Archive for June, 2010

What Edwin Jackson’s Pitch Count Hath Wrought

Edwin Jackson threw a bit of a lame no-hitter on Friday. I’m sorry if it offends you when I call such a hallowed feat lame, but eight walks in a game for a major-league pitcher is bad (see Pulling a Homer). But aside from this, one aspect of his performance has gotten a lot of attention: 149 pitches thrown. This is the highest pitch count allowed in a game since 2005 (see my previous post on how pitch counts have changed over the past two decades).

I have been conducting a study of pitch counts with Sean Forman, and we will be presenting our findings at the upcoming SABR convention in Atlanta. But since it’s applicable to Jackson’s situation, I’ll reveal some of the findings. Our study uses past pitching performances to estimate the impact of pitch counts on future performance, controlling for numerous factors, using fractional polynomial regression analysis to capture potential non-linear relationships. The results indicate that the impact of the pitch count in a single game on the following game is real but small; and, the impact is linear, not increasing as some analysts have theorized.

On average, every pitch thrown raises a pitcher’s ERA by 0.007 in the following game. Jackson’s ERA was 5.05 going into Friday’s game averaging 104 pitches per game; thus, based on the historical response of pitchers to pitch counts Jackson’s expected performance in his next start is about 5.37. So, Jackson can be expected to pitch worse, but not that much worse. Really, it’s not that big of a deal as a one-time event. Should Jackson continue to average around 150 pitches a game, the impact will grow, but I doubt that is going to happen. As for the impact on injuries, we didn’t look into it in this study. However, I have previously found little correlation between pitching loads and injury.

My take: if you have a pitcher going for a no-hitter—not matter how bad he’s pitching—the benefit of the excitement and media coverage of letting a pitcher throw more pitches is probably worth the cost. Let’s stop freaking out about pitch counts until we understand their influence a little better.

Update: In response to Jackson’s high pitch count, the Diamondbacks will push back his next start a day or two. How much will this help him recover? No much. On average, each day of rest lowers a pitcher’s ERA by approximately 0.015. Thus, his expected ERA drops from 5.37 to 5.34 (with two days of extra rest). Why rest days matter so little is an interesting question. A few years ago, I saw an presentation on muscle recovery from exercise, and one of the interesting findings was that most of the healing happens within the first few days. Whether this explains the finding or not, I don’t know.

The Last Father’s Day

Some words about my father are below the fold.

»» The Last Father’s Day

2010 PrOPS Over- and Under-Performers (Through 6/15)

I have updated PrOPS through June 15 (minimum 200 PA). I report the top-30 over- and under-performers. Here is my previous post on 2010 PrOPS.

Top-30 Over-Performers

Rk	Player 			Team	OPS	PrOPS	Diff	PA
1	Andres  Torres		SFG	0.885	0.721	0.164	220
2	Justin  Morneau		MIN	1.079	0.925	0.154	266
3	Kevin  Youkilis		BOS	1.043	0.889	0.154	273
4	Ichiro  Suzuki		SEA	0.830	0.698	0.132	293
5	Jayson  Werth		PHI	0.904	0.776	0.128	243
6	Nick  Markakis		BAL	0.818	0.695	0.123	282
7	Andrew  McCutchen	PIT	0.861	0.741	0.120	271
8	David  DeJesus		KCR	0.873	0.761	0.112	276
9	Colby  Rasmus		STL	0.997	0.888	0.109	223
10	Daric  Barton		OAK	0.818	0.712	0.106	293
11	Evan  Longoria		TBR	0.964	0.861	0.103	279
12	Carl  Crawford		TBR	0.831	0.731	0.100	274
13	Adam  Dunn		WSN	0.951	0.852	0.099	265
14	Johnny  Damon		DET	0.808	0.711	0.097	262
15	Ben  Zobrist		TBR	0.824	0.728	0.096	275
16	Billy  Butler		KCR	0.890	0.798	0.092	278
17	Fred  Lewis		TOR	0.780	0.689	0.091	218
18	Franklin  Gutierrez	SEA	0.755	0.666	0.089	273
19	Robinson  Cano		NYY	1.022	0.936	0.086	278
20	Brett  Gardner		NYY	0.842	0.763	0.079	236
21	Elvis  Andrus		TEX	0.722	0.647	0.075	279
22	Aubrey  Huff		SFG	0.909	0.835	0.074	256
23	David  Freese		STL	0.809	0.735	0.074	234
24	Jason  Bay		NYM	0.790	0.719	0.071	272
25	Brandon  Phillips	CIN	0.849	0.780	0.069	287
26	Andre  Ethier		LAD	1.021	0.959	0.062	203
27	Josh  Hamilton		TEX	0.941	0.880	0.061	268
28	Drew  Stubbs		CIN	0.738	0.678	0.060	242
29	Erick  Aybar		LAA	0.688	0.629	0.059	292
30	Troy  Tulowitzki	COL	0.869	0.810	0.059	257
Top-30 Under-Performers

Rk	Player			Team	OPS	PrOPS	Diff	PA
1	Casey  Kotchman		SEA	0.551	0.749	-0.198	200
2	Carlos  Lee		HOU	0.658	0.823	-0.165	259
3	Hunter  Pence		HOU	0.751	0.906	-0.155	251
4	Jose  Lopez		SEA	0.571	0.717	-0.146	271
5	Kendry  Morales		LAA	0.833	0.970	-0.137	211
6	Skip  Schumaker		STL	0.613	0.748	-0.135	247
7	Ian  Stewart		COL	0.758	0.877	-0.119	224
8	Derek  Jeter		NYY	0.780	0.896	-0.116	301
9	Mike  Napoli		LAA	0.798	0.912	-0.114	211
10	Juan  Rivera		LAA	0.746	0.853	-0.107	223
11	Adam  Lind		TOR	0.636	0.737	-0.101	268
12	Carlos  Gonzalez	COL	0.824	0.919	-0.095	250
13	Cameron  Maybin		FLA	0.631	0.726	-0.095	201
14	Clint  Barmes		COL	0.671	0.761	-0.090	202
15	Carlos  Pena		TBR	0.736	0.823	-0.087	261
16	Aaron  Hill		TOR	0.666	0.752	-0.086	230
17	A.J.  Pierzynski	CHW	0.649	0.734	-0.085	204
18	Pedro  Feliz		HOU	0.567	0.651	-0.084	224
19	Carlos  Quentin		CHW	0.681	0.764	-0.083	224
20	Melky  Cabrera		ATL	0.646	0.724	-0.078	212
21	Nate  McLouth		ATL	0.577	0.653	-0.076	205
22	Yadier  Molina		STL	0.666	0.739	-0.073	227
23	Matt  Wieters		BAL	0.629	0.697	-0.068	231
24	Howie  Kendrick		LAA	0.712	0.777	-0.065	276
25	Miguel  Tejada		BAL	0.676	0.741	-0.065	265
26	Alcides  Escobar	MIL	0.657	0.722	-0.065	233
27	Jerry  Hairston		SDP	0.618	0.682	-0.064	229
28	Derrek  Lee		CHC	0.688	0.750	-0.062	270
29	Juan  Pierre		CHW	0.584	0.645	-0.061	277
30	Brandon  Inge		DET	0.715	0.774	-0.059	248

A Lesson in Concentrated Benefits and Dispersed Costs

File under: Mancur Olson was right.

From San Francisco Chronicle:

The vote came after the football team spent an astonishing $4 million-plus on a campaign in a city with only 46,000 registered voters. Signs backing the 49ers sprang up in front yards across the community as the team carpet-bombed the city with TV spots, radio ads and campaign mailers.

It was a different story for opponents of the stadium, who managed to collect about $20,000, enough for some yards signs and some campaign handouts for the volunteers who knocked on doors.

Improvement in Fielding: Personal Evidence

In my previous post, I present some data that indicates fielding has improved over time. Here is a partial explanation.

My grandfather’s glove (circa 1910s)


Grandfather's glove

My father’s glove (circa 1950s)


Father's glove

My glove (circa 1980s)


My glove

Why More Perfect Games?

Better defense?

Errors and Perfect Games

Just a guess.