Author Archive

Quick And Dirty Aging Curves With Exit Velocity.

Two weeks ago I wrote about what I call “Peak Angles” for batters. That is the angle at which they produce the highest ratio of high exit velocity to low exit velocity batted balls. The working theory is that this angle roughly correlates to swing plane, and when you know swing plane you might be able to work out valuable information. For example, you might be able to gain insight on batter versus pitcher match-ups by comparing the average pitch plane to the average bat plane. There are other factors involved, obviously, like contact skill and plate discipline, but swing plane could prove to be valuable in the long haul.

Over the past two weeks this line of thinking brought me to two different lines of inquiry. First, can you use the “Peak Angles Exit Velocity” to predict the maximum effective angle for a batter? Second, how do the most valuable launch angles and exit velocities age over time? Read the rest of this entry »

Batter Peak Launch Angles

Swing plane has always been an important metric for evaluating batters, but there has never been an objective measure of swing plane in the public. Privately, through wearable technologies or video analysis one could obtain information regarding swing path, which has since gone on to become a valuable tool for coaching and training. Even still, we lacked data from actual games.

Over the past two years many writers and researchers have turned to using Exit Velocity vs Vertical Angle charts to analyze batter performance. Ranging from Rob Arthur to David Kagan to Alan Nathan. It is a great way to visualize the data. I have wondered in the past whether you could use these information to estimate the average plane of the bat on impact. If you were to plot a second order polynomial regression on top of such a chart and take the derivative of the function you could find the peak launch angle, that is the angle with the highest average exit velocity. Perhaps. I’m not entirely sure this is the case, but it is a good place to start. Read the rest of this entry »

Miguel Cabrera vs Comerica Park

Over the year or two many people have noted that the Statcast numbers in Comerica Park seem inflated compared to the real world results for the batted balls. From cursory research it appeared that this trend may be focused in right field, but perhaps not. Either way, you see Miguel Cabrera topping the xwOBA leaderboards on Baseball Savant, and xOBA leaderboards on xStats while his true results are lagging behind.

In one hand, that may appear to be a positive sign for a possible recovery, given his down season in 2017. In the other hand, it shouldn’t sit that well. His xwOBA is about 60 points higher than his real wOBA. The xStats fair a little better, and the difference is closer to 40 points. Either way, that is an absolutely enormous discrepancy.

There have been some hints that this effect may be focused in right field, which I noticed with Nick Castellanos. When I tell you something weird is going on in right field of Comerica Park, you might instinctively shed blame on that ludicrously deep right center field fence. I certainly did. That fence is about 430 feet deep and 11 feet high. It is one of the deepest areas in any MLB ballpark, rivaling AT&T Park.

But, I no longer believe that is the explanation. More on that in a moment, first I want to explain my methods. Read the rest of this entry »

The Minor League Ball is Such a Drag

Several years ago Alan Nathan, Jeff Kensrud, Lloyd Smith, and Eric Lang brought an air cannon and a few boxes of brand new baseballs to Minute Maid Park. If you’re anything like me, you like where this is going. They set up their cannon to fire balls roughly 96mph on a 28° angle and used Trackman to measure their distance and spin rate. They tested four groups of balls, two groups composed of MLB balls, one MiLB, and one NCAA. One group of MLB balls, group A, were tested using reasonably low spin rates, about 1800. The other, group B, had variable spin rates, ranging from 2100 to 3300. The results of their study were published in an article titled  How Far Did That Fly Ball Travel (Redux)? on Baseball Prospectus, although it can also be found here. I encourage you to read the piece, but today I want to focus on the MLB-A and MiLB groups.

Measured Ball Distance and Spin
Ball Lot Distance (S. D.) Spin (S. D.)
MLB-A 390 (8) 1806 (58)
MiLB 362 (8) 1583 (49)

The major league ball traveled 28 feet further than the minor league ball. Albeit with a higher spin rate. Presumably, the higher spin rate should translate to increased distance, but it is difficult to imagine that a difference of 200 rpm could bridge a gap of 28 feet. More on this in a moment. Read the rest of this entry »

Step Aside, Statistics. It Is Physics Time.

Since the beginning of December I have been working on an updated method to estimate home run probability. This method will be built around a physics model, compared to real life ballpark dimensions, and then evaluated using known sources of error. Especially for the coefficients of drag and lift.

As a first step, I reverse engineered Alan Nathan’s trajectory calculator. I then built my own version of the calculator, excluding wind, but including a few other features that his lacks. You can read about that here and look at my calculator here.

Once I felt I had fully grasped the necessary physics, I set forth and rewrote the calculator as a stored procedure in my database, and I ran it on all of the batted ball data I currently have. I have exported this data and used it to create the viz you see towards the bottom of this article. But first, there are a few things I need to address. Read the rest of this entry »

Ozuna Has Room For Growth

Marcell Ozuna had a breakout year in 2017. If you haven’t been following him much over the past few years, Ozuna had a terrific year in 2014 which set high expectations for him going into 2015. Unfortunately, he had a terrible 2015 season and was eventually demoted to AAA. Some say it may have been related to his maturity or attitude. Michael Hill, Marlins President of Baseball Operations, had this to say about the incident:

“I’ve seen him since he was 16, and it was the first time I had ever seen him hang his head. We spoke after the game, and I was like, ‘Ozo, what’s up?’ He said, ‘I don’t know.’ He had no answers. He was completely lost. That was when we decided it was in his best interests to send him down. It’s hard when you don’t see Marcell Ozuna with a big smile; that’s who he is.”

Source: Miami CBS Local

Ozuna described being sent to the minors as a “jail sentence.” To his credit, he appears to have used the experience to propel his career forward. In 2016 he had a bounce back year. He matched his then career high 23 homers, posted a solid 106 wRC+, improved peripheral stats (more walks, fewer strikeouts), and played pretty decent defense on top of it.

He took another step forward in 2017, hitting 37 home runs, with a 142 wRC+, even better peripherals, and great defensive numbers. This career year, combined with the extra year of control the Marlins “earned” in 2015 by keeping Ozuna in the minors (nothing to see here) made Ozuna a valuable trade chip. The Cardinals, aiming to consolidate their resources, were happy to trade Sandy Alcantara, Magneuris Sierra, Zac Gallen, and Daniel Castano for an upgrade. So let’s see what sort of player they acquired. Read the rest of this entry »

Let’s Have A Conversation About Spin Rate.

Spin rate is becoming ever more important to baseball analysis now that we have access to more reliable measurement devices. Namely, Trackman. But there are other technologies as well which are being used by high school, college, and minor league teams. Trackman is the big name, though, since it has been adopted by MLB, NPB and KBO along with many colleges and even a few high schools.

Trackman uses Doppler radar to measure the movement of the ball. I want to paint a picture in your mind of what this may look like, in the eyes of the radar. Remember, we’re trying to track the ball here. Read the rest of this entry »

Ground Balls Are Changing.

Major league batters are generally shifting towards a fly ball approach. The idea is to hit more balls in the air. Not necessarily fly balls, in fact there are those who wish to only hit line drives. When I say in the air, I mean ‘not on the ground.’ You want the ball to leave the infield before it bounces, ideally. Preferably this happens at a very high speed.

Duh, no kidding, right? Well, yeah. Obviously hitting the ball out of the infield is the goal for just about everyone. The goal isn’t the key, we’re talking about the approach used to actualize the goal. Read the rest of this entry »

Adjusting Hoskins’ Batted Balls

Every year we have a number of players who make their debut towards the end of the season, wildly exceed expectations, and leave us wondering what the future may hold. Last year we had Gary Sanchez. This year, Rhys Hoskins.

Hoskins hit the ground running. I mean, how many guys reach double digit homers before they reach double digit singles? I could probably look it up, I’m not going to. I don’t want to know. Hoskins did it, and that’s good enough for me.

Read the rest of this entry »

Year Three of xStats–A Review

I have spent the past few years creating a family of stats that I’ve called xStats. These stats use Statcast batted ball metrics to analyze each player, which I then manipulate and export in a manner I hope is useful for fans and analysts.

Exit Velocity and launch angle data are good, and I include those, but they aren’t yet intuitive for more baseball fans so I have set forth to display my data in terms of numbers that are more relatable. Namely the standard slash line numbers. I have expected batting average, on base percentage, slugging percentage, batting average on balls in play, and weighted on base average. For pitchers I have bbFIP, which is an ERA scalar. Today, though I’m only going to be looking at batters.

These stats are available, but they don’t help much unless you know how well they are working. To that end, I have created the following table, which compares the regular, standard slash line to the xStats slash line. Read the rest of this entry »