Base Running: Taking the Extra Base

I have spent a lot of time this winter talking about hitting, pitching and fielding. Another element of the game which has traditionally not been measured well is base running. For the most part, the only statistics which have been used to measure base running are stolen bases and times caught stealing. This, of course, is only a small part of base running. With the recent development of play by play databases, it is now possible to measure base running far beyond stolen bases. For example, we can now count how many times a player goes from first to third on a single or from second to third on a fly out.

Bill James wrote an article in the Bill James Handbook 2007 detailing some of the work that Baseball Info Solutions (BIS) has done in base running measurement. Dan Fox at Baseball Prospectus has also been analyzing base running over the past couple of years. In one recent article, he critiques the BIS method and includes links to his methods. While, the BIS method and write-up are more fan friendly, the Fox analysis is more mathematically correct. I think both are useful and they seem to produce reasonably simlar results.

I have been mucking around in the retrosheet database the past week or so trying to do my own base running analysis. My method is really a hybrid between the BIS and Fox methods. I will present my analysis step by step over the next couple of weeks and eventually arrive at a system for rating base runners for players and for teams. Naturally, I'll focus on the Tigers.

The first thing I'll look at is taking extra bases on hits. There are three situations of interest:

1. going from 1st to 3rd on a single
2. going from 1st to home on a double
3. going from 2nd to home on a single
   

The probability of success of course changes according to how many outs there are and where the ball is hit. Fox takes that into consideration in his analysis. BIS does not and I'm not going to do it either (at least not this year). I'd rather keep it simple for now. Over the course of the season, I think the opportunities even out so that it should not matter too much for my purpose which is to distinguish good runners from mediocre runners from bad ones.

Looking at the bottom row of the table below, we can see that the average Major League team had 250 opportunities to go from 1st to 3rd on a single and made the advancement 27% of the time. They had 72 opportunuties to go from 1st to home on a double and were successful 40% of the time. In 216 chances to move from 2nd to home on a single, they made it 60% of the time. Overall, the average team had 538 opportunities to take an extra base on a hit and they made the advancement 42% of the time.

The Tigers were better than average in each of the above mentioned categories - 31% successful in going from 1st to 3rd on a single, 51% succesful advancing from 1st to home on a double and 65% successful moving from 2nd to home on a single. Overall, they took the extra base 47% of the time.

Individually, the most successful Tigers in taking the extra base on hits were Brandon Inge (59%), Ivan Rodriguez (57%) and Carlos Guillen (53%). Omar Infante was also 53% but with only 19 opportunities. The least successful Tigers in this category were Marcus Thames (23%) and Placido Polanco (37%).

Advancement on ground outs, fly outs, and balls not hit follows. At the end, I'll combine all the base running plays and calculate a single base running performance measure.

The information used here was obtained free of charge from and is copyrighted by
Retrosheet.  Interested parties may contact Retrosheet at "www.retrosheet.org".

Table: Taking the Extra Base on Hits - Tigers versus the average team

Player	Opp 1-3	Adv	%	Opp 1-4	Adv	%	Opp 2-4	Adv	%	Opp	Adv	%
Inge	15	5	33%	8	6	75%	18	13	72%	41	24	59%
Rodriguez	18	5	28%	7	6	86%	22	16	73%	47	27	57%
Guillen	27	13	48%	6	2	33%	16	11	69%	49	26	53%
Infante	9	3	33%	2	2	100%	8	5	63%	19	10	53%
Monroe	23	6	26%	3	2	67%	18	14	78%	44	22	50%
Ordonez	21	6	29%	6	2	33%	21	14	67%	48	22	46%
Granderson	26	5	19%	13	7	54%	24	15	63%	63	27	43%
Shelton	17	7	41%	4	1	25%	8	4	50%	29	12	41%
Polanco	33	9	27%	5	2	40%	14	8	57%	52	19	37%
Thames	17	1	6%	3	1	33%	10	5	50%	30	7	23%
Team Totals	228	70	31%	61	31	51%	179	117	65%	468	218	47%
MLB Averages	250	69	27%	72	28	40%	216	129	60%	538	226	42%