006.

Name                Dif    Name                  Dif
Corey Patterson   5.10%    Brad Wilkerson     -8.87%
Mike Piazza       5.17%    Bill Hall          -7.41%
Adam Everett      5.51%    Nick Swisher       -7.02%
Reed Johnson      5.71%    Chris Shelton      -6.37%
Troy Glaus        6.71%    Craig Monroe       -5.21%

Finally, Z% showed the least amount of correlation from year to year, but it wasn’t a poor correlation by any means. The decreased correlation I suspect is due to this metric not being entirely within the batters control. While how a batter is pitched is indicative of his various skills (mainly power and overall plate discipline), it’s still up to the pitcher to decide how to proceed.

Between both Contact and OSwing there appears to be a sort of “sweet spot” for batters. Let’s apply some filters to OSwing and see what happens. Particularly, let’s look at power batters who have a HR/FB greater than 15%.

For the first list, let’s limit the batters to those who have “considerably better” plate discipline than the rest of the league. Let’s call “considerably better” an OSwing of 5% or more than league average.

Name                  Contact     HR      HR/FB
Jason Giambi           80.97%     37     20.00%
Morgan Ensberg         74.65%     23     16.43%
Barry Bonds            85.78%     26     16.56%
Nick Johnson           84.53%     23     15.97%
Pat Burrell            79.50%     29     18.13%
Jim Thome              71.92%     42     27.81%
Chipper Jones          82.27%     26     19.12%
Frank Thomas           86.58%     39     17.41%
Carlos Beltran         84.08%     41     21.13%
Adam Dunn              70.42%     40     22.22%
Troy Glaus             75.66%     38     18.72%
Jason Bay              75.26%     35     18.82%
Nick Swisher           71.07%     35     17.86%
Austin Kearns          74.11%     24     15.29%

If we move to the next list, which I’ll use the same criteria for, but instead of batters who are “considerably better”, this will just be batters who have “above average” plate discipline (OSwing between 0% and 5% above league average).

Name                  Contact    HR     HR/FB
Josh Willingham        79.31%    26    15.85%
David Ortiz            77.92%    54    26.09%
Albert Pujols          86.24%    49    22.48%
Casey Blake            82.82%    19    16.67%
Raul Ibanez            80.26%    33    16.50%
Jim Edmonds            73.31%    19    16.81%
Travis Hafner          72.73%    42    30.22%
Lance Berkman          79.24%    45    24.59%
Phil Nevin             72.79%    22    21.57%
Jermaine Dye           78.26%    44    25.43%
Bill Hall              71.97%    35    19.44%
Brad Hawpe             73.98%    22    16.18%
Paul Konerko           82.11%    35    17.50%
Moises Alou            85.24%    22    17.46%
Andruw Jones           72.94%    41    22.04%
Richie Sexson          69.40%    34    19.32%
Mark Teixeira          79.93%    33    15.94%
Alex Rodriguez         74.27%    35    20.23%
Mike Piazza            81.88%    22    17.05%
Ken Griffey Jr.        80.70%    27    18.00%
Manny Ramirez          78.46%    35    23.49%
Miguel Cabrera         80.65%    26    15.57%
Adrian Gonzalez        79.93%    24    15.69%

Next up are the batters who have “below average” plate discipline (OSwing between 0% and 5% below league average).

Name                  Contact     HR      HR/FB
Ray Durham             88.15%     26     15.95%
Adam LaRoche           76.81%     32     21.19%
Marcus Thames          73.19%     26     17.11%
Carlos Delgado         74.39%     38     22.89%
Ty Wigginton           76.38%     24     16.90%
Carlos Lee             86.49%     37     16.09%
Ryan Howard            67.49%     58     39.46%
Mike Cuddye            76.26%     24     15.69%
Aramis Ramirez         84.28%     38     15.14%
Juan Rivera            84.38%     23     17.69%
Mark Teahen            79.05%     18     16.51%
Craig Wilson           70.20%     17     15.74%
Craig Monroe           74.79%     28     15.14%
Matt Holliday          78.84%     34     20.00%
Prince Fielder         76.55%     28     15.82%
Vernon Wells           83.45%     32     15.02%
Torii Hunter           78.02%     31     18.34%
Wilson Betemit         76.67%     18     18.00%
Preston Wilson         76.26%     17     16.67%
Miguel Tejada          84.33%     24     15.48%

And finally, the batters who have “considerably worse” plate discipline (OSwing of 5% or more below average).

Name                  Contact    HR     HR/FB
Jeromy Burnitz         72.47%    16    16.00%
Ben Broussard          77.00%    21    15.56%
Justin Morneau         81.07%    34    16.43%
Rocco Baldelli         77.09%    16    16.00%
Jacque Jones           73.82%    27    25.47%
Alfonso Soriano        73.92%    46    18.25%
Jeff Francoeur         76.47%    29    15.26%
Vladimir Guerrero      83.15%    33    16.34%

Now that you’ve seen the lists, it seems clear to me at least, that it’s preferable to have above average plate discipline. Some of the guys in the below average list are borderline, but for the most part, it’s just not as prestigious a list.

The “considerably worse” list is fascinating, since some of these players actually get away with such an aggressive approach. Vladimir Guerrero, who swings at pretty much everything, is talented enough to get away with it. Justin Morneau got away with it last year, but it’s worth noting his plate discipline didn’t improve from 2005 to 2006 and his 2005 season was, fairly forgettable. For what it’s worth, his contact rate did rise by about 3%.

It looks like high contact rates may be able to counter poor plate discipline. It would seem to me that the truly “special” players (with exceptions like Vladimir Guerrero) have that rare combination of power, plate discipline, and contact rates. You see this in players like Barry Bonds, Jason Giambi, Frank Thomas, Carlos Beltran and of course Albert Pujols. Of course, this isn’t the be-all-end-all filter, since there are a few players who sneak in like Casey Blake, who I wouldn’t consider particularly special.

So far we’ve looked at players who had at least 300 at bats, but maybe it’s possible to identify some breakout players from batters who had less than desired playing time.

Here are the players in 2006 who had an OSwing greater than -2% below average and a HR/FB over 12%. I relaxed the HR/FB filter slightly since being able to hit for power might not be quite there yet in younger players.

Name                  Contact    HR     HR/FB
Hideki Matsui          87.70%     8    12.12%
Gabe Gross             76.60%     9    14.06%
Chris Snyder           80.31%     6    12.24%
David Dellucci         73.62%    13    14.44%
Greg Norton            76.61%    17    17.89%
J.J. Hardy             85.78%     5    13.89%
Derrek Lee             81.04%     8    15.09%
Corey Koskie           77.05%    12    17.14%
Damion Easley          83.13%     9    14.06%
Aaron Guiel            77.69%     7    17.07%
Luke Scott             78.83%    10    14.71%
Jason LaRue            71.65%     8    15.69%
Wes Helms              77.88%    10    14.71%
Freddie Bynum          72.73%     4    15.38%
Ben Johnson            72.95%     4    12.90%
Michael Napoli         68.34%    16    17.20%
Chris Duncan           77.25%    22    29.33%
Scott Spiezio          80.91%    13    13.83%
Corey Hart             75.84%     9    12.16%
Russell Branyan        63.90%    18    22.50%
Dave Ross              71.51%    21    23.86%
Yorvit Torrealba       78.96%     7    16.28%
Ryan Doumit            74.43%     6    14.63%
Marlon Anderson        81.94%    12    13.79%
Daryle Ward            77.90%     7    15.22%
Josh Bard              85.16%     9    15.79%
Carlos Quentin         74.38%     9    18.00%
Joe Borchard           70.60%    10    17.54%
Cody Ross              76.85%    13    14.77%
Adam Melhuse           73.71%     4    14.81%

This is by no means a “magic bullet” list, but I’d consider it one of many starting points for narrowing down possible breakout players. There are certainly a few players on this list such as Josh Bard, Chris Duncan, Luke Scott, and others that appear to be quite promising. It’s also a reminder that injured players shouldn’t be forgotten such as Derrek Lee, Hideki Matsui, and David Dellucci.

If you were to look at the same list last year, out of about 30 players, you’d have identified Frank Thomas, Jim Thome, J.D. Drew, Mark DeRosa, Milton Bradley, Matt Murton, Ty Wigginton, Nomar Garciaparra, Marcus Thames and Curtis Granderson. So, about one third of the players ended up being at least decent to excellent sleepers.

If you’re still with me, we’ll look at one last list of filters, which I’d consider a sort of potential breakout power hitter list with already established players. I’ll filter on players with an above average OSwing, a contact rate between 70% and 85%, a HR/FB greater than 7.5%, and players all under the age of 30.

Name                  Contact    HR    HR/FB
Ryan Langerhans        76.50%     7     8.54%
Jhonny Peralta         73.48%    13     9.22%
Bobby Crosby           77.88%     9     9.09%
Jonny Gomes            70.95%    20    13.33%
Rickie Weeks           73.58%     8     9.09%
Jose Bautista          77.72%    16    11.59%
Chris Shelton          73.46%    16    12.60%
Edwin Encarnacion      80.15%    15    12.10%
Curtis Granderson      70.84%    19    11.66%
Matt Murton            83.57%    13    13.54%
Jeremy Hermida         78.88%     5     6.17%

Last year, using the same filter, yielded a group of 15 batters who hit 190 home runs in 2005 and 266 home runs in 2006. The group included Carlos Beltran, Grady Sizemore, Mark Teahen, Nick Swisher, Brad Hawpe, and others.

The bottom line is, that since stats like OSwing and Contact do correlate so well from year to year, it would definitely make sense to include them in a projection system (instead of me boring you to death with random filters). I’d say Contact is arguably better than using strikeouts, and OSwing is really unlike any of the traditional statistics that would go into projections.

There’s another article of mine up on Baseball Analysts about how the strike zone expands/contracts as the count changes and how different some pitchers take advantage of it.

“Ideally, a pitcher is going to try and get ahead in the count and when this happens the pitcher has effectively “expanded the strike zone” since the batter is now on the defensive and will be more prone to chase pitches outside the strike zone. Conversely, when a pitcher is behind in the count, a batter will be less prone to chasing bad pitches. Looking at OSwing by count this becomes fairly evident.”

You can find the rest of the article here: Expanding the Strike Zone

Last week Baseball Analysts published my article Generalities in Pitch Location, which led Tangotiger to ask the following question:

“…how often does Brandon Webb and his brothers get a GB on balls thrown down and balls thrown up the zone. That is, are they “true” groundball pitchers, who can get batters to hit the ball on the ground, because they can. Or, are they groundball pitchers, as a byproduct of them throwing the ball low?”

First let’s take a look at ground ball percentage by pitch location on a major league level.

I don’t think there are too many surprises here. The lower the pitch, the greater the chance that it will be hit on the ground. So, let’s look at what Brandon Webb‘s (extreme groundball pitcher) chart looked like the past two season, compared to say Barry Zito‘s (extreme fly ball pitcher).

Starting with Webb, we can see that no matter where he throws the ball, there’s a pretty good chance it will end up being a groundball. Zito on the other hand, will have a greater chance of inducing a fly ball despite the location of the pitch.

Now if you were to calculate a so called, “expected” groundball percentage based on the pitch locations of balls hit into play for a particular player and the league average groundball percentage for that particular pitch location, you’d see that Webb has an expected GB% of about 48%, while Zito’s is 44%.

All in all, a pretty similar “expected” groundball percentage based on pitch location and major league averages, but in reality the two couldn’t be further apart. Webb’s actual GB% the past two years is about 66% with Zito’s being around 39%.

It would seem, at least in the case of these two pitchers, that their ability (or lack there of) to induce groundballs is not entirely a function of where they throws the ball, but probably reliant on several other factors.

Thought I’d mention that I have an article on Pitch Location running this week on Baseball Analysts. Here’s a little teaser….

“How often have you heard a player attribute his success to “throwing more pitches inside,” or heard a manager say a pitcher was “hitting his spots?” Pretty much everyone talks about pitch location, but how often is it actually quantified? Thankfully, our pals over at Baseball Info Solutions tracked the x-y coordinates of nearly all 1.5 million pitches thrown the past two seasons. Let’s start by looking at the average major league pitch locations broken down by batter/pitcher handedness.”

You can find the rest of the article here: Generalities in Pitch Location

I figured I’d share a little tool that FanGraphs and Baseball Analysts have been using internally for a little while now. Basically you paste the text of an article into the text box, select whatever parameters you want, and then hit the link button.

All the properly spelled, full player names will have hyperlinks to the stats pages on FanGraphs, giving your readers the option to see more detailed stats about that particular player.

Feel free to send us your suggestions and if you have any special requests that would make using the tool easier for your particular site, don’t hesitate to ask.

To access the tool, click here . . . .

Career postseason stats have been added to the stats pages and 2002-2005 postseason game logs have been added to the game log pages

Post season stats will be updated throughout the playoffs with a 24-48 hour delay.

With the regular season finally over, it’s time to start thinking about who should be the recipient of the National League Cy Young award. A month ago, I thought Chris Carpenter was a shoe in to win for the second straight year, but over the past month, the landscape has significantly changed.

Roy Oswalt won 6 of his last 8 starts to put himself in contention while Brandon Webb righted the ship with a strong September posting a 2.43 ERA including two complete games. Then of course there are the relievers, who aren’t typically in Cy Young talks, but would the Padres be in the playoffs without Trevor Hoffman, or the Dodgers without Takashi Saito? Maybe you could even throw the Mets’ Billy Wagner into the discussion.

Just looking at the three starting pitcher candidates of Carpenter, Oswalt and Webb, they had freakishly similar seasons:

Name             W   L    Inn  ShO  CG   ERA   SO  BB  WHIP   WPA
Chris Carpenter  15  8  221.2    3   5  3.09  184  43  1.07  3.38
Roy Oswalt       15  8  220.2    0   2  2.98  166  38  1.17  4.15
Brandon Webb     16  8  235.0    3   5  3.10  178  50  1.13  3.69

How do you choose between these three? Webb has the most innings and wins. Oswalt has the best ERA and Win Probability Added (WPA). Carpenter has the most strikeouts and the best WHIP. May as flip a coin (a three sided coin). Their offenses all gave them about the same amount of run support too, so you can’t even say one of them should have more wins.

If I had a vote, my personal preference of the three would lean towards Oswalt. If you take away his one relief appearance, his WPA jumps to 4.43, which is nearly one win more than either Webb or Carpenter. Also, he’s coming off back to back 20 win seasons which were certainly Cy Young worthy, but just slightly worse than the eventual winners.

But what about those relievers? Their seasons were pretty similar too:

Name             W   L   SV   BS    Inn    ERA   SO   BB  WHIP   WPA    LI
Takashi Saito    6   2   24    2    78.1  2.07  107   23  0.91  4.09  1.50
Trevor Hoffman   0   2   46    5    63.0  2.14   50   13  0.97  4.04  2.08
Billy Wagner     3   2   40    5    72.1  2.24   94   21  1.11  3.85  1.88

This is also a tough group of pitchers to pick a winner from. Even though Saito had about 20 less saves than Hoffman or Wagner, he still managed to top them both in WPA, not to mention his 107 strikeouts are pretty off the charts. Hoffman was used in the most difficult situations of the three, according to his Leverage Index (LI) and he did lead the majors in saves. Wagner falls a bit short of both Hoffman and Saito, but he still had a stellar season, though probably not Cy Young worthy.

If I had to choose one I’d go with Hoffman since he’s pitched in more pressure packed situations than any of the three and he’s been nothing but stellar all season long. Saito should probably take home the NL Rookie of the Year award, but that’s an entirely different discussion.

So for me at least, it comes down to either Oswalt or Hoffman and I’m seriously torn between the two of them. I really think Oswalt will (and should) win a Cy Young award eventually, but I’d really love to see Hoffman win now, especially in a year where there’s no clear cut starting pitcher. Capturing the career lead in saves, leading his team to the playoffs, and winning the Cy Young award, all in the twilight of his career, sure would make a feel good story.

A number of Win Probability aficionados have pointed out that So Taguchi was inacurately credited with -0.193 wins for his 8th inning lead-off walk. The problem has now been fixed and he has been accurately credited with 0.096 wins.

It’s worth noting that in this same game, Albert Pujols‘ home run was worth 0.624 wins and it was the 4th time this season he’s had a single at-bat worth more than 0.5 wins. He’s the only player, in the five years of win probability data I have, that has 4 hits worth over 0.5 wins in a single season. Since 2002, he’s had 6 such regular season hits, which is also the most in the majors. Make it 7 if you count his one post-season hit worth 0.716 wins:

Playoff Win Probability graphs have been added for the 2002-2005 seasons. Relive the joy/pain of the 2003 Aaron Boone home run, or see just how close the Giants were to winning it all in 2002.

From now until the playoffs we’ll be updating the various sections of the site with playoff stats to compliment our regular season stats. Also, don’t forget that FanGraphs will continue to have daily updated Win Probability graphs and all the usual stats throughout the 2006 playoffs.

Tangotiger is doing his fourth annual fielding survey: The 2006 Scouting Report by the Fans for the Fans. The balloting ends soon, so don’t forget to fill out a ballot before the 2006 “Globe Gloves” are awarded.

As I was browsing the new leaderboards, I noticed that Albert Pujols has the 10th fewest strikeouts among qualified players with only 43. That’s pretty damn impressive for a guy who’s hit 45 home runs this season. Actually, it’s a little more than impressive as there’s only been six other players who have more home runs than strikeouts and have hit over 40 home runs.

Name            Season       HR       SO
---------------------------------------------
Mel Ott           1929       42       38
Lou Gehrig        1934       49       31
Lou Gehrig        1936       49       46
Joe DiMaggio      1937       46       37
Johnny Mize       1947       51       42
Johnny Mize       1948       40       37
Ted Kluszewski    1953       40       34
Ted Kluszewski    1954       49       35
Ted Kluszewski    1955       47       40
*Barry Bonds      2004       45       41

* - denotes MVP Season

Only Barry Bonds has accomplished the 40-plus home run season with fewer strikeouts since 1955 and he’s the only one to win an MVP award in the same season. Hitting 30 home runs with fewer strikeouts has been slightly more rewarding in the MVP department and is still a very exclusive club.

Name            Season       HR       SO
---------------------------------------------
Ken Williams      1922       39       31
Lefty O'Doul      1929       32       19
Al Simmons        1930       36       34
Joe DiMaggio      1938       32       31
*Joe DiMaggio     1939       30       20
Joe DiMaggio      1940       31       30
Ted Williams      1941       37       27
*Joe DiMaggio     1941       30       13
Willard Marshal   1947       36       30
*Stan Musial      1948       39       34
Joe DiMaggio      1948       39       30
Andy Pafko        1950       36       32
Yogi Berra        1952       30       24
Yogi Berra        1956       30       29
Ted Kluszewski    1956       35       31

* - denotes MVP Season

Is there a point to this? Not really, but it’s fun trivia and maybe fodder for your MVP discussions.

And speaking of the MVP, a few days ago (September 9th), Ryan Howard briefly overtook Pujols for the major league lead in WPA. Before that, Pujols led the majors in WPA since April 16th (145 days). Last night’s 2-run walk-off double put Pujols back on top by a margin of 0.73 wins.

I thought I’d give everyone a little sneak peak at our long overdue leaderboards. The 4 different stat pages for batters and pitchers include pretty much all of the stats in the usual player pages. All the stats are sortable; just click on the stat name and it will sort in ascending order first and then if you click it again, it will sort in descending order.

The leaderboards are not integrated into the regular site navigation yet, but you can access them if you click here.

If you find any problems or errors, please let us know and feedback (bad or good) is always welcome.

After being down 10-1 after the first inning, the Indians pulled off the comeback of the year to win the game 15-13 in extra innings. This is one of the craziest win probability graphs I’ve seen this season.

It even bests the August 9th comeback last season, when the Indians overcame a 5 run deficit by scoring 11 runs in the top of the 9th.

Browsing the player captions in my Sportsline fantasy league, I noticed that they had this to say about Miguel Cabrera:

News: 3B Miguel Cabrera has been Mr. Clutch for the Marlins all season, but he has turned it up in the second half. Cabrera had batted .395 with runners in scoring position since the All-Star break going into Monday, fourth in the NL.

Cabrera is in fact #1 by a long shot for the Marlins with a 3.39 WPA this season. This ranks him 14th in baseball and 7th in the National League. Since the All-Star break he’s wracked up a 1.13 WPA, good for 32nd in baseball during that same time period.

Yet since the All-Star break, part time 1st-baseman and pinch hitter, Wes Helms has a WPA of 0.93, nearly as good as Cabrera, with Josh Willingham not far behind with 0.89. Cabrera and Helms have had consistent positive contributions compared to Willingham, whose main contribution was a 2-run walk off homer against the Mets on August 1st. That single shot was worth 0.70 WPA, nearly all of Willingham’s post All-Star value.

Cabrera’s actual Clutchiness for the season is -0.35, so while he’s certainly been the most valuable Marlin, he’s hardly been contributing above and beyond what a “non-clutch” player would with the same stats. Hanley Ramirez actually leads the Marlins this season with 0.75 Clutchiness, while since the All-Star break, Willingham leads the team with a 0.81 Clutchiness.

Joe Crede is finally hitting the way Baseball America thought he would. Remember, when Crede was a 24-year-old third baseman in AAA Charlotte, he batted .312/.359/.571 with 24 home runs in just 359 at bats. His minor league career was filled with honors (twice the MVP of his league and twice the White Sox’s minor league player of the year) and an All-Star major league career seemed inevitable.

Before this year, it hadn’t quite happened. Over the last three full years of play, he’s batted .261, .239 and .252 with a high of 22 home runs. His OPS (On-Base plus Slugging) was below the league average each year, as was his batting WPA . Despite his fine glove and World Series heroics, Crede was considered a disappointment by most White Sox fans.

Something has clicked for Joe this year. He’s batting .298/.333/.545 and he’s already set a career high with 25 home runs. He’s creating 6.8 runs a game and his batting WPA is 1.53, making him three wins better than average.

As you can see on the following graph of his Runs Created per Game, he’s been consistently fine this year, suggesting he truly has moved up to another level of production.

How has he done it? He’s striking out less and hitting more flyballs, without losing any power. Crede has always managed to put the bat on the ball, but this year he’s been particularly adept at it:

When a player makes better contact, you might expect him to give up something in power, but 13% of Crede’s outfield flyballs have been home runs, the same as last year. His home run totals are up because he’s hitting more outfield flies:

The White Sox’s Jermaine Dye is also clearly having a career year. He’s creating 9.7 runs a game and his WPA is 4.25. But his production is driven by a big jump in his BABIP (from .286 last year to .353 this year) and flyball production (17% home runs last year to 25% this year). No one should expect him to maintain that pace.

Joe Crede’s story appears to be different. Of course, he could also go back to his old self the rest of this year and next year, but the stats indicate something more permanent. At the age of 28, Joe Crede is finally meeting the expectations folks had for him.

Quite a few feature additions just went into production.

-First off, WPA is no longer expressed as a percentage. Every player still has the same value, it’s just 100 times less.

-WPA is now displayed in each player’s game log and all the dates in the game logs are linked back to the correct Win Probability graph.

-There’s a new table for both batters and pitchers in the player stat pages that include the following Win Probability & Leverage stats:

WPA: Win Probability Added.
-WPA: The total of a player’s negative contributions towards their team’s win/loss.
+WPA: The total of a player’s positive contributions towards their team’s win/loss.
pLI: Average Leverage on a plate-appearance basis.
inLI: Average Leverage when a pitcher starts an inning.
gmLI: Average Leverage when a pitcher enters the game.
exLI: Average Leverage when a pitcher exits the game (game ends not included).
Pulls: Number of times a pitcher has been pulled from a game before it ended.
G: The number of games pitched in.
phLI: Average Leverage when pinch-hitting.
PH: Pinch-hitting opportunities.
OBP Wins: Player’s wins in a context-neutral environment.
Clutchiness: Difference between WPA and a Leverage adjusted OBP Wins.

For more information about these stats, take a look at the following links:

-Tangotiger’s Critical Situation Series: Part 1, Part 2, Part 3.
-Clutchiness: The Blog.
-The One About Win Probability.

If you notice any problems, please let us know and we’ll fix them as quickly as possible.

In the past, navigating you’re way through the Win Probability graphs was probably a bit of a pain since you had to go game by game until you got to the correct date. This was finally fixed today with the addition of a calendar where you can easily go directly to the game you’re looking for.

Additionally, the calendar is color coded so you can see which games were won (green) and lost (red) on each particular day they played. This may bring back some painful memories of some of the worst months in recent history like the Tigers’ 3-win April in 2003, or the Orioles 24-loss September back in 2002.

All the best months are in there too, such as the Athletics’ 17 straight wins to finish August in 2002 and the Red Sox’s 21-win August in 2004. Try it out and let us know what you think!

Update: It should be working for mac users now, but the formatting is going to be a bit off in safari until I can figure out what’s causing the issue.

You may have noticed that the Win Probability section has changed slightly. Thanks to our stats provider, Baseball Info Solutions (BIS), we now have 2002-2006 game logs, which we have used to compile the 2002-2006 Win Probability graphs and stats. Note that we were not using any of BIS’s data previously to compile Win Probability stats and you may notice that a few of the values have changed.

The data BIS provides is much more accurate than our previous data source and as a result there should be few-to-no errors. If you do happen to find an error, chances are it will be corrected the next day.

Hopefully there will be quite a few updates in the next week or two which should include:

- Play-by-Play for each game with Win Probability stats.

- Additional leverage statistics for relievers and pinch hitters.

- Win Probability +/- breakouts.

- Season Leaderboards. (FINALLY!)

- All Win Probability and Leverage stats in the regular player stats pages and game logs.

In the meantime, the 2002-2005 Win Probability data looks quite interesting, especially if you’re still debating the 2005 AL MVP race.

A week ago, the Rangers and Brewers swapped leftfielders and a few other players. Texas acquired Carlos Lee and minor leaguer Nelson Cruz for Kevin Mench, Laynce Nix, Francisco Cordero and a minor leaguer. At the time, I thought Cordero (an A reliever most of his career) was the key to the deal, and I called Mench a “poor man’s Lee.”

Most Internet posters seem to think that the Rangers got the best of this deal. For instance, ESPN’s Keith Law opined…

Unless the Brewers have a second move in mind involving Mench, Cordero, or Turnbow, it’s hard to see how this is a good return on arguably the most attractive position player on the trade market.

But the erstwhile MGL, in this thread feels that once you include fielding and baserunning, Mench is actually a better player than Lee — and he’s cheaper to boot. So I thought it would be fun to compare the two. Let’s start with a basic Runs Created graph, showing each player’s Runs Created over their career:

You’ve got to say that the Brewers picked a fine time to trade Lee, who is having the best year of his career and will be a free agent at the end of the season. Mench isn’t having as good a year, but his production was very similar to Lee’s prior to 2006.

Breaking down their stats a little, Mench and Lee have exhibited the same level of on-base skill throughout the years…

..but the difference between the two this year has been their power.

Almost 18% of Lee’s outfield flies have been home runs, compared to a previous average of about 13%. Given his track record, I’d say it’s highly unlikely he will maintain that rate for the rest of the year.

In comparison, Mench has kept his home run/outfield fly rate at about 11% (aided by his old home park), but his 2006 slugging decline is more related to a higher groundball rate (42% vs. a previous career average of 36%). That could be a disturbing trend, because changes in batted ball rates can signal abrupt changes in a batter’s true performance. At least, that’s my hypothesis. Maybe I’ll test that someday…

If you had compared Lee and Mench at the end of last year, you might have said that Lee has a slight edge in power but not much else. Does this year–particularly Mench’s increase in groundballs–change that assessment? I will leave that to you.

As for fielding, Mench ranked 15th among leftfielders last year and Lee ranked 23rd, according to John Dewan’s Fielding Bible. Lee truly looks like a bad baserunner, however. The Hardball Times Annual gave him -2.8 baserunning runs and Mench received a positive 2.2.

Overall, there appears to be about a 10-run edge for Mench in fielding and baserunning (equal to one win) and prior to this year, you might have rated Lee and Mench relatively even in batting prowess. Add in the fact that Mench is younger and won’t be a free agent for two years, and you might actually believe that Mench really isn’t that “poor” a relation to Lee. In the meantime, watch his groundball rate.

I’ve received a few requests to do Win Probability charts for the 2004 Red Sox-Yankees ALCS. Enjoy!

(Click Image for Full Size)