Freaky Pitching Leaderboards

We keep track of a number of unusual baseball stats at The Hardball Times, based on the data sent to us by Baseball Info Solutions, including batted ball stats (ground ball, fly ball, line drive) for each batter and pitcher. We think these stats provide a little extra insight into what’s happening in the baseball world.

You can find many of these stats in our stats section. We’re working on a sortable version (similar to our new Win Shares format) so you can construct your own leaderboards. In the meantime, however, I’ve constructed some special THT-only leaderboards, including some new stats. Pitchers today, batters Thursday.

These leaderboards include only pitchers who have faced at least 149 batters—a total of 152 pitchers or about five per team. Stats are based on games through last Friday, which marked the end of the first third of the season. There are four Leaderboards in all. (If you like, you can start with more conventional leaderboards on the Major League Baseball site).

Expected DER

Lately I’ve been reading a lot of articles claiming that you can judge a team’s fielding prowess by its Defense Efficiency Ratio (DER). I’m not so sure about that.

DER tracks the number of batted balls that are caught for outs by fielders, not including home runs, so it seems as though DER should be a useful fielding stat. Pitchers, however, can have a lot of impact on whether a batted ball is caught or not. In fact, I’ve conducted research in the past that indicates that fielders are responsible for at most 50% of variance in DER between teams. How can this be?

There are two issues:

  • The batted ball type yielded by a pitcher can have a big impact on DER. Line drives are converted into outs only about 25% of the time. For ground balls, the percentage is 72%; that figure is 75% for outfield flies and 97% for infield flies.
  • Beyond that, batted balls fall into different zones on the field, some of which are within a fielder’s normal range and others that aren’t. Without zone data, it is impossible to use statistics to judge whether or not a batted ball might have been fairly caught by a fielder.

I’ve constructed a stat that attempts to address the first of these two issues. It’s called Expected DER.

To create Expected DER, I looked at all 2004 pitchers with at least 50 innings pitched, and ran a simple regression analysis of batted ball types against each one’s DER. The best formula I found was

Expected DER equals .738 + .068*OF% – .349*LD% + .23*IF%

where OF% equals the percent of batted balls that were outfield flies (not including home runs), LD% the percent that wereline drives, and IF% the percent that were infield flies. This formula has an R squared of .195, which means that about 20% of an individual pitcher’s DER can be explained by the type of batted ball he allows.

As I said, this is a simple analysis; I didn’t attempt to correct for team fielding or ballpark. I will improve this formula in the future, but I think that even this simple form is useful. So here’s a leaderboard of the pitchers whose actual DERs most exceeds their expected DERs, based on the above formula. These pitchers either have some fine fielders behind them or are getting batters to hit into good zones.

Player         Team        ERA      IP     DER    xDER    Diff
Ohka T.        WAS         3.20   50.67    .805   0.695   0.110
Clemens R.     HOU         1.30   76.00    .784   0.696   0.087
Myers B.       PHI         2.06   74.33    .765   0.693   0.072
Martinez P.    NYN         2.62   79.00    .789   0.722   0.067
Santos V.      MIL         2.73   62.67    .751   0.685   0.067
Prior M.       CHN         2.93   58.33    .774   0.710   0.064
Rogers K.      TEX         1.65   76.33    .747   0.685   0.062
Hampton M.     ATL         1.83   59.00    .766   0.709   0.057
Contreras J.   CHA         3.27   66.00    .789   0.734   0.055
Obermueller    MIL         3.00   36.00    .739   0.687   0.052
Ishii K.       NYN         4.79   35.67    .790   0.741   0.049
Zambrano C.    CHN         3.22   72.67    .770   0.722   0.048
Redman M.      PIT         3.14   71.67    .750   0.705   0.045
Estes S.       ARI         4.16   67.00    .722   0.677   0.044
Heilman A.     NYN         3.99   49.67    .721   0.682   0.038

Many of the best pitchers so far this year are on this list, which of course makes absolute sense. If you achieve a DER of .750 or higher, you are going to have a very good year.

The opposite is also true. Here is the Expected DER un-leaderboard (or laggardboard, I guess):

Player         Team        ERA      IP     DER    xDER    Diff
Ortiz R.       CIN         5.23   43.00    .634   0.717  -0.082
Brown K.       NYA         5.14   56.00    .635   0.704  -0.069
Wilson P.      CIN         7.77   46.33    .644   0.709  -0.065
Schmidt J.     SF          5.08   51.33    .680   0.740  -0.060
Glover G.      MIL         6.19   48.00    .660   0.712  -0.052
May D.         SD          4.96   32.67    .667   0.718  -0.052
Perez O.       PIT         6.92   53.33    .703   0.752  -0.049
Kennedy J.     COL         6.51   56.67    .655   0.703  -0.048
Young C.       TEX         3.03   65.33    .704   0.744  -0.039
Hendrickson    TB          5.37   55.33    .682   0.720  -0.038
Washburn J.    LAA         3.80   68.67    .674   0.711  -0.037
Escobar K.     LAA         2.97   36.33    .697   0.733  -0.036
Waechter D.    TB          5.43   53.00    .700   0.730  -0.030
Lilly T.       TOR         7.60   45.00    .653   0.682  -0.029
Vazquez J.     ARI         3.65   74.00    .677   0.706  -0.029

It’s interesting that there are some pitchers having very good years on this list, such as Javier Vazquez, Chris Young, Kelvim Escobar and Jerrod Washburn. I don’t know what that means, but just think how good they’d be if their actual DERs were as good as expected.

By the way, Oliver Perez’s .752 Expected DER is by far the best in the majors (Chris Young is second at .744) due to an extreme fly ball ratio and low line drive rate.

Dominance

Because infield flies are caught 97% of the time, they are just about as certain an out as a strikeout. So I’ve created a stat that I call Dominance, which measures how often a pitcher induces either a strikeout or infield fly as a percent of batters faced. Here are the Dominance Leaders:

Player         Team         IP      ERA       K   IFFly     Dom
Martinez P.    NYN         79.0    2.62      92      11   0.354
Santana J.     MIN         83.3    3.67     105       8   0.348
Burnett A.     FLA         68.0    2.91      64      21   0.309
Escobar K.     LAA         36.3    2.97      43       3   0.305
Myers B.       PHI         74.3    2.06      76       9   0.294
Prior M.       CHN         58.3    2.93      62       7   0.292
Peavy J.       SD          76.0    2.37      78       6   0.287
Vazquez J.     ARI         74.0    3.65      67      19   0.282
Harang A.      CIN         66.7    2.97      57      17   0.280
Clemens R.     HOU         76.0    1.30      76       6   0.279
Fossum C.      TB          40.7    3.54      40       9   0.275
Zambrano C.    CHN         72.7    3.22      68      12   0.275
Sheets B.      MIL         37.3    4.34      39       4   0.274
Perez O.       PIT         53.3    6.92      51      15   0.266
Schmidt J.     SF          51.3    5.08      49      14   0.265

As you can see, Pedro and Johan (yes, we’re on first name bases here) are the most dominant pitchers in baseball, measured in this manner. Thirty-five percent of the time, they have been 100% responsible for getting an out.

Here’s the Dominance un-leaderboard:

Player         Team         IP      ERA       K   IFFly     Dom
Drese R.       TEX         67.0    6.04      18       5   0.076
Saarloos K.    OAK         55.0    4.75      14       5   0.078
Erickson S.    LAN         42.7    6.75       9       7   0.083
Silva C.       MIN         67.0    3.09      21       2   0.087
Rueter K.      SF          65.3    4.27      14      13   0.095
Ohka T.        WAS         50.7    3.20      16       5   0.100
Blanton J.     OAK         48.7    6.66      16       8   0.108
Wang C.        NYA         37.7    4.06      14       3   0.109
Robertson N.   DET         59.7    3.17      27       3   0.114
Lima J.        KC          55.3    8.13      25       6   0.118
Ramirez H.     ATL         58.0    5.43      20      10   0.120
Glavine T.     NYN         62.3    5.05      31       4   0.122
Rogers K.      TEX         76.3    1.65      30       8   0.123
Hampton M.     ATL         59.0    1.83      22       6   0.124
Sele A.        SEA         63.0    4.43      29       5   0.125

Once again, there are some very good pitchers on this list, such as Carlos Silva, Kenny Rogers and Mike Hampton. The key to Silva’s ERA is his outstanding control. I’ll have more to say about Rogers and Hampton in a bit.

Home Run/Outfield Fly

In general, the number of home runs a pitcher gives up depends on the number of outfield fly balls he yields and the park in which he pitches. This year, 11% of outfield fly balls have been home runs overall, though there are a lot of differences among pitchers. Here is a leaderboard of the pitchers who have given up the fewest home runs, as a percent of outfield flies, adjusted for ballpark. For reference, I’ve also listed each pitcher’s Ground ball/Fly ball ratio.

Player         Team         IP     ERA     HR/F     G/F
Wang C.        NYA         37.7    4.06      0%    2.67
Rusch G.       CHN         55.0    1.96      2%    1.02
Patterson J.   WAS         47.3    2.85      2%     .79
Rogers K.      TEX         76.3    1.65      2%    1.25
Saarloos K.    OAK         55.0    4.75      2%    2.26
Brown K.       NYA         56.0    5.14      4%    2.00
Lidle C.       PHI         69.7    3.88      4%    1.54
Thomson J.     ATL         50.0    3.42      4%    1.36
Willis D.      FLA         78.0    1.85      4%    1.69
Robertson N.   DET         59.7    3.17      4%    1.97
Young C.       TEX         65.3    3.03      4%     .87

It pays to be a fly ball pitcher who doesn’t allow home runs, because fly ball pitchers have high DERs. This has been the secret of the success so far this season for John Patterson, Chris Young and Glendon Rusch.

Here’s a list of the pitchers who have yielded the most home runs as a percent of outfield flies (adjusted for ballpark again):

Player         Team         IP     ERA     HR/F     G/F
Erickson S.    LAN         42.7    6.75     25%    1.86
Westbrook J.   CLE         69.7    5.30     24%    4.05
Burnett A.     FLA         68.0    2.91     24%    2.41
Perez O.       PIT         53.3    6.92     23%     .57
Lowry N.       SF          58.7    5.37     23%    1.05
Lima J.        KC          55.3    8.13     23%     .79
Maroth M.      DET         64.3    5.04     21%    1.40
Suppan J.      STL         63.3    4.41     21%    1.63
Belisle M.     CIN         39.7    4.76     20%    1.73
Pineiro J.     SEA         48.7    6.66     19%    1.57
Lowe D.        LAN         78.0    3.58     19%    2.92

For groundball pitchers like Jake Westbrook, Derek Lowe and A.J. Burnett, the high percentage doesn’t hurt nearly as much because they don’t give up a lot of fly balls. For fly ball pitchers however, such as Oliver Perez and Jose Lima, these percentages are killers.

Expected FIP

So far, these leaderboards have been retrospective, uncovering the keys to each pitcher’s success or lack thereof. For our last leaderboard, let’s turn to a prospective stat called Expected Fielding Independent Pitching, which I introduced a few articles ago.

Expected FIP is just like regular Fielding Independent Pitching, except I’ve normalized each pitcher’s home run rate to the average of 11%. As Ron Shandler disclosed in his most recent Baseball Forecaster, most pitchers will regress to the mean of 11% over time.

In last month’s article, I reviewed a list of all pitchers whose ERA most exceeded their Expected FIP and stated that they could be expected to improve. Here’s the list, with their May 10 ERA and June 4 ERA, so you can see how many actually saw their ERAs drop in the last month:

                       Previous  Current
Player        Team        ERA      ERA
Brown K.      NYA         8.25     5.14   Down
Wright J.     NYA         9.15     6.39   Down
Lilly T.      TOR         7.77     7.60   Down
Anderson B.   KC          6.91     6.75   Down
Elarton S.    CLE         7.20     5.53   Down
Bell R.       TB          8.28    ----
Backe B.      HOU         6.81     4.67   Down
Kennedy J.    COL         7.56     6.51   Down
Lohse K.      MIN         6.65     4.25   Down
Harper T.     TB          6.27     7.36    Up
Wood K.       CHN         6.15    ----
Wilson P.     CIN         7.25     7.77    Up
Vazquez J.    ARI         4.70     3.65   Down

The list worked pretty well; nine of the 11 pitchers who actually pitched in the last month did indeed improve. So here’s an updated list of pitchers most likely to improve in the second two-thirds of the season, based on June 4 stats:

Player         Team         IP      ERA    xFIP    Diff
Lilly T.       TOR         45.0    7.60    4.91    2.69
Wilson P.      CIN         46.3    7.77    5.11    2.66
Pineiro J.     SEA         48.7    6.66    4.51    2.15
Lima J.        KC          55.3    8.13    6.20    1.94
Padilla V.     PHI         32.0    7.03    5.13    1.90
Glover G.      MIL         48.0    6.19    4.34    1.85
Milton E.      CIN         65.0    7.06    5.22    1.84
Wells D.       BOS         52.3    5.85    4.05    1.80
Perez O.       PIT         53.3    6.92    5.27    1.65
Kim B.         COL         31.0    6.97    5.33    1.64
Cabrera D.     BAL         58.3    5.40    3.92    1.48
Westbrook J.   CLE         69.7    5.30    3.82    1.48
Ledezma W.     DET         45.3    6.75    5.38    1.37
Dempster R.    CHN         44.7    4.84    3.48    1.36
Weaver J.      LAN         73.3    5.65    4.31    1.34

I mean, Ted Lilly and Paul Wilson have to turn their season around sometime, right?

Now for the other side of last month’s list: here are the pitchers whose ERAs I expected to increase the rest of the year, and a review of how they’ve done since May 10:

                       Previous  Current
Player        Team        ERA      ERA
Blanton J.    OAK         2.67     6.66    Up
Garland J.    CHA         1.38     3.22    Up
Chacon S.     COL         3.27     3.83    Up
Rogers K.     TEX         2.11     1.65   Down
Moehler B.    FLA         2.19     2.59    Up
Hampton M.    ATL         2.47     1.83   Down
Patterson J.  WAS         1.60     2.85    Up
Sabathia C.   CLE         2.63     3.58    Up
Contreras J.  CHA         2.60     3.27    Up
Seo J.        NYN         2.00    ----
Santos V.     MIL         2.88     2.73   Down
Robertson N.  DET         4.18     3.17   Down

Seven have indeed gotten worse, but four have actually improved. This list is a real surprise to me. Four months ago, Kenny Rogers had a 2.47 ERA, and I would have taken very heavy odds that his ERA would go up. But it’s actually gone down to a miniscule 1.65 ERA (and this doesn’t include his dominant game against Kansas City on Sunday, in which he lowered his ERA to 1.62). Mike Hampton’s ERA has actually dropped from 2.47 to 1.83. Crazy.

Rogers and Hampton lead the list of pitchers now most likely to see ERA increases the rest of this year. Sooner or later, it will happen. Here’s the current version of that list:

Player         Team         IP      ERA    xFIP    Diff
Rogers K.      TEX         76.3    1.65    4.87   -3.22
Hampton M.     ATL         59.0    1.83    4.64   -2.81
Ohka T.        WAS         50.7    3.20    5.56   -2.36
Rusch G.       CHN         55.0    1.96    4.20   -2.24
Santos V.      MIL         62.7    2.73    4.73   -2.00
Chacon S.      COL         51.7    3.83    5.83   -2.00
Robertson N.   DET         59.7    3.17    5.08   -1.92
Obermueller    MIL         36.0    3.00    4.91   -1.91
Clemens R.     HOU         76.0    1.30    2.95   -1.65
Willis D.      FLA         78.0    1.85    3.36   -1.52
Bedard E.      BAL         61.0    2.07    3.46   -1.40
Moehler B.     FLA         55.7    2.59    3.97   -1.39
Patterson J.   WAS         47.3    2.85    4.14   -1.29
Marquis J.     STL         69.0    3.39    4.67   -1.28
Chacin G.      TOR         67.0    3.36    4.64   -1.28

In a way, these lists aren’t that impressive. If you take a bunch of pitchers with low ERAs and say they’re going to get worse, well, no kidding. So let’s construct one last leaderboard. Here’s a list of the pitchers whose ERA most exactly matches his expected FIP. In other words, these are the guys most likely to continue to pitch as well or as poorly as they have been pitching so far:

Player         Team         IP      ERA    xFIP    Diff
Martinez P.    NYN         79.0    2.62    2.62    0.00
Backe B.       HOU         71.3    4.67    4.67   -0.01
Lohse K.       MIN         55.0    4.25    4.24    0.01
Lidle C.       PHI         69.7    3.88    3.89   -0.02
Burnett A.     FLA         68.0    2.91    2.88    0.03
Mussina M.     NYA         73.0    4.32    4.36   -0.04
Webb B.        ARI         76.0    3.20    3.15    0.05
Suppan J.      STL         63.3    4.41    4.46   -0.05
May D.         SD          32.7    4.96    4.89    0.06
Lackey J.      LAA         67.3    4.01    4.08   -0.07
Pettitte A.    HOU         70.0    3.47    3.55   -0.07
Mulder M.      STL         74.7    3.62    3.69   -0.08
Glavine T.     NYN         62.3    5.05    5.13   -0.08
Benson K.      NYN         36.3    4.21    4.13    0.08
Park C.        TEX         58.7    4.60    4.70   -0.10
Brazelton D.   TB          42.0    6.43    6.33    0.10

Met fans will be happy to see Pedro at the top of this list, but sad to see Tom Glavine on it too. A few comeback players, such as Brandon Webb, Chan Ho Park and Mark Mulder are for real. And that’s good to see.

We’ll have the batter leaderboards on Thursday. Come on back then.

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