Left On Base, the Hidden Enemy

Recently, Derek Jacques at Baseball Prospectus wrote a great article called Stranded! It’s focus was trying to determine if the Batters Left on Base (BLOB) statistic for a team was a measure of offensive success or failure. It was a fascinating article. It confirmed some common sense and completely missed the crux of the matter. I sent him a quick note and I will share and elaborate here.

The Obvious

Let’s cover the obvious. The more people that you put on base, Total on Base (TOB), the more people will score. It is a simple concept that powers Batting Average (AVG) and On Base Percentage (OBP). Derek ran some numbers for about 918 teams over the course of 25+ seasons and sure enough, there was a strong correlation.

Next bit of logic, the more people that you put on base, the more people that you leave there. Very simple. If you, on average, got 40% of your base runners home, then you would have a higher BLOB with 2000 base runners than with 1900 base runners. The numbers confirm the correlation, not as strong as with runs, but strong.

Finally, he compared the number of Runs with BLOB. This also had a strong correlation, but it was the weakest of the three. This may seem to indicate that a high BLOB is good. Well, over the course of a season it isn’t bad as it indicates more men on base which leads to more Runs.

Derek then concludes that saying a high BLOB, while frustrating, may be a good thing. This is where I pick it up.

Base Running Efficiency

I decided to check the ratio of Runs to BLOB in 2007. Derek used numbers from 2007 for his quick illustration, and I’m going to use the same numbers, mostly because I have them readily accessible from Derek’s article.

The more Runs a team scored, the higher the ratio. What is very interesting was that the ratio for the majors last year was .666. That means for every two LOB, a team scored a Run. Those that fell below that ratio, faired poorly. The top 15 teams all had ratios higher than .666. Of the bottom 15, only the Blue Jays ranked at 17, had a score above the mark. They came in at .677, but were in the bottom 25% in TOB. Back to obvious statement number 2, more on base, more runs. Let’s call this the Left on Base Ratio (LOBR)

To look at it another way, the lower scoring teams got 33-35% of their base runners around to score. The higher scoring teams, around 40%. The number 15 team, the Tampa Bay Rays, got 37.3% of their runners across. Their ratio of Runs to Everyone that scored more than them (756 Runs) had a better ratio of getting those runners home. Only 1 of the remaining 15 teams below them had a better rate. Let’s call this Base Runner Efficiency (BRE).

Here is a quick chart with all the numbers for 2007. Totals for the majors are at the bottom.

Team	Runs	TOB	BLOB	BRE	LOBR
NYA	968	2371	1249	40.8%	0.775
PHI	892	2289	1295	39.0%	0.689
DET	887	2182	1148	40.7%	0.773
BOS	867	2314	1291	37.5%	0.672
COL	860	2271	1250	37.9%	0.688
ANA	822	2125	1100	38.7%	0.747
TEX	816	2019	1092	40.4%	0.747
CLE	811	2174	1216	37.3%	0.667
ATL	810	2145	1205	37.8%	0.672
NYN	804	2146	1196	37.5%	0.672
MIL	801	2032	1117	39.4%	0.717
SEA	794	2080	1127	38.2%	0.705
FLO	790	2107	1192	37.5%	0.663
CIN	783	2098	1170	37.3%	0.669
TBA	782	2098	1166	37.3%	0.671
BAL	756	2076	1152	36.4%	0.656
TOR	753	2014	1112	37.4%	0.677
CHN	752	2070	1190	36.3%	0.632
OAK	741	2143	1258	34.6%	0.589
SDN	741	2014	1153	36.8%	0.643
LAN	735	2096	1200	35.1%	0.613
SLN	725	2073	1168	35.0%	0.621
PIT	724	1997	1119	36.3%	0.647
HOU	723	2058	1181	35.1%	0.612
MIN	718	2020	1120	35.5%	0.641
ARI	712	1939	1090	36.7%	0.653
KCA	706	1964	1089	35.9%	0.648
CHA	693	1925	1074	36.0%	0.645
SFN	683	1978	1141	34.5%	0.599
WAS	673	1992	1163	33.8%	0.579
	23322	62810	35024	37.1%	0.666

One thing that you realize, and can enter the obvious discussion, the more people a team can get on base, the better they are at getting them home. The very act of getting on base can push existing runners closer to home, or the rest of the way there.

What can we do with this in evaluating our daily frustration? Let’s look at a recent slate of games apply the norms for the majors to the games.

Any Given Day

Here a a chart showing the Teams, Runs, BLOB, LOBR, and Result for Sunday, May 18 2008 I’ve paired the teams from each game together, Winner and then Loser.

Team	Runs	BLOB	LOBR	Result
Cubs	4	6	0.667	W
Pirates	3	5	0.600	L
Royals	9	7	1.286	W
Marlins	3	5	0.600	L
Reds	6	7	0.857	W
Indians	5	9	0.556	L
Red Sox	11	9	1.222	W
Brewers	7	2	3.500	L
Braves	5	6	0.833	W
Athletics	2	11	0.182	L
Blue Jays	6	4	1.500	W
Phillies	5	11	0.455	L
Cardinals	5	16	0.313	W
Rays	4	5	0.800	L
Astros	5	9	0.556	W
Rangers	4	3	1.333	L
Rockies	6	9	0.667	W
Twins	2	5	0.400	L
Nationals	2	8	0.250	W
Orioles	1	5	0.200	L
Angels	10	5	2.000	W
Dodgers	2	6	0.333	L
White Sox	13	5	2.600	W
Giants	8	8	1.000	L
Mariners	3	5	0.600	W
Padres	2	5	0.400	L
Diamondbacks	4	8	0.500	W
Tigers	0	7	0.000	L
Mets	11	3	3.667	W
Yankees	2	5	0.400	L

Go National League! 8-6 on Sunday. What we are looking at though is the LOBR. Here is the average for the Winners and Losers:

• Winner LOBR: 0.935
• Loser LOBR: 0.543

The Winning teams did leave an average of one extra runner on base. However, they scored twice as many runs, winning by an average score of 7 to 3. It was a good day for all the teams as the overall ratio for the day was 0.754.

A quick note of exceptional games:

• Boston over Milwaukee (11-7 Runs, 9-2 BLOB). The Brewers were very efficient in getting their people home. However, the Red Sox got them by volume and were still over the 0.666 average at 1.222.
• St. Louis over Tampa Bay (5-4, 16-5) Another case of sheer volume. Tampa did a great job, they just needed more.
• Houston over Texas (5-4, 9-3) Just like the St. Louis game, just smaller LOBR numbers. Two one-run games. Reinforces the importance of getting on people to start the process.

The other 12 games went to the winner in LOBR. If I had a full database, I’d pull more games in and see how it all maps out. In any case, this can serve as a starting point in understanding the role of BLOB in greater detail.