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Speed Scores and Reaching Base on Errors
|In a previous essay I examined the
effect of team speed on opposition errors.
This essay expands the analysis by looking at individual players
I examined the effect of speed on
reaching base on error by looking at all 219 batters who had at least 300
at bats in 1980 using the 1980 Retrosheet files.
As a proxy for player speed I used the Bill James Speed Score.
The table below summarizes the data by breaking it into quintiles.
I also looked at correlations based on the 219 individual player
RBoE.GB Opp.GB /Opp.GB
Speed Score Quintile
A very modest correlation of .14 exists between reaching base on
error per opportunity and a player's speed score.
Because nearly all times first base is reached on error comes on a
ground ball, much of this correlation can be explained by the relationship
between speed scores and the propensity to hit ground balls (correlation =
.30), i.e. faster players tend to be ground ball hitters.
When one looks at times reached base on error as a percentage of
non-basehit ground balls the correlation between speed and reaching base
on error evaporates to basically zero (correlation = .04).
As a further inquiry I examined
whether reaching base by error is related to whether a hitter bats
left-handed or right-handed.
RBoE.GB Opp.GB /Opp.GB
The side of the plate the at bat took place from.
Switch hitter at bats are therefore split. All other columns are
the same as above.
Summary: Here it seems fairly
conclusive that those hitting from the right side are much more likely to
reach base on error than those hitting from the left side.
I would suppose righties are more likely to reach base on error
because they are more likely to hit to the SS or 3B who typically make
more errors (mainly due to the longer throw) than first or second basemen.
A note on Speed Scores
Bill James developed Speed Scores as
a method for determining a player's practical game condition speed.
It is calculated by averaging the top five of six different
statistics. The scale for
players ranges from approximately one for the slowest players to ten for
the fastest. In my analysis,
for simplicity, I use only five of the statistics (the one not used is
by Dan Levitt
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