Mixing Fantasy & Reality: Pitch Velocity Changes & Notes by Jeff Zimmerman August 19, 2016 Pitch Velocity Effects on Groundballs, Exit Velocity, and Swinging Strikes Last week, I examined Danny Duffy and several other writers have examined at him also. If you want to read up on various theories on my he is performing great and why that may change, go ahead. Instead, today I am going to concentrate on his fastball velocity changes and how the results change as the velocity changes. Danny Duffy is starting to get some Cy Young consideration after spending part of the season in the bullpen. One cause for the turnaround is his fastball velocity increasing from 93.8 mph to 95 mph. The average velocity was even higher earlier in the season but it has been steadily dropping. So what difference does it make if he is throwing 96 mph or 94 mph? Today, I am going to lay the groundwork for finding such an answer. Simply, I looked at three different factors, exit (or batted ball) velocity (EV), groundball rate (GB%), and swinging-strike rate (SwStr%) and how each compared to a 1 mph velocity block. To help smooth out the results, I looked velocities between whole values like 90 mph to 91 mph and labeled them 90.5 mph. Also, I looked at values between 90.5 mph and 91.5 mph and put them in the 90 mph bin. I know there is overlap, but I hoped the higher number of samples would help smooth at the final results, especially with a limited number of samples at both ends of the data range. To start off, here are Duffy’s average exit velocities for a given range of fastball velocities. Duffy sees his average exit velocity dropped steadily as his velocity increases. So the harder he throws, batters will weakly hit his fastballs. Here is his velocity compared to his groundball rate. Just so everyone knows, Duffy is one of the most extreme flyball pitchers in the league. He should be attempting to keep his pitches at this high flyball rate to help limit his BABIP. I am not 100% sure how to read this information, but it looks like Duffy wants to increase the number of easy pop-outs, he can lower his velocity. It is a tough trade off. Now, moving onto his swinging-strike rate versus his velocity. The slope of the graph is pretty steep with almost a tripling of his SwStr% from 93 mph to 96 mph. Duffy’s fastball definitely performs better at higher velocities. So how do this match up with results? Danny Duffy as a Starter Dates Fastball Velo SwStr% FB% Exit Velocity 5/15/16 to 7/7/16 95.4 12.9% 46.5% 89.4 7/16/16 to 8/16/16 94.0 12.6% 48.5% 90.2 The results are all heading in the expected direction, but I thought there would be a little bit bigger change in his SwStr%. Duffy’s swinging strike rate will likely to continue to drop has his fastball velocity drops. Additionally, he is going to allow more and more hard hit flyballs (i.e. home runs) but will likely see a lower BABIP. I am just beginning to analyze data with this method, so I have no idea on league-wide averages, stabilization rates, or year-to-year correlation. What I do know, is that I look the results so far and plan on using it with future velocity changing pitchers like Dylan Bundy and Michael Pineda. Let me know if you have any questions and pitcher samples you would like to see. Notes (These got a little out of hand in length. I will try to keep them shorter next time): On Wednesday, I warned people about using Tyler Skaggs in his start because he would need to work with a new stretch move. The Angels talked about it some. It was a matter of importance to the organization. Manager Mike Scioscia promised it would be immediately addressed. Asked if it had been fixed Wednesday afternoon, before Skaggs’ follow-up start against Seattle, Scioscia described the solution as simple and himself as confident the 25-year-old would “do a better job of it.” “It’s just experience,” Scioscia said. “Sometimes a blessing comes out of when you have a day like he did in Cleveland.” Scioscia said he and his staff had recognized that Skaggs’ difficulties condensing his delivery could cause challenges. His two-year recovery from Tommy John surgery, he said, simply took precedence over more minor aspects. But now that the problem has presented itself, Scioscia said it should not again. “In fact,” he said Wednesday, “I know it won’t be an issue. It’ll be a quick fix.” The fix didn’t seem to happen last night with Skaggs giving up four runs in only 3.1 innings of work. I would still stay away from owning him for a bit longer. • There seems to be some disagreement on how to value Jon Gray with some pundits just looking to stay away like they previously did with all Colorado pitchers. This approach is not the preferred method in my opinion. The best way is to come up with educated projection, find similar players, and slot the player around these similarly valued players. For next season, I would think 190 innings of 9 K/9 and 3 BB/9 baseball is reasonable starting spot for Gray. I think he should be able to throw a full 200 IP workload, but his innings may get cut short because of some rough starts at home. Looking at his current WHIP of 1.25 and .299 BABIP, I could see his BABIP increase and WHIP go to 1.30. Finally, his ERA. All his current ERA estimators are in the high threes. 3.83 FIP, 3.70 xFIP, 3.79 SIERA, 3.73 kwERA, but his ERA his sits at 4.69. Colorado pitchers are usually going to have an inflated ERA because of the extra hits which fall in Coors, but probably not to the 4.69 level. I will go with a 4.25 ERA for now. Note: I have started collecting all my preseason projections in a spreadsheet for reference. I know there is only two players on it, but I hope to fill it up before next season. Some pitchers who are putting up similar numbers this season are Kevin Gausman, Gio Gonzalez, and Scott Kazmir. If these three pitchers are owned/valued in your league, so should be Gray. If they aren’t, maybe stay away from Gray. • Yasmany Tomas is slugging .289/.319/.867 this August. I went looking through his data and found his batted ball distance to be the same, but he is pulling the ball over short left field fences more and more. Month: Pull% Apr: 33% May: 44% June: 44% July: 48% August: 54% This increase in pull rate, and a small drop in his K%, makes him an interesting value pick for next season.