Does Base Stealing Create Havoc?

 

by Cyril Morong

 

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White Sox GM Ken Williams said this about Scott Podsednik: ďOne positive is his speed, his ability to create havoc on the bases"

 

Exactly how much havoc do base stealers in general, and Podsednik in particular create? Probably not much.

 

What did all that havoc on the bases that Podsenik created do for the Brewers? They were next to last in runs scored in the NL last year. The Brewers led the NL with 138 SBs. The Giants stole only 43 yet were second in runs scored. The Red Sox led the AL in runs while stealing 68 bases, 21 below the league average. This havoc theory is a bad theory.

 

What value does stealing have? The run value of a SB is .22, according to Pete Palmer, editor of the Baseball Encyclopedia. A caught stealing (CS) is a -.38. Last year Podsednik had 70 SB and 13 CS. Using the Palmer values, that is a run value of 10.46. This would add about 1 win over a season. But, Podsednik also only had a .313 on-base percentage OBP, 20 points below the NL average and 25 below the AL average. Since the NL does not have the DH, and we should probably compare Podsednik only to position players, letís use the 25 point differential (the NL average OBP among non-pitchers is probably around this anyway). Podsednik had 706 plate appearances last year, not counting sacrifices. That means he reached base 17.65 fewer times than the average hitter (706*.025 = 17.65). What run value does that have? In Pete Palmerís system, a batting out is usually around -.25 and a walk is around .33. So if you turn an out into a walk, that value is .58, losing the -.25 and gaining the .33. If Podsednik had turned those 17.65 outs into walks, the run value would be 10.24 (17.65*.58 = 10.24), very close to the value he created by his base stealing. In other words, a player with no SBs or CSs and a .338 OBP would help your offense just as much as Podsednik. The stealing may have created havoc, but not runs.

 

Stealing is not correlated much with scoring at the team level, either.The table below summarizes the correlation and r-squared that various stats had with team runs per game from 2001-03

 

Stat

Correlation

R-squared

AVG

0.858

0.736

SLG

0.917

0.842

OBP

0.891

0.794

OPS

0.950

0.903

SB/G

-0.032

0.001

Net SB/G

0.136

0.018

SB%

0.303

0.092

 

 

SLG is slugging percentage and OPS is OBP + SLG. A perfect correlation would be 1.00. Notice how close the hitting stats are to it and how far away the stealing stats are. SB/G is team stolen bases per game. Net SB/G is stolen bases per game minus caught stealing per game. So, if you want to score, get great hitters first. The R-squared number is the square of the correlation. It tells us how what percent of the variation in team runs per game is explained by the variable. (Note: things are little more complicated since a multiple regression needs to be done to see the value of stealing, holding other factors constant-this analysis, too, shows Podsednikís stealing to have little value-see below for details).

 

Do good base stealers distract the pitcher and help the hitter? Probably not much going on here, either.

 

Now it is possible that other factors affect a teamís OPS. Take base stealing for example. If a man is on, this distracts the pitcher. Maybe he throws more fastballs and the batter can be ready for this. Or a hole opens up that makes it easier to get a hit. So some of the 87% I attributed to OPS might, in fact, actually come from another source. So I looked at how both good and bad stealing teams hit with a runner on first base only.

 

I looked at the top 10 teams in SBs from 1982-92 and the bottom ten. Then I determined how much their AVG, SLG, OBP and OPS differed between having a runner on 1st or no runners on at all. I determined the runner on first data by finding the difference between the runners on base and the runners in scoring position data (from Retrosheet).

 

The top ten teams in SBs had the following increases when there was a runner on first compared to no runners on (the average across the teams)

 

AVG-.025

SLG-.030

OBP-.008

OPS-.038

 

That is, with a runner on first, these teams had a .025 higher batting average than they did when there were no runners on base. Slugging went up .030, OBP .008 and OPS .038.

 

The bottom ten teams in SBs had the following increases

 

AVG-.019

SLG-.028

OBP-.011

OPS-.039

 

The top ten teams averaged about 240 SBs and the bottom around 40. The one difference that is big is the AVG difference (.025-.019=.006).But in general, the best stealing teams had little additional benefit over what the worst stealing teams.

 

The best stealing teams had in the 900 range of ABs with a runner on first. The bottom in the 1100 range. This makes sense because the best steal and they wonít be on first as often. Also, who is most likely to be left on first base on those teams? The few guys who donít steal, like Jack Clark (5 of the teams were Cards). But those bottom teams must have rarely had a good base stealer on, a lot less often than the best. I think if the runners bother the pitcher, we should see a bigger effect here. After all, we are comparing the best stealing teams to the worst.

 

The change in OPS for both teams is just about the same. I am still skeptical that having a good stealer on first helps a lot. Maybe the change in AVG is simply a result of the hole opened up at first. There is little change in SLG. Maybe the fast guy bothering the pitcher and making it easier for the hitter is not happening.

 

 

Using a multiple regression

 

In a regression with team runs per game as the dependent variable, the equation was

 

R/G = -5.12 + 15.46*OBP + 11.25*SLG + .353*SB - .922*SB

 

the R-squared was .919. This covered all teams from 2001-03.

 

So a SB adds .353 runs per game while a CS costs .922. For Podsednik, he gets 12.72 runs since 70*.353 Ė 13*.922 = 12.72. But how many runs does he cost with his low OBP and SLG? Since he would only be about one 9th of the team, his being .025 below the league average in OBP should count for .003 and his being about .060 below the league average in SLG will count for .007. Since 15.46*.003*162 = 7.51, he cost his team that many runs with his low OBP. Since 11.25*.007*162 = 12.75, that his how much he cost his team with his low SLG (it was only .364 last year about .060 below the league average, more if you donít count pitchers). So combined, he cost the team about 20.27 runs with his low SLG and OBP, more than he gained with his stealing.

 

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