Update: SO > TB, Minimum 200 AB

Today I'm revisiting my first real post on this blog. Back in 2007, my first topic was hitters who wound up with more strikeouts than total bases. To make sure I only got players who spent a significant time in the majors, I set the minimum to qualify for the list at 200 at bats. It turns out three players have officially joined the list since the original post.

Name	Year	Team	Pos	AB	AVG	OBP	SLG	TB	SO	OPS+
Bill Bergen	1911	BRO	C	227	.132	.183	.154	35	42	-4
Billy Consolo	1954	BOS	SS	242	.227	.324	.277	67	69	59
Billy Consolo	1959	BOS WSH	SS	216	.213	.331	.269	58	59	67
Ernie Fazio	1963	HOU	2B	228	.184	.273	.281	64	70	65
Jerry Kindall	1963	CLE	2B	234	.205	.266	.295	69	71	58
Dave Nicholson	1964	CHW	LF	294	.204	.329	.365	107	126	96
Chris Cannizzaro	1965	NYM	C	251	.183	.270	.231	58	60	46
Don Zimmer	1965	WSA	C	226	.199	.284	.252	57	59	55
Ray Oyler	1966	DET	SS	210	.171	.263	.252	53	62	48
Jerry Zimmerman	1967	MIN	C	234	.167	.243	.192	45	49	26
Ray Oyler	1968	DET	SS	215	.135	.213	.186	40	59	20
George Scott	1968	BOS	1B	350	.171	.236	.237	83	88	40
Dick Tracewski	1968	DET	SS	212	.156	.239	.236	50	51	43
Al Weis	1968	NYM	SS	274	.172	.234	.204	56	63	32
Darrel Chaney	1969	CIN	SS	209	.191	.278	.234	49	75	42
Ray Oyler	1969	SEP	SS	255	.165	.260	.267	68	80	49
Jim Mason	1975	NYY	SS	223	.152	.228	.211	47	49	27
John Hale	1978	SEA	RF	211	.171	.283	.265	56	64	56
Leroy Stanton	1978	SEA	LF	302	.182	.265	.248	75	80	47
Bobby Bonds	1980	STL	LF	231	.203	.305	.316	73	74	72
Tom Donohue	1980	CAL	C	218	.188	.216	.243	53	63	27
Reggie Jackson	1983	CAL	RF	397	.194	.290	.340	135	140	74
Gary Pettis	1987	CAL	CF	394	.208	.302	.259	102	124	53
Jody Davis	1989	ATL	C	231	.169	.246	.242	56	61	39
John Shelby	1989	LAD	CF	345	.183	.237	.229	79	92	36
Jeff Kunkel	1990	TEX	SS	200	.170	.221	.280	56	66	40
Rob Deer	1991	DET	RF	448	.179	.314	.386	173	175	92
Hensley Meulens	1991	NYY	LF	288	.222	.276	.319	92	97	65
Gary Pettis	1991	TEX	CF	282	.216	.341	.277	78	91	75
Andujar Cedeno	1992	HOU	SS	220	.173	.232	.277	61	71	47
Jack Clark	1992	BOS	DH	257	.210	.350	.311	80	87	82
Billy Ashley	1995	LAD	LF	215	.237	.320	.372	80	88	90
Benji Gil	1995	TEX	SS	415	.219	.266	.347	144	147	60
Kimera Bartee	1996	DET	CF	217	.253	.308	.304	66	77	57
Archi Cianfrocco	1997	SDP	1B	220	.245	.328	.355	78	80	85
Mark Johnson	1997	PIT	1B	219	.215	.345	.315	69	78	73
Ryan McGuire	1998	MON	1B	210	.186	.292	.243	51	55	46
Greg Vaughn	2002	TBD	LF	251	.163	.286	.315	79	82	60
Mark Bellhorn	2005	BOS NYY	2B	300	.210	.324	.357	107	112	81
Mark Bellhorn	2006	SDP	3B	253	.190	.285	.344	87	90	66
Ryan Langerhans	2007	ATL OAK WSN	OF	210	.167	.272	.305	64	81	53
Andruw Jones	2008	LAD	CF	209	.158	.256	.249	52	76	34
Tony Pena Jr.	2008	KCR	SS	225	.169	.189	.209	47	49	7
Name	Year	Team	Pos	AB	AVG	OBP	SLG	TB	SO	OPS+

I think it's cool that Pena became only the second player with an OPS+ of under 10 to show up. In fact, he is the first player since Bill Bergen a century ago to have an OPS+ that low under in 200+ at bats.

In addition to Langerhans, Jones, and Pena, Jeff Mathis of the Angels deserves a mention. In 2008 he came to bat 283 times and wound up with 90 total bases. He also struck out 90 times. Darrel Chaney in 1973 was the last player to have equal strikeouts and total bases in 200 or more at bats.

I wonder which hitters will linger long enough in the big leagues next year to make the list. I guess we'll see...

WHIP<=1.000, Qualified for ERA Title

By now you've no doubt heard about the large offer extended by the New York Yankees to free agent pitcher CC Sabathia. As I looked at Sabathia's 2008 stats, I noticed that he had a WHIP of 1.003 for Milwaukee as he led the Brewers to the playoffs. Sabathia made half his starts for Milwaukee and half for Cleveland. Since his WHIP for the Indians was 1.234, his 2008 WHIP wound up at 1.115, a little bit lower than his Cy Young season of 2007.

WHIP is an acronym for Walks + Hits over Innings Pitched, a way of measuring how many baserunners a pitcher allows. Obviously, the fewer baserunners a pitcher allows, the harder it is for the opposing offense to score runs. Over the past five years, the major league average WHIP is around 1.400. So Sabathia's 1.115 WHIP is very good, indeed. It's nowhere near record-setting, however.

Since 1990, eleven different pitchers have qualified for the ERA title (1 IP per team game, usually 162 IP in a season) with a WHIP of 1.000 or lower a total of twenty-two times. Since 1901, ninety-eight different pitchers did it 161 total times. It's possible to find different eras in baseball history by looking at the list. From 1901 to 1920, the deadball era, eighty of those 161 seasons were recorded. From 1921 to the start of World War II, when offense reigned, only one pitcher made the list (Carl Hubbell, 1933). The 1950's only saw two pitchers join. The so-called "Year of the Pitcher," 1968, had nine pitchers accomplish the feat. You get the idea.

It's kind of interesting that while offense in the late 1990's and 2000's increased to levels not consistently seen since the 1930's, the number of pitchers with a WHIP under 1.00 hasn't been impacted like it was back then. Presumably this has something to do with increased strikeouts; if hitters aren't putting the ball in play as much, they don't have as many chances of those balls falling in for hits, thus inflating the pitcher's WHIP.

Whatever the reason, there have been twenty-two sub-1.000 WHIP seasons since 1990. The list of names reads like a future Hall of Fame ballot, with a couple exceptions.

WHIP <= 1.000, Qualified for ERA Title (1990-2008)

Name	Year	Walks	Hits	IP	WHIP
Curt Schilling	1992	59	165	226.1	0.990
Greg Maddux*	1994	31	150	202.0	0.896
Greg Maddux*	1995	23	147	209.2	0.811
Kevin Brown	1996	33	187	233.0	0.944
Pedro Martinez*	1997	67	158	241.1	0.932
Greg Maddux	1997	20	200	232.2	0.946
Greg Maddux	1998	45	201	251.0	0.980
Pedro Martinez*	1999	37	160	213.1	0.923
Kevin Millwood	1999	59	168	228.0	0.996
Pedro Martinez*	2000	32	128	217.0	0.737
Kevin Brown	2000	47	181	230.0	0.991
Derek Lowe	2002	48	166	219.2	0.974
Pedro Martinez	2002	40	144	199.1	0.923
Odalis Perez	2002	38	182	222.1	0.990
Curt Schilling	2002	33	218	259.1	0.968
Jason Schmidt	2003	46	152	207.2	0.953
Ben Sheets	2004	32	201	237.0	0.983
Johan Santana*	2004	54	156	228.0	0.921
Randy Johnson	2004	44	177	245.2	0.900
Pedro Martinez	2005	47	159	217.0	0.949
Johan Santana	2005	45	180	231.2	0.971
Johan Santana*	2006	47	186	233.2	0.997

* - Cy Young Award winner

Pedro Martinez's 0.737 WHIP in 2000 is an all-time record. The only other pitcher to have a WHIP under 0.800 was Walter Johnson in 1913 (0.780). Addie Joss had a 0.806 WHIP in 1908, and Greg Maddux's 0.811 in 1995 is fourth all-time.

The major league WHIP leader in 2008 was Toronto's Roy Halladay. He issued 39 walks and allowed 220 hits in 246 innings, good for a 1.053 WHIP. The 2007 leader was Jake Peavy of the Padres at 1.061 (169 hits, 68 walks, 223 1/3 innings). Justin Duchscherer wound up 20 1/3 innings short of joining the list in 2008: he had a WHIP of 0.995 in 141 2/3 innings.

John Smoltz in 1996 got as close as you can get to a 1.000 WHIP without actually getting there. He allowed 199 hits and 55 walks in 253 2/3 innings. He was one out short of a 1.000 WHIP, but he had to settle for 1.001. Maybe I should've rounded?

Hitters' Performance in Team Wins and Losses

In the Milwaukee Journal Sentinal's regularly updated baseball blog, beat writer Tom Haudricourt recently noted slugger Prince Fielder's performance seemed to be an integral part of the team's wins and losses (link). This idea was later put into a print article (web version). It fell to fellow slugger Ryan Braun to debunk the idea that Fielder was mostly responsible for the team winning and losing. Braun said,

"When you lose close games, you're facing better pitchers in the bullpen, the set-up guy, the closer," he said. "Whereas when you're squaring balls up and scoring runs, you might get the last guy in the bullpen.

"It would be almost impossible for it to be the other way around."

Indeed, it is rare to find a regular player who managed to hit better in team losses than he did in team wins. In fact, of the 280 players who had 300 or more plate appearances in 2007, only six had a higher OPS in team losses. Twenty-six players had a drop of .400 or more in their OPS from team wins to team losses.

If you look at all players who had at least 200 plate appearances in team wins, the composite hitter put up a .319/.392/.527 line, good for a .919 OPS. Pretty darn good when you consider that's about what David Wright has done in his career. Part of that can be explained by the .343 BABIP for those hitters (more on BABIP can be found here). Given that the MLB BABIP in 2007 was .303, this means hitters on teams that won games had hits fall in more often than usual. This makes sense - how many games can you recall turning on bloop hits here and there? Similarly, players with 200+ PA in team losses had worse luck: their BABIP was only .276. Those hitters put up a composite .242/.307/.373 line, good for a .681 OPS - about the same level of production as Endy Chavez.

So which players declined (or, in the case of the aforementioned six, improved) the most when going from team wins to team losses? Below is a table of the players with the twenty largest drops in OPS from wins to losses along with their corresponding BABIP. Beneath that table is another showing the twenty smallest declines in OPS from wins to losses (negative numbers correspond to OPS and BABIP increases).

20 Largest OPS Differences (Wins-Losses), 2007 Minimum 300 Plate Appearances
Name	Team	Total PA	OPS Diff.	BABIP Diff.
Miguel Cabrera	FLA	680	.599	.178
Matt Holliday	COL	713	.577	.137
Kenny Lofton	TEX/CLE	559	.521	.341
Xavier Nady	PIT	470	.497	.143
Matt Kemp	LAD	311	.482	.134
Chris Duncan	STL	432	.476	.057
Josh Willingham	FLA	604	.465	.169
Bobby Abreu	NYY	699	.462	.159
Hunter Pence	HOU	484	.451	.087
Magglio Ordonez	DET	679	.450	.128
Jack Cust	OAK	507	.449	.135
Mark Grudzielanek	KCR	486	.448	.130
Marlon Byrd	TEX	454	.448	.105
Brad Hawpe	COL	606	.447	.090
Jim Thome	CHW	536	.439	.097
Chase Utley	PHI	613	.429	.081
Gary Matthews Jr.	LAA	579	.425	.149
Vernon Wells	TOR	642	.423	.125
J.D. Drew	BOS	552	.421	.123
Travis Buck	OAK	334	.418	.094

Many of the players on that list are pretty good hitters overall. I think it's interesting to see guys like Marlon Byrd and Mark Grudzielanek up there, too, since they're not anyone's idea of great hitters. Nevertheless, they raked whenever the Rangers and Royals won.

I just want to note one final time that negative numbers in the table below actually indicate an increase in OPS or BABIP from team wins to team losses.

20 Smallest OPS Differences (Wins-Losses), 2007 Minimum 300 Plate Appearances
Name	Team	Total PA	OPS Diff.	BABIP Diff.
Miguel Olivo	FLA	469	-.068	-.028
Greg Dobbs	PHI	358	-.042	.030
Shawn Green	NYM	491	-.024	.027
Nate McLouth	PIT	382	-.013	-.009
Andre Ethier	LAD	507	-.008	-.073
Mike Jacobs	FLA	460	-.003	.030
Ryan Theriot	CHC	597	.006	.002
Jose Vidro	SEA	625	.022	-.015
Aaron Hill	TOR	657	.023	.064
Wily Mo Pena	BOS/WSN	317	.028	-.014
Lyle Overbay	TOR	476	.031	.028
Placido Polanco	DET	641	.033	.022
Ryan Garko	CLE	541	.042	-.041
Josh Bard	SDP	443	.044	-.003
Ron Belliard	WSN	557	.046	.029
Brian Giles	SDP	552	.051	.026
Dave Roberts	SFG	443	.055	.012
Melvin Mora	BAL	527	.057	.037
Casey Blake	CLE	662	.060	.038
Corey Patterson	BAL	503	.067	.032

Nothing seems to have fazed Nate McLouth or Ryan Theriot last season. They just kept on putting up their regular numbers regardless of whether the team won or lost. Dobbs, Green, and Jacobs are interesting because their OPS increased while their BABIP decreased. All in all, the second list doesn't seem as impressive as the first list in terms of hitter quality. It's kind of cool that Florida had the guys with the largest and smallest declines in OPS from team wins to team losses.

Last Position Players to Pitch by Team

UPDATE: I've posted a table through May 6, 2009 here.

It's always notable when a position player takes the mound for an inning or two. Usually it only happens in blowouts when a manager wants to save the other arms in the bullpen for another day. While it hasn't happened yet this season, six position players on four different teams toed the rubber at some point in 2007 (Can you name them? Answers at the end of the post). For this post I looked up the last position players to pitch for every team. Surprisingly, three of the four teams that have gone the longest without using a position player on the mound play in the National League.

Last Position Player to Pitch by Team

Team	Name	Date
Arizona Diamondbacks	Jeff Cirillo	8-20-2007
Atlanta Braves	John Russell	6-25-1989
Baltimore Orioles	Manny Alexander	4-19-1996
Boston Red Sox	David McCarty	10-3-2004
Chicago Cubs	Gary Gaetti	7-3-1999
Chicago White Sox	Dave Martinez	8-4-1995
Cincinnati Reds	Lenny Harris	6-1-1998
Cleveland Indians	Tim Laker	4-20-2004
Colorado Rockies	Todd Zeile	9-14-2002
Detroit Tigers	Shane Halter	10-1-2000
Florida Marlins	Jason Wood	6-29-2007
Houston Astros	Tim Bogar	6-24-2000
Kansas City Royals	Shane Halter	7-17-1998
Los Angeles Angels	Chili Davis	6-17-1993
Los Angeles Dodgers	Robin Ventura	6-25-2004
Milwaukee Brewers	Trent Durrington	4-17-2004
Minnesota Twins	John Moses	7-31-1990
New York Mets	Todd Zeile	7-26-2004
New York Yankees	Wade Boggs	8-19-1997
Oakland Athletics	Frank Menechino	7-18-2000
Philadelphia Phillies	Tomas Perez	5-13-2002
Pittsburgh Pirates	Abraham Nunez	5-30-2004
San Diego Padres	Sean Burroughs	9-20-2005
Seattle Mariners	John Mabry	5-28-2000
San Francisco Giants	Greg Litton	7-4-1991
St. Louis Cardinals	Aaron Miles	9-20-2007
Tampa Bay Rays	Josh Wilson	6-8-2007
Texas Rangers	Scott Sheldon	9-6-2000
Toronto Blue Jays	Frank Menechino	8-28-2004
Washington Nationals	Junior Noboa	7-20-1990*

* - Fellow position player Dave Martinez pitched right before Noboa in the same game.

I wonder which team will have a position player pitch first this season. The Braves already got creative by having a pitcher play the outfield (Chris Resop on April 4) for one batter, but it's been almost twenty years since a position player pitched for them.

As promised, the six position players to pitch last season:

• Jeff Cirillo - Arizona Diamondbacks
• Aaron Miles - St. Louis Cardinals
  
• Augie Ojeda - Arizona Diamondbacks
• Scott Spiezio - St. Louis Cardinals
  
• Josh Wilson - Tampa Bay Devil Rays
  
• Jason Wood - Florida Marlins
  

Playoff Rotations, 2003-2007

Anyone who's been a regular reader here knows how I've already looked at rotation spots throughout MLB in terms of FIP and ERA. The numbers for each league in 2007 and data for 2003-2007 using both statistics can be found here. The methodology is also explained there.

I've noticed some people disparaging the notion of a pitcher putting up league average numbers having much value. After all, the reasoning goes, league average includes all the bad teams whereas the average rotation to make the playoffs would be more telling (because no mediocre teams make the playoffs). Snark aside, there's a certain logic in that line of thinking. Making the playoffs with a below average rotation is possible (see: 2007 Phillies), but rare.

With that in mind, I decided to crunch the numbers and find out the rotation numbers of playoff teams over the past five seasons. Treating all four teams each year as one giant staff starting approximately 648 games, I then figured out the FIP and ERA for each rotation spot. Below are the results compared to the relevant league average for each season. The numbers (#1, #2, etc.) correspond to each spot in the rotation.

FIP: AL Playoff Teams vs. AL Average, 2003-2007

Year	Team	FIP	#1	#2	#3	#4	#5
2003	AL Playoff Teams	4.10	3.18	3.77	4.23	4.43	5.15
	AL Average	4.73	3.57	4.30	4.78	5.17	6.30
2004	AL Playoff Teams	4.38	3.42	3.93	4.34	4.95	5.55
	AL Average	4.80	3.75	4.40	4.77	5.19	6.11
2005	AL Playoff Teams	4.33	3.60	4.05	4.30	4.56	5.43
	AL Average	4.56	3.65	4.18	4.56	4.92	5.77
2006	AL Playoff Teams	4.49	3.31	4.19	4.47	4.81	6.03
	AL Average	4.66	3.55	4.18	4.63	5.08	6.31
2007	AL Playoff Teams	4.18	3.22	3.80	4.12	4.50	5.67
	AL Average	4.47	3.47	4.01	4.45	4.88	6.02
Last 5	AL Playoff Teams	4.29	3.31	3.96	4.28	4.61	5.63
	AL Average	4.64	3.60	4.21	4.64	5.05	6.13

Only in one spot in on year did the league out-perform the playoff teams. In 2006, the league average #2 starter had an FIP of 4.18 compared to the playoff teams' 4.19. Otherwise the playoff squads handily outpaced the rest of the league. The average playoff team's starter FIP was between 92.6% that of the league's. Note, however, that a league average starter (by FIP) still makes a good #4 pitcher for a playoff team based on the last five seasons.

ERA: AL Playoff Teams vs. AL Average, 2003-2007

Year	Team	ERA	#1	#2	#3	#4	#5
2003	AL Playoff Teams	4.15	2.66	3.66	4.30	4.61	6.04
	AL Average	4.66	3.18	4.05	4.56	5.37	6.97
2004	AL Playoff Teams	4.47	3.22	4.03	4.58	4.99	6.27
	AL Average	4.83	3.57	4.35	4.84	5.22	6.93
2005	AL Playoff Teams	4.15	3.21	3.59	4.00	4.52	6.17
	AL Average	4.52	3.21	3.85	4.40	5.07	6.73
2006	AL Playoff Teams	4.38	3.16	3.80	4.19	4.81	6.58
	AL Average	4.73	3.36	4.17	4.62	5.10	7.06
2007	AL Playoff Teams	4.29	3.07	3.70	4.26	4.73	6.27
	AL Average	4.61	3.29	3.88	4.42	5.23	7.00
Last 5	AL Playoff Teams	4.29	3.02	3.77	4.26	4.74	6.29
	AL Average	4.67	3.32	4.06	4.56	5.20	6.93

Again the playoff teams sink to league average in only one spot: #1 pitchers on playoff teams in 2005 were league average. Of course, when the rest of your rotation outpitches everyone else, you can afford that. The average playoff team ERA was 91.8% that of the league, or about the same as the difference in FIP. Not surprisingly, then, a league average pitcher slots in at #4 on a playoff team using ERA again.

So now that it turns out a league average starter is generally a good #4 starter on a playoff team in the American League, let's turn to the senior circuit. Pitching in the NL is considered to have a positive effect on a pitcher's statistics since opposing pitchers bat for themselves and the NL FIP has been below that of the AL in four of the past five seasons (2007 is the exception). Similarly, the NL ERA was higher than the AL ERA only in 2007. Perhaps, then, this skews the importance of league average starters to NL playoff teams.

FIP: NL Playoff Teams vs. NL Average, 2003-2007

Year	Team	FIP	#1	#2	#3	#4	#5
2003	NL Playoff Teams	4.13	3.08	3.82	4.14	4.55	5.42
	NL Average	4.55	3.42	4.13	4.52	4.95	6.15
2004	NL Playoff Teams	4.50	3.38	4.08	4.47	4.92	6.17
	NL Average	4.61	3.37	4.14	4.63	5.09	6.47
2005	NL Playoff Teams	4.20	3.11	3.68	4.36	4.72	5.48
	NL Average	4.45	3.35	4.05	4.43	4.95	5.85
2006	NL Playoff Teams	4.65	3.56	4.16	4.72	5.12	5.97
	NL Average	4.66	3.62	4.21	4.63	5.07	6.25
2007	NL Playoff Teams	4.66	3.64	4.34	4.70	5.01	5.90
	NL Average	4.60	3.48	4.17	4.66	5.04	6.04
Last 5	NL Playoff Teams	4.42	3.28	4.03	4.46	4.89	5.83
	NL Average	4.57	3.45	4.14	4.57	5.02	6.15

The past two seasons have been interesting in the National League. The general mediocrity of the starting staffs of the Cardinals and Mets in 2006 contributed the most to the #3 and #4 spots on playoff teams doing worse than league average (the Cardinals #3 starters had a 5.31 FIP!). Of course, each of those teams had better than average results from their fifth starters which no doubt helped them win enough games to get into the playoffs.

Last season is a different story. The Rockies (4.67) and Phillies (4.86) both had below average starting staffs overall. The Diamondbacks (4.58) and Cubs (4.54) were above average, but not by much. Cumulatively, this means the average playoff rotation was worse than league average overall. Only in the fourth and fifth starter spots did the playoff teams manage to outperform the league. There might be a moral in there (depth! depth! depth!). In any event, the National League in the past two seasons has shown that if you can run a half-decent staff out there and mash the ball, you've got a real shot.

The average NL playoff team rotation over the past five years put up an FIP that was 96.8% that of the league. Again, a league average starter slots in as a #4 overall, but in the past two seasons, playoff teams could use such a pitcher as a #3 guy. Maybe ERA will clear up the picture: perhaps these FIP-challenged teams were ERA-lucky.

ERA: NL Playoff Teams vs. NL Average, 2003-2007

Year	Team	ERA	#1	#2	#3	#4	#5
2003	NL Playoff Teams	3.90	2.75	3.45	3.90	4.24	5.66
	NL Average	4.40	2.97	3.81	4.24	4.92	7.04
2004	NL Playoff Teams	4.12	3.03	3.61	4.04	4.35	6.76
	NL Average	4.43	3.00	3.75	4.22	4.87	7.55
2005	NL Playoff Teams	3.79	2.42	3.09	3.78	4.45	5.66
	NL Average	4.23	2.81	3.70	4.23	4.70	6.23
2006	NL Playoff Teams	4.46	3.31	3.74	4.21	4.90	6.17
	NL Average	4.65	3.25	4.00	4.57	5.12	7.07
2007	NL Playoff Teams	4.47	3.43	4.00	4.30	4.78	6.51
	NL Average	4.64	3.29	3.97	4.50	5.12	7.03
Last 5	NL Playoff Teams	4.14	2.86	3.63	4.07	4.54	6.29
	NL Average	4.47	3.07	3.85	4.35	4.95	6.98

ERA makes recent playoff teams look a little better. Only the #1 and #2 (barely) starters last season were substandard, while only 2006 aces were below average. As long as most of your rotation outperforms their equivalents around the league, you can deal with a slightly below average top dog. The #1 pitchers in 2004 didn't get lucky in this table either, still finishing a little below the league average.

The playoff team ERA is 92.7% that of the league average over the past five seasons. That's close to the American League's numbers for FIP and ERA. League average starters are, yet again, good #4 starters on playoff teams.

I can see some people complaining that numbers like FIP and ERA don't get you into the playoffs: it's wins that count! With that in mind, I averaged the wins by each starting staff in each league in each season. In the American League, playoff teams could expect about 70 wins from their rotation each year. In the National League, that number drops to 65 wins. Either way, I think the moral of the story is it takes good defense combined with great offense to overcome a league average pitching staff and make the playoffs, but it's certainly possible.

2007 NL LOB/RISP Data

I thought it'd be interesting to look at the numbers of baserunners (a guy that hits a home run doesn't count as a baserunner for this) left on base and in scoring position by each team in the National League. To do that, I'm going to use a table to show raw numbers for all of the teams and then a number of lists for some further percentages.

In the following table, LOB, as usual, stands for Left On Base, RISP stands for Runners In Scoring Position, RLISP is Runners Left In Scoring Position, and RISPR is Runners In Scoring Position Runs, my lingo for runs scored by guys who began the run-scoring play in scoring position. You'll note RLISP and RISPR values don't always add up to RISP values. This is because teams make outs on the basepaths - runners picked off second or third or thrown out at third or home plate may have started the play in scoring position but may not have made the final out of the inning. If they did make the final out of the inning, I considered them runners left in scoring position. Perhaps that's not the right way to interpret the term but I figure in most cases they could have pulled up a base short and not been thrown out or gotten picked off; either way, the risk they took hurt their team and I wanted to reflect this in the numbers. What's the difference between a guy absentmindedly being picked off third base and a guy who's too busy swinging for the fences to make contact with RISP and two outs in the long run?

2007 NL Raw Numbers for Baserunners

Team	Baserunners	LOB	RISP	RLISP	RISPR
Colorado	2156	1251	1292	716	556
Philadelphia	2151	1295	1296	722	546
Atlanta	2035	1205	1221	667	525
New York	2032	1196	1221	672	519
Los Angeles	2019	1200	1209	666	508
St. Louis	1996	1167	1157	639	494
Chicago	1993	1190	1194	661	494
Florida	1970	1196	1140	644	465
Cincinnati	1961	1170	1124	645	452
Houston	1950	1181	1133	653	455
Washington	1921	1163	1093	629	441
Pittsburgh	1903	1119	1123	611	484
San Francisco	1901	1141	1099	612	453
San Diego	1889	1152	1098	604	472
Milwaukee	1863	1117	1084	614	442
Arizona	1826	1090	1058	592	437
NL Sums	31566	18833	18542	10347	7743
NL Averages	1973	1177	1159	647	484

You can see every team was within 330 baserunners of each other; that's a little over two per game. Alone, these numbers don't say much: so what if Arizona left the fewest runners on base, they had the fewest opportunities to leave guys out there. With that in mind, here's the list of teams ranked by lowest to highest LOB%:

1. Colorado, 58.02% of baserunners left on base
2. St. Louis, 58.47%
3. Pittsburgh, 58.80%
4. New York, 58.86%
5. Atlanta, 59.21%
6. Los Angeles, 59.44%
7. NL Average, 59.66%
   
8. Cincinnati, 59.66%
9. Arizona, 59.69%
10. Chicago, 59.71%
11. Milwaukee, 59.96%
12. San Francisco, 60.02%
13. Philadelphia, 60.20%
14. Washington, 60.54%
15. Houston, 60.56%
16. Florida, 60.71%
17. San Diego, 60.98%

The fact playoff contenders and non-contenders are all jumbled up is a pretty good clue that LOB numbers don't have much bearing on a team's overall success. The fact all teams are within 3 percentage points of each other is another -- given the league average number of baserunners, 3% is 59 baserunners. That's about 1 every three games; hardly a huge number.

If you get on base, your ultimate destination is home plate. It's much easier for your teammates to bring you home if you are on second or third base--they only need to hit a single in most cases--so I want to look at which teams had the highest percentage of baserunners who got into scoring position.

1. Philadelphia, 60.25% of baserunners got into scoring position
2. New York, 60.09%
3. Atlanta, 60.00%
4. Colorado, 59.93%
5. Chicago, 59.91%
6. Los Angeles, 59.88%
7. Pittsburgh, 59.01%
8. NL Average, 58.74%
9. Milwaukee, 58.19%
10. San Diego, 58.13%
11. Houston, 58.10%
12. St. Louis, 57.97%
13. Arizona, 57.94%
14. Florida, 57.87%
15. San Francisco, 57.81%
16. Cincinnati, 57.32%
17. Washington, 56.90%

Good and bad teams are still jumbled up, though perhaps not as much as before. It's kind of intuitive that if you get more runners into scoring position, you'll likely have a better offense anyway. One other thing to note: teams that knock out a bunch of extra base hits don't need runners in scoring position as much. If you're hitting home runs a lot, you can score runners from first just fine.

So, of all those guys to get into scoring position, which team was best at not stranding them there?

1. Pittsburgh, 54.41% of RISP stranded
2. Atlanta, 54.63%
3. San Diego, 55.01%
4. New York, 55.04%
5. Los Angeles, 55.09%
6. St. Louis, 55.23%
7. Chicago, 55.36%
8. Colorado, 55.42%
9. San Francisco, 55.69%
10. Philadelphia, 55.71%
11. NL Average, 55.80%
12. Arizona, 55.95%
13. Florida, 56.49%
14. Milwaukee, 56.64%
15. Cincinnati, 57.38%
16. Washington, 57.55%
17. Houston, 57.63%

If you thought Pittsburgh was the best at not leaving runners in scoring position, congratulations. The fact the league average is below ten teams underscores just how out of whack the five bottom teams were. Of course, and I don't know if this is true, it's possible those were the most conservative teams - if you don't try and take extra bases with less than two outs, you can't get thrown out doing it. Similarly, maybe teams near the top were more reckless than others.

Finally, which teams were the best at bringing their RISP around to score?

1. Pittsburgh, 43.10% of RISP scored
2. Colorado, 43.03%
3. Atlanta, 43.00%
4. San Diego, 42.99%
5. St. Louis, 42.70%
6. New York, 42.51%
7. Philadelphia, 42.13%
8. Los Angeles, 42.02%
9. NL Average, 41.76%
10. Chicago, 41.37%
11. Arizona, 41.30%
12. San Francisco, 41.22%
13. Florida, 40.79%
14. Milwaukee, 40.77%
15. Washington, 40.35%
16. Cincinnati, 40.21%
17. Houston, 40.16%

I guess Pittsburgh wasn't reckless after all; I didn't realize they scored the highest percentage of runners in scoring position. Be that as it may, again there's about a 3% difference between the top and bottom teams. Given the league average number of runners in scoring position for a team, that's about 35 runs per season, or one every four games. Teams near the bottom of this can mitigate their lack of RISP conversion by hitting a lot of home runs; you'd be hard pressed to say Milwaukee and Cincinnati didn't have good offenses last season.

Getting Worse as the Game Goes On

As mentioned yesterday, there are always exceptions to the rule in baseball. Though the majority of players improve the more they see a pitcher in a certain game, some unlucky few actually do worse. A lot of this is because of the BABIP concept I brought up yesterday: if you're not getting bloop singles, your batting average, OBP, and slugging percentage will all go down. Thus a number of the players on the list below may simply have had a big downturn in their BABIP causing their OPS to drop. A few, whom I'll note after the list, actually have seen this sort of drop, though not as dramatic, throughout their careers. I've kept the last column of the table as "OPS Increase" just so it's not confusing switching between this post and the last one; that's why there are a bunch of negatives.

Facing Opposing Starters in a Game
Largest Decrease in OPS, 1st to 3rd (or greater) Time

Rank	Name	1st Time vs. SP	2nd Time vs. SP	3rd+ Time vs. SP	OPS Increase (1st to 3rd+)
1	Jack Wilson	131 PA, 1.014 OPS	127 PA, .772 OPS	92 PA, .571 OPS	-.443
2	Morgan Ensberg	74 PA, .940 OPS	62 PA, .834 OPS	59 PA, .528 OPS	-.412
3	Gary Matthews	136 PA, .889 OPS	133 PA, .716 OPS	131 PA, .526 OPS	-.363
4	Adam LaRoche	148 PA, .920 OPS	145 PA, .884 OPS	135 PA, .585 OPS	-.335
5	Jim Thome	124 PA, 1.104 OPS	118 PA, 1.041 OPS	126 PA, .821 OPS	-.283
6	Yunel Escobar	77 PA, 1.004 OPS	73 PA, 1.040 OPS	60 PA, .726 OPS	-.278
7	Matt Diaz	81 PA, 1.235 OPS	75 PA, .844 OPS	52 PA, .967 OPS	-.269
8	Alex Gonzalez	103 PA, .916 OPS	96 PA, .824 OPS	66 PA, .647 OPS	-.268
9	Bobby Crosby	92 PA, .773 OPS	89 PA, .674 OPS	65 PA, .505 OPS	-.268
10	Jason Kendall	131 PA, .625 OPS	124 PA, .848 OPS	77 PA, .360 OPS	-.264
11	Hideki Matsui	143 PA, .999 OPS	139 PA, .921 OPS	114 PA, .739 OPS	-.259
12	Adam Kennedy	75 PA, .702 OPS	73 PA, .809 OPS	57 PA, .443 OPS	-.259
13	Barry Bonds	116 PA, 1.219 OPS	114 PA, 1.084 OPS	116 PA, .963 OPS	-.256
14	Luis Gonzalez	131 PA, .939 OPS	126 PA, .831 OPS	103 PA, .684 OPS	-.255
15	Kevin Millar	135 PA, .960 OPS	132 PA, .773 OPS	121 PA, .706 OPS	-.254
16	Chad Tracy	63 PA, .928 OPS	59 PA, 1.084 OPS	55 PA, .681 OPS	-.247
17	Frank Catalanotto	92 PA, 1.095 OPS	87 PA, .495 OPS	89 PA, .849 OPS	-.246
18	Rob Mackowiak	82 PA, .823 OPS	73 PA, .726 OPS	51 PA, .592 OPS	-.231
19	Mike Redmond	72 PA, .740 OPS	71 PA, .715 OPS	53 PA, .512 OPS	-.228
20	Jack Cust	115 PA, .977 OPS	108 PA, 1.039 OPS	98 PA, .757 OPS	-.220
21	Nick Markakis	158 PA, .983 OPS	157 PA, .833 OPS	175 PA, .773 OPS	-.210
22	Gary Sheffield	131 PA, .985 OPS	128 PA, .967 OPS	137 PA, .777 OPS	-.207
23	Bengie Molina	126 PA, .913 OPS	124 PA, .647 OPS	98 PA, .706 OPS	-.207

These twenty-three players were the only ones to see a 200 (or more) point decrease in their OPS over the course of a game. Guys like Molina and Catalanotto actually did the worst in their second times to the plate while Chad Tracy, Adam Kennedy, and Jason Kendall improved before crashing downward.

Kendall is a good case study again of the effects of BABIP. He can't hit in the first place, and this is borne out by his .625 OPS with a .252 BABIP in the first column. That .252 is kind of low (again, the MLB average was .305), but .625 is also a little below what you would've expected him to hit anyway. Then in the second time against the same pitcher, his BABIP jumps to .353 and his OPS hops up to .848 - more balls were falling in and, when they did, they went for extra bases. Finally, in the last column, his BABIP fell to an awful .164 and his OPS crashed to an anemic .360. When you look at his career splits (scroll down about 2/3 of the page), you can see that he's usually a normal player, improving slightly against pitchers as the game wears on. This season, however, BABIP wreaked havoc on his numbers.

Only two members of the list saw their BABIP actually increase while their OPS went down. Rob Mackowiak's went from .269 to .360 to .308 and his OPS fell at every step. Gary Sheffield had a barely noticeable .259 to .277 to .260, and his OPS also fell at every step. Kind of strange, but both players' slugging percentages also went down through the game so perhaps they hits they were getting didn't go for extra bases.

Finally, a few players from this list have seen dips in their OPS across their careers. I'm going to express their numbers in the form OPS/BABIP for the 1st, 2nd, and 3rd+ time facing an opposing starter.

• Morgan Ensberg: .924/.307 to .779/.287 to .893/272
• Adam LaRoche: .819/.315 to .884/.321 to .810/.307
• Yunel Escobar, though 2007 was his first season.
• Hideki Matsui: .884/.302 to .836/.304 to .850/.305
• Adam Kennedy: .776/.329 to .760/.326 to .677/.288
• Rob Mackowiak: .768/.332 to .669/.286 to .717/.310
• Mike Redmond: .755/.318 to .732/.321 to .747/.329
• Most of Jack Cust's numbers are fueled by 2007.
• Nick Markakis: .841/.330 to .888/.347 to .806/.295
• Gary Sheffield: .945/.290 to .953/.288 to .904/.282

Now, most of these changes are almost unnoticeable. Frankly, is it going to bother you that Hideki Matsui dips to a still-good .850 at the end of games? Ditto Adam LaRoche, Ensberg, Markakis, Sheffield, etc. Adam Kennedy and Rob Mackowiak are kind of weird, but perhaps not incredibly so since they're not power threats and their BABIP fluctuates as well.

Of course, in the end, you just look at the fact there's not many plate appearances to work with for a lot of guys and decide this all doesn't mean anything anyway. :)