Ahead in the count

 Introduction This is the final update that I'll be making to my pitch quality model. The main update is the inclusion of spin/movement axis differences which was a clear weakness of my previous work. In addition, I've reworked the format of the underlying models. These approach changes have limited me to data from 2020 onwards, but greater accuracy has been achieved in almost every model prediction. This model update will only be used on my main website , other apps will continue to use the old version. Pitching grades from before 2020 will be grandfathered in using the old model. For more information on older versions of the model, see these blog posts: [1] , [2] Spin Axis and Efficiency On a pitch-by-pitch basis, the observed spin and movement axis from Statcast data can be compared to produce the axis difference metric, commonly attributed to Seam-Shifted Wake (SSW). Increased SSW is generally correlated with improved performance as seen in the graph below, which used the o

Introduction When a pitcher starts dealing or falling apart over the course of a couple of months, I often see release point changes suggested as a possible cause for the sudden change in fortunes. I’m interested to see if this holds up in aggregate. Do release point changes have any effect on pitcher performance? Do many pitchers undergo release point changes every month with no change in ability level? If any correlation is found, then this is informative, and suggests that release point changes could be incorporated into a general theory of pitching. However, if not, it implies that analysis of release points may be similar to reading tea leaves. Searching for patterns to explain randomness is human nature, and this could be an example of it. This isn’t to say that release point changes cannot be informative and causes for changes in ability level, but that there should be some additional justification for why a particular release point