[in R]

> MLB_08 MLB_09 MLB MLB
[,1] [,2]
MLB_08 20 20
MLB_09 79 140
> fisher.test(MLB)

Fisher’s Exact Test for Count Data

data: MLB
p-value = 0.1120
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
0.8464159 3.6972463
sample estimates:
odds ratio
1.768135

Our p-value from this Fisher’s exact test comparing GBs to non-GBs is almost less than .1 (which isn’t the generally used scientific p-value, that’s usually .05, but many companies/government institutions use .1 including the US Census Bureau). We don’t quite have a statistically significant difference, but it’s so close we have to consider this a meaningful relationship in this real world of incomplete information we live in.

Similarly, the AAA relationship is almost statistically significant.

> AAA
[,1] [,2]
AAA_08 30 26
AAA_09 38 55
> fisher.test(AAA)

Fisher’s Exact Test for Count Data

data: AAA
p-value = 0.1742
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
0.8112947 3.4407261
sample estimates:
odds ratio
1.664258

Here it is .1742, which is also not quite significant but still suggests that there is something there.

So to reiterate, no there isn’t a simple explanation, and if there was it certainly is not MLE.

Exactly. So I say ‘rise’ for pitches with positive vertical movement, because they do not actually rise as the move to the plate. But they drop less than you would expect due to gravity.

Agreed on the ‘rise’ of the fastball and it’s correlation to GB%. Your article on Affeldt displayed that beautifully if I recall correctly.

One question, ‘rise’ (or really just vertical movement generally) in PitchFX is considered to be the vertical distance (in inches) that a pitch deviates from the expected trajectory at a given velocity with gravity included, correct.

So a FB with positive vertical movement, i.e. ‘rise’ (which I believe you refer to by placing it in quotes) before it crosses a certain threshold actually means the ball goes more “straight”, right?

Good point about the small sample size. You are right there is very little we can infer from those 14 innings. But generally the expected groundball rate off a fastball varies inversely with the ‘rise’ of the fastball. I will dig up the reference for that, and if I cannot find one I have done the work and will post it here or at Baseball Analysts.

This is an interesting question, and Mr. Cameron does not assert that the theory his 1.6 increased “rise” on the fastball is necessarily correct, but analysis on pitch type (which divides the small sample further by categorizing int by pitches) from a sample of 14.0 IP is meaningless.