"I don't do that MLB Network on-base percentage (stuff). That's the new thing now. I feel like all of these stats and all of these geeks upstairs, they're messing up baseball, they're just changing the game. It's all about on-base percentage. If you don't get on base, then you suck. That's basically what they're saying. People don't care about RBI or scoring runs, it's all about getting on base."
Coming from a guy like Phillips this isn't very surprising, but just being around a guy like Joey Votto, you'd think he'd be a little more educated. Now I don't expect players to be into advanced statistics, but they at least understand the value of getting on base.
Well today Jon Morosi over at Fox Sports tweeted this:
Interesting on Brandon Phillips/OBP discussion: Royals and Giants finished 16th and 18th in majors, respectively, in team OBP. They did OK.
— Jon Morosi (@jonmorosi) March 25, 2015
Jon's tweet got me thinking. I would assume there is some sort of connection between on base percentage and winning percentage, but just how strong is that correlation? So I decided to crunch the numbers. I took the winning percentage of all 30 teams over the past five years (2010-2014). This gave me a decent sample of 150. I did a simple correlation with two different statistics, OBP and wOBA (Weighted on base, which you can read about HERE. Here were the results, in both table form and as a scatter plot
Winning % | OBP | wOBA | |
Winning % | 1.000 | ||
OBP | .535 | 1.000 | |
wOBA | .547 | .908 | 1.000 |
Winning Percentage vs. OBP
Winning Percentage vs. wOBA
As you can see from the scatter plots, there is a pretty strong correlation between winning percentage and both OBP and wOBA, with wOBA being the stronger correlation.
The r value, which describes how strong the correlation is for OBP is .535 while the r value for wOBA is .547.
In general, here is a guide that describes r value and how strong a correlation is (From http://faculty.quinnipiac.edu/libarts/polsci/Statistics.html).
If r = +.70 or higher Very strong positive relationship
+.40 to +.69 Strong positive relationship
+.30 to +.39 Moderate positive relationship
+.20 to +.29 weak positive relationship
+.01 to +.19 No or negligible relationship
-.01 to -.19 No or negligible relationship
-.20 to -.29 weak negative relationship
-.30 to -.39 Moderate negative relationship
-.40 to -.69 Strong negative relationship
-.70 or higher Very strong negative relationship
This shows that the correlation is indeed a strong one, like I had originally suspected. Take notes Brandon Phillips, on base percentage is important.
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