2010 PrOPS Over- and Under-Performers

Since The Hardball Times stopped carrying stats, I have received several requests for 2010 PrOPS. I’m happy that some people have an interest in the numbers, and PrOPS was in need of a serious update anyway, so I decided to calculate PrOPS for 2010 based on the past five seasons using data from Baseball-Reference. While I can’t list a full slate of PrOPS for all players, I will report the top over- and under-performances for this season.

If you are not familiar with PrOPS, it’s an estimate of player hitting performance (measured on the scale of OPS) according to how players hit the ball rather than using in-play outcomes (see the introductory essay). OPS is estimated from batted-ball types (line-drive percentage and groundball-flyball ratio), walk rate, strikeout rate, home run rate, hit batter rate, home ballpark, and season. The idea is to identify players who are hitting the ball well (or poorly), but the measured outcome differs from what is typical for players who hit the ball in the same way. Players who are over- or under-performing their PrOPS are more likely to decline or improve than players whose performances are in-line with their OPS. PrOPS does not remove all aspects of luck, it just highlights one common area where random bounces on the field can distort outcome-based metrics.

The tables below are based on performances through Friday, May 14 for players with more than 100 plate appearances. Here is a list of players who are playing over their heads and may be headed toward a fall.

Top-30 Over-Performers

Rank	Player			Team	OPS	PrOPS	Diff.	PA
1	Jayson  Werth		PHI	1.089	0.836	0.253	142
2	Justin  Morneau		MIN	1.142	0.948	0.194	148
3	Colby  Rasmus		STL	0.958	0.795	0.163	127
4	Carl  Crawford		TBR	0.868	0.710	0.158	154
5	Elvis  Andrus		TEX	0.791	0.646	0.145	153
6	Ichiro  Suzuki		SEA	0.853	0.708	0.145	158
7	Troy  Tulowitzki	COL	0.823	0.680	0.143	139
8	Kevin  Youkilis		BOS	0.969	0.828	0.141	157
9	Miguel  Cabrera		DET	1.088	0.948	0.140	157
10	Andrew  McCutchen	PIT	0.913	0.779	0.134	147
11	Adam  Dunn		WSN	0.917	0.788	0.129	147
12	Andre  Ethier		LAD	1.201	1.085	0.116	140
13	Stephen  Drew		ARI	0.848	0.733	0.115	140
14	Franklin  Gutierrez 	SEA	0.865	0.752	0.113	144
15	Fred  Lewis		TOR	0.828	0.716	0.112	111
16	Carlos  Ruiz		PHI	0.948	0.841	0.107	106
17	Ryan  Braun		MIL	1.007	0.906	0.101	153
18	Johnny  Damon		DET	0.814	0.716	0.098	153
19	Daric  Barton		OAK	0.791	0.694	0.097	158
20	Nick  Markakis		BAL	0.837	0.741	0.096	159
21	Josh  Willingham	WSN	0.909	0.816	0.093	137
22	Adam  LaRoche		ARI	0.802	0.709	0.093	133
23	Geovany  Soto		CHC	0.954	0.863	0.091	111
24	Blake  DeWitt		LAD	0.711	0.622	0.089	108
25	Shin-Soo  Choo		CLE	0.853	0.768	0.085	148
26	Evan  Longoria		TBR	1.007	0.923	0.084	153
27	Brett  Gardner		NYY	0.832	0.751	0.081	131
28	Casey  McGehee		MIL	0.935	0.855	0.080	147
29	Kosuke  Fukudome	CHC	0.960	0.880	0.080	118
30	Ben  Zobrist		TBR	0.725	0.646	0.079	151

The players in the table below have had some tough luck to start the year and are likely to improve as the season progresses. It’s interesting that the list includes Derek Jeter and Victor Martinez, who have both been singled out for their unexpected poor play. And David Ortiz just misses the cut (99 PAs), but his PrOPS is .906, a difference of -.140 from his actual OPS.

Top-30 Under-Performers

Rank	Player			Team	OPS	PrOPS	Diff.	PA
1	Hunter  Pence		HOU	0.705	0.927	-0.222	128
2	Skip  Schumaker		STL	0.589	0.800	-0.211	146
3	Brandon  Wood		LAA	0.414	0.622	-0.208	107
4	Chris  Coghlan		FLA	0.517	0.723	-0.206	132
5	Akinori  Iwamura	PIT	0.489	0.683	-0.194	142
6	Kendry  Morales		LAA	0.780	0.974	-0.194	150
7	Casey  Kotchman		SEA	0.627	0.811	-0.184	128
8	Derek  Jeter		NYY	0.717	0.886	-0.169	161
9	Adam  Rosales		OAK	0.677	0.837	-0.160	117
10	Victor  Martinez	BOS	0.641	0.801	-0.160	138
11	Rod  Barajas		NYM	0.860	1.016	-0.156	110
12	Melky  Cabrera		ATL	0.523	0.676	-0.153	124
13	Mark  DeRosa		SFG	0.537	0.686	-0.149	104
14	Cesar  Izturis		BAL	0.486	0.626	-0.140	104
15	Jose  Lopez		SEA	0.530	0.667	-0.137	149
16	A.J.  Pierzynski	CHW	0.547	0.680	-0.133	115
17	Russell  Martin		LAD	0.741	0.872	-0.131	140
18	Juan  Rivera		LAA	0.677	0.800	-0.123	127
19	Aramis  Ramirez		CHC	0.500	0.623	-0.123	146
20	Carlos  Lee		HOU	0.514	0.636	-0.122	139
21	Brendan  Ryan		STL	0.480	0.594	-0.114	117
22	Luis  Castillo		NYM	0.646	0.760	-0.114	122
23	Scott  Sizemore		DET	0.591	0.700	-0.109	112
24	Placido  Polanco	PHI	0.789	0.897	-0.108	149
25	Ian  Stewart		COL	0.906	1.010	-0.104	128
26	Jhonny  Peralta		CLE	0.690	0.791	-0.101	127
27	Grady  Sizemore		CLE	0.558	0.656	-0.098	137
28	Alcides  Escobar	MIL	0.622	0.719	-0.097	125
29	Pedro  Feliz		HOU	0.531	0.625	-0.094	123
30	Mark  Teixeira		NYY	0.733	0.824	-0.091	160

I want to reiterate that over- and under-performing does not guarantee a reversion, but it is one tool to identify those who are likely to deviate from their performances so far this season.

6 Responses “2010 PrOPS Over- and Under-Performers”

  1. Cyril Morong says:

    What is a better predictor of a player’s OPS in a season? Last year’s OPS or PrOPS?

    What about within season? Say, what predicts 2nd half OPS better, first half OPS or first half PrOPS?

  2. JC says:

    In this incarnation, lagged OPS predicts OPS better than PrOPS; however, previously PrOPS predicted better. I don’t know why it’s changed, but roughly they explain about the same amount of variance. Adding the lag of the difference between PrOPS and OPS improves the predictive power of the model. Also, I don’t think that all of Houston’s poor play can be explained by luck. Their OPS is so historically low that it’s not surprising there is such a disparity.

  3. Cyril Morong says:

    Okay, thanks.

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