While we have established that velocity is very important to success several times on this blog, it seemed like it would be helpful to look at some probabilities of fastballs broken down by velocity. In other words, I wanted to see if we could look at individual fastballs, and just based on velocity (there are things like movement that we can look at in the future if need be) see how likely it is for the fastball to be a positive or negative result for the pitcher. This is what I will try to do in this post.
First, the effectiveness of four seam fastballs (MLBAM tags) are broken down by month, separated by fastballs throw in the zone and outside of the zone (based just on the traditional Pitch F/X strike zone). To measure effectiveness, rather than trying to measure by average or OPS, I broke it down by three numbers that were easy to calculate, and at the same time, in my opinion, very predictive, swinging strike percentage, contact percentage (contact % is just balls put in play, the "in play" tags on GameDay/Pitch F/X), and home run percentage. I broke it down by month because it gives us both a league average rate, along with a glimpse at the changes of fastball effectiveness as the season goes on.
After breaking it down by month, I broke it down the fastball effectiveness by MPH, starting with all pitches tagged as four seam fastballs below 85 MPH (it is admittedly a random starting point). I then went up 1 MPH each until I reached 100 MPH (100 MPH + pitches were all lumped together because there aren't a lot over 100, so it makes sense to lump them all together).
Obviously, when evaluating individual pitchers' fastballs, things like deception, sequencing and the quality of the other pitches' affect on the fastball have to be taken into consideration (not to mention that I only looked at pitches inside the strike zone and outside the strike zone, not where the pitch was in the strike zone. All strikes are not created equally). However, this does give us a general idea of how well an average 97 MPH fastball has been hit in the strike zone this year, or a 86 MPH fastball thrown outside of the strike zone. Velocity does matter, and I think this can help project pitchers that we have velocity data for, but not a large enough sample size to see how his fastball will actually play. It is also a starting point to see which pitchers are over achieving or under achieving when it comes to their fastball's velocity and their fastball's success.
An example of how this might work as a projection, we can look at the Sunday starts of two well known NPB pitchers and use the Yahoo data to project how the fastballs they showed would work in the Majors, assuming average deception, etc. Based on the velocities of his fastballs and the amount of fastballs thrown in and out of the zone, Shohei Otani's fastball would have a 6.84 whiff %, 19.28 contact %, and .78 HR %. Kenta Maeda's fastball, based on the data just from his last start, would have a 6.77 whiff %, 18.81 contact %, and .74 HR %, meaning that at least the way in which they pitched in their last start, Otani is a little more likely to get whiffs, but Maeda is a little less likely to give up contact or home runs, which I think makes some sense.