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Geeking Out: Pitch To Contact And Team Pitching

Attached Image: BlackboardTeal.jpg Pitch To Contact - at this point, I think we can go with capital letters, don't you? That phrase and philosophy have drawn a fair amount of criticism, a chunk of which is just snark, but some of which at least tries to ground itself in statistical analysis. In a thread started yesterday on Twins Daily, there was a lot of debate on Pitch To Contact, what it means and what we really know about its effects.

When Bill James unveiled several new tools for analyzing baseball, the most fundamental ones usually started by analyzing team stats.[PRBREAK][/PRBREAK]
For instance, by studying teams' wins and losses, he found a correlation with runs scored and runs given up. And by studying team runs scored, he discovered a correlation between getting on base and total bases. From there, it's a short step to assuming that if you get a lot of players who get on base or hit for power, you'll score more runs.

But how about teams that don't give up many runs? If we take a look at teams for the last few years, can we see a trend in those that don't give up many runs? And does that trend match or contradict a "Pitch To Contact" philosophy.

So let's do a very quick-and-dirty back-of-the-napkin study. I looked at 150 teams, or all the teams from the last five years, ranked them by runs/game (R/G) and then searched the stats that most closely correlate with it. I did this using the "CORREL" function in Excel, which generates a coefficient between 0 and 1. 1 means a perfect correlation. 0 means it is entirely random. The full results are at the bottom, but here is a summary.

Those who are critical of the Pitch To Contact philosophy are usually reacting to the reduced emphasis it puts on striking people out. The K/9 correlation to runs per game is .54, one of the lower correlations on the list. That's lower than I would have expected. Clearly, having a staff that strikes out a ton of batters isn't especially important.

The defenders of the Pitch To Contact philosophy like to say that it's essentially saying "throw strikes." Presumably, that would imply not walking people, something that the Twins have certainly emphasized. However, the correlation of BB/9 to R/G is about the same: .56. Like strikeouts, not walking players is good, but not great.

Combing the two gets us a little closer. SO/BB has a .69 correlation. Close to that correlation is something else the Twins have been especially good at this year: not giving up home runs. HR/9 has a .65 correlation.

But the winner, without question, is hits. H/9 has a correlation of .88, crazy high compared to the other traditional stats in the list. That might seem obvious - if you don't give up hits, you shouldn't give up runs. So the question changes....how do you avoid giving up hits?

Well, it isn't just "strike people out". In fact, we proved just the opposite - that's fine, but a very small part of the story. So the difference is...defense? Luck? Secret sauce?

The truth is we don't know what it is. Sabrmetrics is still remarkably poor at predicting pitching. But we know what it isn't - it isn't as easy as gathering Ks. And whatever philosophy one adopts, its goal better be limiting hits.

~~~


Here is a link to the spreadsheet to check things or play with it yourself:

https://docs.google....dit?usp=sharing

~~~

And here are the final numbers....

Stat Correl
R/G 1.00
R 1.00
ERA 0.99
ER 0.99
WHIP 0.93
H/9 0.88
H 0.86
ERA+ -0.81
BF 0.80
SO/BB -0.69
L 0.66
W-L% -0.66
W -0.66
HR 0.66
HR/9 0.65
tmSHO -0.65
SO -0.57
BB/9 0.56
SO/9 -0.54
#Pitch 0.54
BB 0.53
SV -0.53
IP -0.51
cgSHO -0.36
GF 0.32
CG -0.32
HBP 0.27
WP 0.27
BK 0.20
PitchAge -0.13
IBB 0.01


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