I have been working on a 3D batted ball classification system. That is, classifying batted balls based upon their exit velocity, vertical angle, and horizontal angle. I have identified a few patterns, and I am pretty excited with the advances I have made over the past week. However, I realized this project could take many weeks or months to complete and I wanted to push an update sooner than that. So, I have put the 2D solution onto xStats and pushed the update to the stats spreadsheet. This 2D solution is not groundbreaking work in terms of Statcast research, but it is a significant improvement over the classification system that was previously published on xStats.
Read moreIntroducing xStats version 2.9
xStats version 2.9 launched on opening day. Here are a look at some of its features.
Read moreThe New Player Search Tool.
Keeping data on multiple spreadsheets isn't ideal, and while moving it all onto a webpage would be ideal it unfortunately isn't something that can happen right now. In the mean time, I want to make these spreadsheets a little easier to use. This new Player Search tool is a good first step. Let me show you its features.
Read moreLeaderboards For The Six Batted Ball Types
You may be curious about the real world stats for individual batters in each of these batted ball categories (DB, GB, LD, HD, FB, and PU). Included are 12 charts, two for each batted ball type, which display the top 30 batters ranked by total Balls In Play and wOBA.
Read moreA New Stat! bbFIP
A few weeks ago I began dabbling with a stat that combined extremely well hit balls and walks plus extremely poorly hit balls and strike outs. In other words, automatic successful at bats versus automatic failed at bats. The aim here is to blend the line between Defense Independent Pitching, which largely ignores BABIP, and the newer, more nuanced approach towards judging batted ball quality.
Read morexStats and Fantasy Uses for Statcast
This is the most up to date article about xStats. It describes the current methodology and the descriptive and predictive qualities of the stats. It also delves into a quick and dirty method for adjusting the stats using a histogram of their exit velocities.
This article was featured on the Hardball Times on March 9th, 2017, and it is even John Sickels Approved. I consider it a must read for anyone even tangentially interested in xStats or Statcast in general.
Introducing xFantasy Parts I, II, III, and IV.
xFantasy is a system based on xStats that integrates hitters' xAVG, xOBP, and xISO in order to predict expected fantasy production (HR, R, RBI, SB, AVG). The underlying models are put together into an embedded "Triple Slash Converter" in Part 2. Part 3 compares the predictive value of xFantasy (and therefore xStats) vs. Steamer and historic stats, ultimately finding that for players under 26, xStats are indeed more predictive than Steamer.
First Published 12/22/16 Written by Ryan Brock
First Published 12/23/16 Written by Ryan Brock
First Published 1/21/17 Written by Ryan Brock
First Published 2/24/17 Written by Ryan Brock
The Updated xStats And Their Year To Year Correlations
Blending Extremely Poorly Hit Balls And FIP.
Evaluating Hard and Soft Hit Balls Using Statcast
Read this article to learn more about the PH% (Poorly Hit) and VH% (Value Hit) stats. You may see those stats in the main stat spreadsheet and not quite understand what they are or what they mean, this article should help clear up any questions you may have. You may also be interested in reading about the updates to the system.
Statcast FIP: Estimating Home Runs
Fitting Running Speed into xOBA and xBABIP.
A general introduction to the methods I use to incorporate running speed. The system remains almost entirely intact, but I have since added a few small corrections here and there to fix small problems. I'm not happy with this system, and I would love to get rid of it, but I haven't found a better solution. Which is a low bar, since I don't feel this solution is very good.
A New BABIP for a Statcast Era
A follow up companion piece for xOBA and Using Statcast Data To Measure Offense.
xOBA and Using Statcast Data To Measure Offense
The first public introduction to xStats. Some of the methods described here are obsolete, but the core concepts remain intact. Keep in mind that the window and bucket system has been updated to more resemble a kernel based approach; park factors and handedness factors were added; and exit velocities are modified and corrected for measurement error.