Ground ball rates of Tigers pitchers in 2007

ERA has traditionally been used to evaluate overall pitching performance but it is problematic because it does not separate pitching from fielding. More and more, I've been using FIP ERA (or Fielding Independent ERA) which is calculated using only statistics over which a pitcher has control - strikeouts, bases on balls, hits batsmen and home runs. FIP is more predictive or more stable from year to year than ERA.

In last year's article on repeatable pitching skills, I showed that SO/IP (correlation=.77) and BB/IP (correlation=.67) are very repeatable from one year to the next. Home runs per IP is less consistent (.38) and it is also park dependent. For this reason, many analysts are now using ground ball percentage (percent of batted balls which are hit on the ground) more than home runs. Ground ball percentage is relatively consistent (.73) and is also not very dependent on ballpark. One disadvantage of ground ball rate is that it is not an actual outcome. Getting a batter to hit a ground ball is fielding independent but getting the ground ball to turn into an out is not.

The statistic QERA, developed by Nate Silver at Baseball Prospectus, uses GB% instead of home runs:

QERA= (2.69 - SO% x .34 + BB% x 3.88 - GB% x .66)^2

While QERA is more predictive of future performance than ERA (.51 versus .33), I have not found it to be more predictive than FIP (.54). Still, GB% by itself is a useful tool which helps to describe an important pitching skill.

While a ground ball does not always produce a good result for a pitcher, it’s much less likely to produce a bad result than a line drive or a fly ball. Table 1 (data taken from a discussion at Fangraphs) shows that ground balls result in a much lower slugging average than either line drives or fly balls.

Table 1: Slugging Percentage By Batted Ball Type

Event	Slg
Line drive	.978
Ground ball	.220
Fly ball	.494

Futhermore, Table 2 (taken from the The Hardball Times Annual 2007) indicates that a ground ball is less likely to contribute to runs than either a fly ball or a line drive. The exception would be an infield fly but those are much less common than outfield flies. Whatever way you look at it, it is clear that the ability to get batters to hit the ball on the ground is a good thing.

Table 2: Run Impact of Batted Ball Type

Event	Run Impact
Line Drive	.391
HBP	.355
Walk	.355
Outfield Fly	.192
Intentional Walk	.075
Ground ball	.045
Bunt	.021
Infield fly	-.088
Strike out	-.113

Table 3 shows how Tigers starting pitchers (plus Dontrelle Willis) ranked in 2007 in ground ball percentage. Table 4 lists the top 20 ground ball pitchers in the American League in 2007. After having three starters (Kenny Rogers, Jeremy Bonderman and Nate Robertson in the top 12 in 2006, the Tigers top ground ball pitcher in 2007 was Bonderman who finished 16th at 48%. Rogers also had a 48% ground ball rate but was limited to 63 innings due to injuries. Nate Robertson had a league average ground ball rate (45%) while Justin Verlander finished at 41%.

My next article will further explore batted balls versus pitchers.

The raw data for Tables 3 and 4 were abstracted from The Hardball Times database.

Table 3: Ground ball Rates for Tigers (plus Dontrelle Willis) Starters in 2007

GB% Rank	Name	IP	GB%	ERA	FIP
16	Bonderman	174.3	0.48	5.01	4.22
23	Willis	205.3	0.46	5.17	5.10
33	Robertson	177.7	0.45	4.76	4.73
36	Durbin	127.7	0.44	4.72	5.73
45	Verlander	201.7	0.41	3.66	4.09
.	Jurrjens	30.7	0.38	4.70	5.40
.	Maroth	78.3	0.43	5.06	6.53
.	Miller	64.0	0.49	5.63	5.41
.	Rogers	63.0	0.48	4.43	5.13

Table 4: Top 20 Ground ball Rates in American League in 2007

GB% Rank	Name	Team	IP	GB%	ERA	FIP
1	Carmona	CLE	215.0	0.64	3.06	4.05
2	Hernandez	SEA	190.3	0.61	3.92	3.83
3	Wang	NYA	199.3	0.58	3.70	3.92
4	DiNardo	OAK	131.3	0.56	4.11	4.93
5	Loe	TEX	136.0	0.56	5.36	4.67
6	Burnett	TOR	165.7	0.55	3.75	4.44
7	Tavarez	BOS	134.7	0.54	5.15	4.79
8	Westbrook	CLE	152.0	0.54	4.32	4.37
9	Halladay	TOR	225.3	0.53	3.71	3.65
10	McGowan	TOR	169.7	0.53	4.08	3.82
11	Gaudin	OAK	199.3	0.51	4.42	4.71
12	Cabrera	BAL	204.3	0.50	5.55	5.06
13	Ramirez	SEA	98.0	0.48	7.16	5.60
14	Litsch	TOR	111.0	0.48	3.81	5.23
15	Bedard	BAL	182.0	0.48	3.16	3.33
16	Bonderman	DET	174.3	0.48	5.01	4.22
17	Pettitte	NYA	215.3	0.48	4.05	4.00
18	Silva	MIN	202.0	0.48	4.19	4.35
19	Beckett	BOS	200.7	0.47	3.27	3.22
20	Blanton	OAK	230.0	0.47	3.95	3.59

Tigers Extend Willis

According to ESPN, the Tigers have signed recently acquired Dontrelle Willis to a three year contract extension worth a reported $29 million. He would have been eligible for free agency after the 2009 season but is now locked up through 2010. The Tigers were able to get him signed up very quickly due to an off year in 2007 where he compiled a 5.17 ERA in 205 1/3 innings. In five years with the Marlins, he had a 3.78 ERA in 1,022 innings.

It's a little surprising to me that the Tigers moved to sign him before seeing how he looked this year. However, they could end up saving themselves some money as his value could rise substantially with a good year in 2008. The quick signing is an indication they are confident he will bounce back in 2008 which is a good sign.

FIP Analysis for Tiger Relievers in 2007

In an earlier post, I discussed team run prevention using FIP ERA to measure pitching performance and DER to measure fielding performance. Then I evaluated the performance of individual starting pitchers using FIP ERA. Today, I’ll look at the relievers. There were 82 primary relievers (more relief appearances than starts) with 40 or more innings pitched in 2007. Table 1 below lists Detroit Tiger relievers in 2007. Table 2 lists all 82 qualifiers in the league.

In both tables, the key variables are actual ERA, FIP ERA, FIP-Actual and LOB%. All are defined in the article on starters linked above. Since relievers pitch fewer innings than starters, all of these statistics are less reliable for relievers and should be interpreted with a little more caution. The averages for relievers in 2007 were: FIP (4.09), DER (0.71) and LOB% (0.74).

The following relievers had FIP ERAs which were worse than their actual actual ERAs: Bobby Seay (FIP ERA = 2.86, ERA = 2.33), Tim Byrdak (3.60, 3.20), and Zach Miner (3.85, 3.02). This is an indication that they may have not pitched quite as well as their ERAs indicated. On the other hand, Todd Jones (3.77, 4.26) and Jason Grilli (4.04, 4.74) had FIP ERAs lower than their ERAs which suggests that they may have been somewhat unlucky.

One thing that comes out of this analysis is that all six qualifying relievers had FIP ERAs which were league average or better. Since FIP ERA is a better predictor than ERA, this gives us reason for cautious optimism for 2008. However, keep in mind that sample sizes (of innings) for relievers are very small and that it's very hard to project relievers into the future. Also note that most of these pitchers do not have long track records of success. The bullpen is going to be another key factor to the team's success in 2008 and I'm still hoping they add another pitcher with a better track record.

The raw data for this report were abstracted from The Hardball Times database.


Table 1: FIP ERA Ranks for Tiger Relievers in 2007

FIP ERA Rank	Name	IP	ERA	FIP ERA	DER	FIP-Actual	LOB %
12	Seay	46.3	2.33	2.86	.722	0.53	.80
26	Byrdak	45.0	3.20	3.60	.708	0.40	.69
30	Jones	61.3	4.26	3.77	.704	-0.49	.70
32	Miner	53.7	3.02	3.85	.694	0.83	.76
36	Rodney	50.7	4.26	3.95	.707	-0.31	.68
39	Grilli	79.7	4.74	4.00	.694	-0.74	.65

Table 2: FIP ERA Ranks for AL Relievers in 2007

FIP ERA Rank	Name	Team	IP	ERA	FIP ERA	DER	FIP-Actual	LOB %
1	Betancourt	CLE	79.3	1.47	2.25	.760	0.78	.86
2	Soria	KC	69.0	2.48	2.51	.750	0.03	.74
3	Jenks	CHA	65.0	2.77	2.52	.757	-0.25	.69
4	Papelbon	BOS	58.3	1.85	2.59	.785	0.74	.88
5	Street	OAK	50.0	2.88	2.70	.748	-0.18	.68
6	Nathan	MIN	71.7	1.88	2.71	.724	0.83	.86
7	Rivera	NYA	71.3	3.15	2.71	.678	-0.44	.76
8	Bale	KC	40.0	4.05	2.81	.627	-1.24	.73
9	Putz	SEA	71.7	1.38	2.81	.803	1.43	.94
10	Brown	OAK	41.7	4.54	2.85	.675	-1.69	.65
11	Rodriguez	LAA	67.3	2.81	2.85	.701	0.04	.78
12	Seay	DET	46.3	2.33	2.86	.722	0.53	.80
13	Perez	CLE	60.7	1.78	3.05	.766	1.27	.84
14	Tallet	TOR	62.3	3.47	3.16	.730	-0.31	.70
15	Sherrill	SEA	45.7	2.36	3.18	.769	0.82	.84
16	Benoit	TEX	82.0	2.85	3.23	.710	0.38	.78
17	Downs	TOR	58.0	2.17	3.23	.714	1.06	.84
18	Frasor	TOR	57.0	4.58	3.26	.716	-1.32	.63
19	Okajima	BOS	69.0	2.22	3.38	.762	1.16	.86
20	Embree	OAK	68.0	3.97	3.45	.703	-0.52	.71
21	Thornton	CHA	56.3	4.79	3.52	.661	-1.27	.69
22	Accardo	TOR	67.3	2.14	3.53	.750	1.39	.81
23	Bradford	BAL	64.7	3.34	3.57	.679	0.23	.73
24	Green	SEA	68.0	3.84	3.57	.646	-0.27	.75
25	Neshek	MIN	70.3	2.94	3.59	.780	0.65	.76
26	Byrdak	DET	45.0	3.20	3.60	.708	0.40	.69
27	O'Flaherty	SEA	52.3	4.47	3.63	.723	-0.84	.64
28	Greinke	KC	122.0	3.69	3.76	.686	0.07	.76
29	Peralta	KC	87.7	3.80	3.76	.689	-0.04	.74
30	Jones	DET	61.3	4.26	3.77	.704	-0.49	.70
31	Oliver	LAA	64.3	3.78	3.83	.725	0.05	.68
32	Miner	DET	53.7	3.02	3.85	.694	0.83	.76
33	Janssen	TOR	72.7	2.35	3.89	.727	1.54	.81
34	Casilla	OAK	50.7	4.44	3.93	.730	-0.51	.72
35	Delcarmen	BOS	44.0	2.05	3.93	.786	1.88	.87
36	Rodney	DET	50.7	4.26	3.95	.707	-0.31	.68
37	Speier	LAA	50.0	2.88	3.96	.767	1.08	.80
38	Wilson	TEX	68.3	3.03	3.97	.743	0.94	.77
39	Grilli	DET	79.7	4.74	4.00	.694	-0.74	.65
40	Shields	LAA	77.0	3.86	4.00	.724	0.14	.71
41	Guerrier	MIN	88.0	2.35	4.02	.750	1.67	.88
42	Gobble	KC	53.7	3.02	4.03	.671	1.01	.80
43	Walker	BAL	61.3	3.23	4.05	.734	0.82	.75
44	Borowski	CLE	65.7	5.07	4.08	.670	-0.99	.68
45	Morrow	SEA	63.3	4.12	4.09	.686	-0.03	.76
46	Ray	BAL	42.7	4.43	4.11	.727	-0.32	.69
47	Bootcheck	LAA	77.3	4.77	4.12	.690	-0.65	.67
48	Vizcaino	NYA	75.3	4.30	4.12	.729	-0.18	.72
49	Moseley	LAA	92.0	4.40	4.16	.696	-0.24	.70
50	Francisco	TEX	59.3	4.55	4.21	.693	-0.34	.69
51	Lopez	BOS	40.7	3.10	4.22	.726	1.12	.76
52	Mastny	CLE	57.7	4.68	4.23	.665	-0.45	.76
53	Calero	OAK	40.7	5.75	4.36	.664	-1.39	.66
54	Riske	KC	69.7	2.45	4.41	.736	1.96	.90
55	Wolfe	TOR	45.3	2.98	4.44	.772	1.46	.75
56	Parrish	BAL	41.7	5.40	4.51	.691	-0.89	.68
57	Myers	NYA	40.7	2.66	4.63	.737	1.97	.81
58	Timlin	BOS	55.3	3.42	4.66	.767	1.24	.75
59	Duckworth	KC	46.7	4.63	4.73	.706	0.10	.64
60	MacDougal	CHA	42.3	6.80	4.73	.641	-2.07	.59
61	Nunez	KC	43.7	3.92	4.75	.717	0.83	.77
62	Ortiz	MIN	91.0	5.14	4.75	.691	-0.39	.68
63	Logan	CHA	50.7	4.97	4.80	.683	-0.17	.71
64	Marshall	OAK	42.0	6.43	4.88	.689	-1.55	.60
65	Eyre	TEX	68.0	5.16	4.95	.688	-0.21	.69
66	Reyes	TB	60.7	4.90	4.95	.757	0.05	.69
67	Camp	TB	40.0	7.20	4.98	.582	-2.22	.69
68	Villone	NYA	42.3	4.25	5.01	.752	0.76	.74
69	Glover	TB	77.3	4.89	5.05	.691	0.16	.72
70	Farnsworth	NYA	60.0	4.80	5.08	.717	0.28	.71
71	Wright	TEX	77.0	3.62	5.09	.724	1.47	.76
72	Rincon	MIN	59.7	5.13	5.11	.694	-0.02	.70
73	Bell	BAL	53.0	5.94	5.12	.656	-0.82	.69
74	Littleton	TEX	48.0	4.31	5.13	.731	0.82	.75
75	Bruney	NYA	50.0	4.68	5.40	.729	0.72	.73
76	Proctor	NYA	54.3	3.81	5.53	.732	1.72	.79
77	Snyder	BOS	54.3	3.81	5.53	.756	1.72	.74
78	Wood	TEX	50.7	5.33	5.77	.674	0.44	.69
79	Rheinecker	TEX	50.3	5.36	5.78	.675	0.42	.68
80	Fossum	TB	76.0	7.70	5.81	.643	-1.89	.59
81	Stokes	TB	62.3	7.07	5.85	.641	-1.22	.67
82	Baez	BAL	50.3	6.44	6.14	.738	-0.30	.67