Do Pitchers Give Up their Expected Number of Runs Based on OPS?

by Cyril Morong

Click here to see my sabermetric blog called Cybermetrics

Yes, for the most part they do. (compare this to how well the Component ERA of Bill James does at my site The Accuracy of Component ERA) NOTE: ADDITIONAL INFORMATION WAS ADDED JULY 11, 2005. I EXPANDED THE REGRESSION BELOW TO INCLUDE A DUMMY VARIABLE FOR LEFT HANDED PITCHERS AND A VARIABLE FOR STRIKEOUTS. The results are even more accurate than what I first had here. On July 13, information about a single season study was added. That information is below as well.

There is a very strong relationship between the OPS a pitcher allows and his ERA (as well as his runs per 9 innings).

I took all of the pitchers who had at least 1000 IP from 1991-2000. Then I looked for their data in my STATS, INC Player Profiles books from 1996 and 2001, to cover the years 1991-2000. Those books gave 5 year totals. If a pitcher did not appear in both editions, he was left out. Also left out were pitchers who pitched so much in relief that they had no column for run support. That left 59 pitchers (for Gooden, I used the years 1990-94 and 1996-2000).

Those books give OBP and SLG allowed. For the entire 10 year period, I calculated their OBP and SLG as a weighted average of the two 5 year periods by IP (BFP and AB would be better, but this is probably fairly accurate and required alot less data entry-in any case, it would just distort the real OPS and bias the study against finding a strong relation).

First, I looked at runs allowed per 9 innings as a function of OPS. The regression equation was

R/9 = 11.26*OPS - 3.72

The r-squared was .92, meaning that 92% of the variation was explained by the equation. The standard error was .157. That would be about 25 runs over a 162 game season. For a guy pitching 225 innings, about 4 runs. The relationship was even closer if I used ERA, since pitchers have different fielders behind them (r-squared was .939). The regression with ERA and OPS broken down into OBP and SLG had a standard error of .129.

For all teams (on offense) from 1991-98, the runs per game regression was

R/G = 12.62*OPS - 4.69

The r-squared was .908 and the standard error was .171. So, OPS is even a better predictor for pitchers than it is for team offense. The relationship is different, as you can see in the slope and the intercept. Why this is, I don’t know. Please email me if you have an explanation. For pitchers, the scatter diagram looks very linear.

In the table below, I show each pitcher’s predicted ERA based on the following equation:

ERA = 11.93*OBP + 10.21*SLG – 3.91

Only 3 pitchers are off by more than .25 runs in their ERA. In 225 IP (or 25 complete games), that is within 6 runs. That is about a full season for most pitchers. Even Hampton, who saved the most runs (.349 per 9 IP), would save only about 8 runs.

Pitcher	OBP	SLG	ERA	Pred	Diff
Mike Hampton	0.330	0.368	3.44	3.79	-0.349
Tom Glavine	0.309	0.350	3.13	3.36	-0.232
Kirk Rueter	0.326	0.427	4.16	4.35	-0.188
Steve Trachsel	0.332	0.445	4.42	4.60	-0.182
Ismael Valdes	0.304	0.394	3.59	3.75	-0.163
Scott Karl	0.356	0.454	4.82	4.98	-0.162
Andy Pettitte	0.336	0.396	3.99	4.15	-0.159
Armando Reynoso	0.348	0.450	4.68	4.84	-0.157
Shane Reynolds	0.310	0.412	3.85	4.00	-0.152
Pat Hentgen	0.331	0.422	4.21	4.36	-0.148
Bobby Jones	0.322	0.423	4.13	4.26	-0.128
Alex Fernandez	0.311	0.397	3.73	3.86	-0.127
Denny Neagle	0.312	0.414	3.92	4.04	-0.122
Chuck Finley	0.332	0.391	3.95	4.06	-0.107
Ken Hill	0.335	0.390	3.98	4.08	-0.101
Jeff Fassero	0.321	0.397	3.89	3.98	-0.092
Charles Nagy	0.331	0.422	4.28	4.36	-0.078
Mike Mussina	0.293	0.393	3.53	3.60	-0.075
Brad Radke	0.312	0.447	4.32	4.39	-0.071
Pete Harnisch	0.305	0.396	3.72	3.78	-0.062
Pat Rapp	0.365	0.418	4.67	4.73	-0.059
Kevin Brown	0.302	0.342	3.15	3.20	-0.048
Greg Maddux	0.269	0.316	2.50	2.54	-0.044
Al Leiter	0.332	0.355	3.65	3.69	-0.043
Andy Ashby	0.322	0.411	4.10	4.13	-0.034
Andy Benes	0.314	0.399	3.90	3.92	-0.025
Darryl Kile	0.343	0.402	4.27	4.29	-0.022
Dave Burba	0.335	0.409	4.26	4.27	-0.011
Orel Hershiser	0.331	0.405	4.17	4.18	-0.010
Aaron Sele	0.349	0.411	4.46	4.47	-0.006
Randy Johnson	0.298	0.329	3.03	3.01	0.023
Omar Olivares	0.353	0.416	4.59	4.57	0.024
Jon Lieber	0.314	0.436	4.32	4.29	0.026
Joey Hamilton	0.332	0.390	4.07	4.04	0.032
David Cone	0.311	0.358	3.50	3.46	0.039
Kenny Rogers	0.332	0.404	4.22	4.18	0.042
Roger Clemens	0.300	0.341	3.20	3.16	0.042
Ramon Martinez	0.324	0.367	3.76	3.71	0.046
Pedro Astacio	0.331	0.425	4.44	4.39	0.052
Todd Stottlemyre	0.326	0.405	4.18	4.12	0.055
Kevin Tapani	0.318	0.434	4.37	4.31	0.057
Tim Belcher	0.335	0.426	4.50	4.44	0.059
David Wells	0.309	0.427	4.20	4.14	0.060
Mark Clark	0.329	0.443	4.61	4.55	0.061
Pete Schourek	0.334	0.434	4.59	4.52	0.070
Jamie Moyer	0.315	0.418	4.20	4.13	0.074
Kevin Appier	0.312	0.367	3.65	3.57	0.079
Curt Schilling	0.286	0.371	3.38	3.30	0.082
Sterling Hitchcock	0.335	0.441	4.69	4.60	0.087
Scott Erickson	0.344	0.413	4.52	4.42	0.104
Pedro Martinez	0.270	0.319	2.68	2.57	0.105
John Burkett	0.329	0.418	4.41	4.29	0.122
Mark Gardner	0.329	0.435	4.61	4.47	0.143
Frank Castillo	0.327	0.427	4.52	4.35	0.166
Dwight Gooden	0.332	0.398	4.32	4.12	0.200
Hideo Nomo	0.316	0.381	3.97	3.76	0.213
Cal Eldred	0.332	0.416	4.52	4.30	0.216
Juan Guzman	0.325	0.375	4.08	3.80	0.278
Jaime Navarro	0.343	0.427	4.84	4.55	0.290

Additional Information

Bob Clark of Louisville suggested that I take lefties into account in looking at component ERA (ERC). The big reason to me might be that lefties face more right handed batters so they might get more GIDPs. So they might have lower ERAs than projected based on hits, BBs, and HRs than RHPs. The same should hold for OBP and SLG. Also, the more strikeouts a pitcher has, the fewer GIDPs he will probably have. That might increase runs allowed

Using the same data as above, the regression equation is

ERA = -4.7 - .096*DUM +.336*SO + 10.78*SLG + 13.01*OBP

DUM was 1 for a lefty and 0 for a righty. SO is strikeouts per IP. The r-squared was .952 and the standard error was .1186. All the variables were statistically significant.

Below is how each pitcher came out. Compared to the above model, the average absolute DIFF fell from .10176 to .0923.

Pitcher	OBP	SLG	SO/IP	Left	ERA	Pred	DIFF
Mike Hampton	0.330	0.368	0.676	1	3.440	3.692	-0.252
Steve Trachsel	0.332	0.445	0.697	0	4.420	4.651	-0.231
Shane Reynolds	0.310	0.412	0.850	0	3.850	4.060	-0.210
Armando Reynoso	0.348	0.450	0.521	0	4.680	4.853	-0.173
Pat Hentgen	0.331	0.422	0.636	0	4.210	4.369	-0.159
Ismael Valdes	0.304	0.394	0.733	0	3.590	3.749	-0.159
Alex Fernandez	0.311	0.397	0.712	0	3.730	3.865	-0.135
Bobby Jones	0.322	0.423	0.588	0	4.130	4.247	-0.117
Charles Nagy	0.331	0.422	0.652	0	4.280	4.374	-0.094
Pat Rapp	0.365	0.418	0.610	0	4.670	4.760	-0.090
Tom Glavine	0.309	0.350	0.660	1	3.130	3.219	-0.089
Darryl Kile	0.343	0.402	0.777	0	4.270	4.357	-0.087
Ken Hill	0.335	0.390	0.598	0	3.980	4.064	-0.084
Scott Karl	0.356	0.454	0.512	1	4.820	4.902	-0.082
Dave Burba	0.335	0.409	0.810	0	4.260	4.340	-0.080
Andy Pettitte	0.336	0.396	0.668	1	3.990	4.069	-0.079
Mike Mussina	0.293	0.393	0.764	0	3.530	3.605	-0.075
Chuck Finley	0.332	0.391	0.845	1	3.950	4.022	-0.072
Aaron Sele	0.349	0.411	0.774	0	4.460	4.531	-0.071
Brad Radke	0.312	0.447	0.614	0	4.320	4.384	-0.064
Denny Neagle	0.312	0.414	0.753	1	3.920	3.979	-0.059
Andy Benes	0.314	0.399	0.809	0	3.900	3.958	-0.058
Kirk Rueter	0.326	0.427	0.500	1	4.160	4.216	-0.056
Pete Harnisch	0.305	0.396	0.710	0	3.720	3.776	-0.056
Jeff Fassero	0.321	0.397	0.831	1	3.890	3.939	-0.049
Andy Ashby	0.322	0.411	0.659	0	4.100	4.141	-0.041
Randy Johnson	0.298	0.329	1.286	1	3.030	3.060	-0.030
Jon Lieber	0.314	0.436	0.779	0	4.320	4.347	-0.027
Kevin Brown	0.302	0.342	0.756	0	3.150	3.170	-0.020
David Cone	0.311	0.358	0.926	0	3.500	3.516	-0.016
Pedro Astacio	0.331	0.425	0.777	0	4.440	4.449	-0.009
Roger Clemens	0.300	0.341	0.966	0	3.200	3.204	-0.004
Orel Hershiser	0.331	0.405	0.599	0	4.170	4.173	-0.003
Al Leiter	0.332	0.355	0.859	1	3.650	3.639	0.011
Todd Stottlemyre	0.326	0.405	0.763	0	4.180	4.164	0.016
Joey Hamilton	0.332	0.390	0.667	0	4.070	4.047	0.023
Omar Olivares	0.353	0.416	0.533	0	4.590	4.556	0.034
Kevin Tapani	0.318	0.434	0.637	0	4.370	4.330	0.040
Pedro Martinez	0.270	0.319	1.153	0	2.680	2.639	0.041
Greg Maddux	0.269	0.316	0.752	0	2.500	2.459	0.041
Ramon Martinez	0.324	0.367	0.717	0	3.760	3.712	0.048
Curt Schilling	0.286	0.371	0.926	0	3.380	3.331	0.049
Mark Clark	0.329	0.443	0.584	0	4.610	4.552	0.058
Tim Belcher	0.335	0.426	0.564	0	4.500	4.440	0.060
Kevin Appier	0.312	0.367	0.797	0	3.650	3.583	0.067
Hideo Nomo	0.316	0.381	1.054	0	3.970	3.872	0.098
John Burkett	0.329	0.418	0.657	0	4.410	4.307	0.103
Mark Gardner	0.329	0.435	0.701	0	4.610	4.505	0.105
Scott Erickson	0.344	0.413	0.551	0	4.520	4.413	0.107
Sterling Hitchcock	0.335	0.441	0.788	1	4.690	4.581	0.109
Pete Schourek	0.334	0.434	0.709	1	4.590	4.466	0.124
Frank Castillo	0.327	0.427	0.695	0	4.520	4.391	0.129
Kenny Rogers	0.332	0.404	0.628	1	4.220	4.090	0.130
David Wells	0.309	0.427	0.668	1	4.200	4.052	0.148
Dwight Gooden	0.332	0.398	0.706	0	4.320	4.147	0.173
Jamie Moyer	0.315	0.418	0.599	1	4.200	4.010	0.190
Cal Eldred	0.332	0.416	0.658	0	4.520	4.325	0.195
Juan Guzman	0.325	0.375	0.838	0	4.080	3.852	0.228
Jaime Navarro	0.343	0.427	0.547	0	4.840	4.549	0.291

Single Season Data

The data set included all pitchers who had 162+ IP from 1994-2000 (529 pitchers). The regression equation was

ERA = -4.99 - .05*DUM +.302*SO + 10.31*SLG + 14.45* OBP

The r-squared was .837 and the standard error was .351. Each Pitcher’s prediction and their relevant data is given below. It is not as accurate as the previous regression, in part because there is so much randomness in single season data.

But first, I want to discuss a problem of possible bias in the regression. It seems as actual ERAs increase, the difference (DIFF) between actual ERA and the predicted ERA increases, with the highest ERA pitchers having actual ERAs much higher than predicted..

The table below summarizes how well pitchers at various levels of ERAs were predicted. A negative number means that actual ERA was less than predicted ERA and a positive number the opposite. The number stated is the average DIFF for the range of ERAs shown. The last number is the number of pitchers in the bracket.

Range of ERAs	AVG DIFF	# of Pitchers
1.5-1.99	0.227	5
2-2.49	-0.100	10
2.5-2.99	0.164	30
3-3.49	-0.141	67
3.5-3.99	-0.109	98
4-4.49	-0.067	127
5-5.49	0.204	57
5.5-5.99	0.519	21
6-6.66	0.584	11

It seems like all pitchers below an ERA of 5.49 are reasonably well predicted. But over that, there seems to be an extreme bias. Their actual ERAs are much worse than predicted.

I tried some non-linear techniques to eliminate this bias. But the results were generally not any better. I also tried looking for a structural break, serial correlation and heteroskedasticity. But I could not find anything going on. For some reason that I cannot determine, high ERA pitchers don’t get well predicted and they get over predicted.

But there seems to be no bias for pitchers with high OPS. They are fairly well predicted. Jose Lima (2000), was the only pitcher over .900 in OPS with .942. There was also no correlation between the prediction error and OBP, SLG or OPS.

Range of OPS	AVG DIFF	# of Pitchers
.450-.499	0.525	2
.500-.549	0.08	3
.550-.599	0.07	12
.600-.649	0.022	37
.650-.699	-0.013	73
.700-.749	0.028	153
.750-.799	0.024	147
.800-.849	0.017	84
.850-.942	0.211	18

Here are the pitchers with their relevant data. 282 of the 529 pitchers were predicted to within .25. 451 were within .50.

Pitcher	YEAR	OBP	SLG	SO/IP	Left	ERA	Pred	DIFF
Brown Kevin	1997	0.303	0.419	0.864	0	2.690	3.969	-1.279
Rijo Jose	1994	0.321	0.396	0.992	0	3.080	4.031	-0.951
Hampton Mike	1998	0.344	0.398	0.647	1	3.360	4.230	-0.870
Rueter Kirk	2000	0.345	0.458	0.386	1	3.960	4.784	-0.824
Reynolds Shane	1998	0.318	0.432	0.896	0	3.510	4.330	-0.820
Bailey Roger	1997	0.354	0.467	0.440	0	4.290	5.073	-0.783
Bottenfield Kent	1999	0.350	0.432	0.651	0	3.970	4.718	-0.748
Ashby Andy	1995	0.321	0.369	0.779	0	2.940	3.688	-0.748
Trachsel Steve	1996	0.298	0.411	0.644	0	3.030	3.748	-0.718
Parris Steve	2000	0.355	0.503	0.607	0	4.810	5.509	-0.699
Guzman Juan	1999	0.332	0.419	0.775	0	3.740	4.361	-0.621
Trachsel Steve	1997	0.344	0.476	0.795	0	4.510	5.128	-0.618
Jones Bobby	1997	0.329	0.416	0.647	0	3.630	4.248	-0.618
Key Jimmy	1997	0.331	0.398	0.664	1	3.430	4.047	-0.617
Hernandez Livan	1998	0.363	0.472	0.691	0	4.720	5.330	-0.610
D'Amico Jeff	2000	0.297	0.365	0.622	0	2.660	3.253	-0.593
Clark Mark	1997	0.322	0.443	0.600	0	3.820	4.411	-0.591
Johnson Randy	2000	0.288	0.356	1.395	1	2.640	3.213	-0.573
Bosio Chris	1995	0.375	0.476	0.500	0	4.920	5.487	-0.567
Oliver Darren	1997	0.346	0.451	0.517	1	4.200	4.766	-0.566
Vazquez Javier	2000	0.335	0.434	0.900	0	4.050	4.597	-0.547
Olivares Omar	1998	0.357	0.409	0.612	0	4.030	4.570	-0.540
Finley Chuck	1998	0.334	0.374	0.949	1	3.390	3.929	-0.539
Dickson Jason	1997	0.338	0.462	0.565	0	4.290	4.828	-0.538
Arrojo Rolando	1998	0.329	0.398	0.752	0	3.560	4.095	-0.535
Radke Brad	1999	0.314	0.443	0.553	0	3.750	4.282	-0.532
Valenzuela Fernando	1996	0.334	0.407	0.553	1	3.620	4.150	-0.530
Mussina Mike	1999	0.312	0.411	0.846	0	3.500	4.011	-0.511
Belcher Tim	1996	0.331	0.436	0.473	0	3.920	4.431	-0.511
Ortiz Russ	1999	0.351	0.388	0.790	0	3.810	4.321	-0.511
Kile Darryl	1997	0.301	0.337	0.802	0	2.570	3.076	-0.506
Burkett John	1995	0.339	0.455	0.669	0	4.300	4.802	-0.502
Drabek Doug	1996	0.355	0.455	0.781	0	4.570	5.067	-0.497
Lopez Albie	2000	0.341	0.439	0.518	0	4.130	4.620	-0.490
Wells David	1995	0.299	0.412	0.655	1	3.240	3.726	-0.486
Ritchie Todd	1999	0.319	0.405	0.621	0	3.500	3.983	-0.483
Ashby Andy	1998	0.309	0.402	0.666	0	3.340	3.821	-0.481
Valdes Ismael	1999	0.321	0.446	0.703	0	3.980	4.459	-0.479
Cooke Steve	1997	0.366	0.420	0.651	1	4.300	4.776	-0.476
Key Jimmy	1994	0.329	0.374	0.577	1	3.270	3.744	-0.474
Anderson Brian	2000	0.308	0.481	0.488	1	4.050	4.517	-0.467
Benes Andy	2000	0.342	0.499	0.825	0	4.880	5.346	-0.466
Gardner Mark	1996	0.341	0.456	0.809	0	4.420	4.883	-0.463
Maddux Greg	1999	0.323	0.403	0.620	0	3.570	4.020	-0.450
Dempster Ryan	2000	0.322	0.404	0.923	0	3.660	4.107	-0.447
Neagle Denny	1996	0.308	0.420	0.673	1	3.500	3.944	-0.444
Saunders Tony	1998	0.364	0.395	0.894	1	4.120	4.562	-0.442
Saberhagen Bret	1994	0.271	0.389	0.806	0	2.740	3.180	-0.440
Neagle Denny	1995	0.312	0.405	0.715	1	3.430	3.860	-0.430
Reed Rick	1998	0.290	0.434	0.721	0	3.480	3.893	-0.413
Moehler Brian	2000	0.342	0.464	0.579	0	4.500	4.910	-0.410
Astacio Pedro	1996	0.324	0.385	0.614	0	3.440	3.847	-0.407
Wakefield Tim	1995	0.300	0.371	0.609	0	2.950	3.354	-0.404
Haynes Jimmy	1998	0.370	0.478	0.690	0	5.090	5.493	-0.403
Loaiza Esteban	2000	0.344	0.463	0.687	0	4.560	4.962	-0.402
Burba Dave	1998	0.330	0.440	0.648	0	4.110	4.511	-0.401
Williams Woody	1997	0.329	0.465	0.637	0	4.350	4.751	-0.401
Trachsel Steve	2000	0.356	0.473	0.548	0	4.800	5.196	-0.396
Glavine Tom	1996	0.314	0.353	0.769	1	2.980	3.369	-0.389
Bergman Sean	1998	0.315	0.424	0.581	0	3.720	4.109	-0.389
Helling Rick	1999	0.340	0.497	0.597	0	4.840	5.227	-0.387
Glavine Tom	1998	0.300	0.325	0.685	1	2.470	2.852	-0.382
Kile Darryl	1996	0.359	0.395	1.000	0	4.190	4.572	-0.382
Witt Bobby	1997	0.350	0.481	0.579	0	4.820	5.201	-0.381
Halama John	1999	0.338	0.439	0.587	0	4.220	4.597	-0.377
Wolf Randy	2000	0.342	0.446	0.775	1	4.360	4.734	-0.374
Johnson Randy	1997	0.277	0.318	1.366	1	2.280	2.654	-0.374
Cone David	1999	0.322	0.375	0.916	0	3.440	3.806	-0.366
Cone David	1997	0.305	0.332	1.138	0	2.820	3.184	-0.364
Suppan Jeff	2000	0.351	0.489	0.590	0	4.940	5.302	-0.362
Hernandez Livan	2000	0.325	0.407	0.688	0	3.750	4.110	-0.360
Heredia Gil	2000	0.332	0.438	0.508	0	4.120	4.477	-0.357
Jackson Danny	1994	0.312	0.381	0.719	1	3.260	3.614	-0.354
Suzuki Mac	2000	0.349	0.429	0.716	0	4.340	4.692	-0.352
Stottlemyre Todd	1998	0.318	0.408	0.920	0	3.740	4.090	-0.350
Schmidt Jason	1999	0.330	0.441	0.696	0	4.190	4.535	-0.345
Nagy Charles	1997	0.342	0.434	0.656	0	4.280	4.625	-0.345
Navarro Jaime	1996	0.326	0.421	0.668	0	3.920	4.263	-0.343
Valdes Ismael	1997	0.282	0.358	0.712	0	2.650	2.991	-0.341
Karl Scott	1998	0.349	0.444	0.530	1	4.400	4.741	-0.341
Lima Jose	1999	0.296	0.427	0.759	0	3.580	3.919	-0.339
Boskie Shawn	1996	0.359	0.508	0.702	0	5.320	5.647	-0.327
Mussina Mike	1994	0.291	0.388	0.561	0	3.060	3.385	-0.325
Wakefield Tim	1997	0.343	0.425	0.750	0	4.250	4.575	-0.325
Fernandez Alex	1996	0.307	0.397	0.775	0	3.450	3.773	-0.323
Olivares Omar	1999	0.348	0.419	0.413	0	4.160	4.483	-0.323
Karl Scott	1999	0.370	0.454	0.374	1	4.780	5.100	-0.320
Daal Omar	1998	0.305	0.348	0.811	1	2.880	3.200	-0.320
Meadows Brian	2000	0.355	0.503	0.402	0	5.130	5.447	-0.317
Brown Kevin	1994	0.361	0.455	0.724	0	4.820	5.136	-0.316
Gubicza Mark	1995	0.326	0.410	0.380	0	3.750	4.062	-0.312
Williams Woody	1999	0.328	0.463	0.658	0	4.410	4.722	-0.312
Sirotka Mike	2000	0.330	0.405	0.650	1	3.790	4.100	-0.310
Schmidt Jason	1998	0.334	0.419	0.737	0	4.070	4.379	-0.309
Pettitte Andy	1999	0.364	0.446	0.631	1	4.700	5.009	-0.309
Clark Mark	1996	0.306	0.398	0.669	0	3.430	3.737	-0.307
Hentgen Pat	2000	0.353	0.459	0.607	0	4.720	5.027	-0.307
Harnisch Pete	1998	0.291	0.388	0.751	0	3.140	3.442	-0.302
Leiter Al	1995	0.345	0.363	0.836	1	3.640	3.940	-0.300
Witt Bobby	1995	0.345	0.406	0.820	0	4.130	4.429	-0.299
Person Robert	2000	0.332	0.372	0.946	0	3.630	3.928	-0.298
Hershiser Orel	1996	0.341	0.428	0.607	0	4.240	4.533	-0.293
Fassero Jeff	1998	0.316	0.436	0.783	1	3.970	4.258	-0.288
Gardner Mark	1997	0.326	0.449	0.754	0	4.290	4.578	-0.288
Hermanson Dustin	2000	0.352	0.467	0.475	0	4.770	5.055	-0.285
Garcia Freddy	1999	0.345	0.398	0.844	0	4.070	4.354	-0.284
Mulholland Terry	1999	0.340	0.451	0.487	1	4.390	4.670	-0.280
Hill Ken	1996	0.332	0.378	0.678	0	3.630	3.909	-0.279
Harnisch Pete	1999	0.307	0.420	0.605	0	3.680	3.959	-0.279
Yoshii Masato	1999	0.324	0.466	0.603	0	4.400	4.679	-0.279
Castillo Frank	1995	0.302	0.378	0.718	0	3.210	3.488	-0.278
Sele Aaron	1998	0.354	0.402	0.785	0	4.230	4.507	-0.277
Hampton Mike	1999	0.322	0.324	0.741	1	2.900	3.177	-0.277
Belcher Tim	1998	0.328	0.449	0.556	0	4.270	4.547	-0.277
Rapp Pat	1995	0.340	0.350	0.610	0	3.440	3.716	-0.276
Park Chan Ho	2000	0.325	0.344	0.960	0	3.270	3.543	-0.273
Ponson Sidney	1999	0.345	0.468	0.533	0	4.710	4.981	-0.271
Martinez Ramon	1996	0.341	0.341	0.789	0	3.420	3.691	-0.271
Mlicki Dave	1997	0.329	0.413	0.811	0	4.000	4.267	-0.267
Morris Matt	1997	0.319	0.352	0.687	0	3.190	3.456	-0.266
Mays Joe	1999	0.336	0.443	0.673	0	4.370	4.636	-0.266
Guzman Juan	1996	0.289	0.363	0.879	0	2.930	3.194	-0.264
Bones Ricky	1994	0.304	0.406	0.334	0	3.430	3.690	-0.260
Candiotti Tom	1995	0.316	0.384	0.741	0	3.500	3.759	-0.259
Rueter Kirk	1997	0.311	0.395	0.603	1	3.450	3.709	-0.259
Parque Jim	2000	0.352	0.418	0.594	1	4.280	4.535	-0.255
Baldwin James	2000	0.335	0.471	0.652	0	4.650	4.904	-0.254
Rekar Bryan	2000	0.329	0.459	0.548	0	4.410	4.662	-0.252
Fassero Jeff	1995	0.348	0.420	0.868	1	4.330	4.581	-0.251
Nagy Charles	1996	0.306	0.388	0.752	0	3.410	3.659	-0.249
Park Chan Ho	1999	0.369	0.472	0.895	0	5.230	5.479	-0.249
Pettitte Andy	1996	0.330	0.404	0.733	1	3.870	4.115	-0.245
Martinez Dennis	1995	0.302	0.367	0.529	0	3.080	3.318	-0.238
Stephenson Garrett	2000	0.327	0.466	0.614	0	4.490	4.725	-0.235
Yoshii Masato	1998	0.316	0.425	0.682	0	3.930	4.164	-0.234
Dreifort Darren	2000	0.329	0.424	0.851	0	4.160	4.393	-0.233
Sele Aaron	1999	0.355	0.447	0.907	0	4.790	5.022	-0.232
Clemens Roger	1997	0.273	0.290	1.106	0	2.050	2.279	-0.229
Lieber Jon	1998	0.311	0.445	0.807	0	4.110	4.336	-0.226
Portugal Mark	1998	0.319	0.471	0.625	0	4.440	4.664	-0.224
Springer Dennis	1999	0.358	0.463	0.423	0	4.860	5.084	-0.224
Leiter Al	1998	0.298	0.306	0.902	1	2.470	2.693	-0.223
Lieber Jon	1999	0.315	0.432	0.915	0	4.070	4.292	-0.222
Woodard Steve	1999	0.330	0.462	0.643	0	4.520	4.736	-0.216
Cordova Francisco	1998	0.303	0.380	0.713	0	3.310	3.521	-0.211
Holt Chris	1997	0.320	0.384	0.453	0	3.520	3.730	-0.210
Neagle Denny	1998	0.307	0.400	0.784	1	3.550	3.757	-0.207
Reynoso Armando	1996	0.347	0.483	0.522	0	4.960	5.161	-0.201
Blair Willie	1998	0.344	0.489	0.525	0	4.980	5.181	-0.201
Watson Allen	1996	0.339	0.460	0.689	1	4.610	4.809	-0.199
Colon Bartolo	1998	0.329	0.379	0.775	0	3.710	3.905	-0.195
Burba Dave	1999	0.336	0.421	0.791