Hitter Analytics Updates
Recently, I made an initial push to get a deeper look at hitters. I felt people have enough information on pitchers, especially with the Pitchf/x data available. I finally had some time to dig into the information a little more and have come up with a couple updates.
Nine batted ball categories is too many
Inside Edge makes avaialble nine non-bunt categories for batted balls. Here are the original nine with the xBABIP and wOBAcon:
Batted Ball Type: xBABIP, wOBAcon, % of batted balls
Groundball – Weak: .151, .112, 31.4%
Groundball – Medium: .461, .416, 9.5%
Groundball – Well-Hit: .647, .610, 3.8%
Line Drive – Weak: .622, .579, 2.3%
Line Drive – Medium: .650, .638, 7.3%
Line Drive – Well-Hit: .719, .815, 11.1%
Flyball – Weak: .078, .074, 18.5%
Flyball – Medium: .069, .081, 8.2%
Flyball – Well-Hit: .641, 1.168, 7.8%
Some of the results are basically the same like with Weak and Medium Fly Balls and Weak and Medium Line Drives. Besides aiming for categories with similar results, I felt some groups had too small of a data sample like the 2.3% of batted balls being Weak Line Drives. I would like the categories to have around 10% of all batted balls to help find similar hitters.
Here are the six types I came up with (these values are updated with the 2015 values so far).
Batted Ball Type: xBABIPwHR, wOBAcon, Overall %
Hard FB: 0.641, 1.162, 7.6%
Hard LD: 0.719, 0.820, 11.0%
Hard GB and Weak and Med LD: 0.644, 0.619, 13.6%
Medium GB: 0.461, 0.423, 9.6%
Weak GB: 0.151, 0.116, 32.0%
Weak and Medium FB: 0.075, 0.074, 26.3%
These categories have a nice hiearcial structure with both xBABIP and OBAcon declining except right at the beginning with Hard-Hit Line Drives having a higher xBABIP. My biggest issue I have with this setup is including Hard-Hit Groundballs in with the Weak and Medium Line Drives. I based my desicion on the outcomes being similar and the amount of Hard-Hit Ground Balls being low (3.8%). I may be talked into combining the two groundball values, but I think the outcomes are far apart.
It is time to speak up about the categories if you see any issues. I will move to these categories this Sunday when I release the first set of 2015 values.
Stabilization Points
I really wanted to see if/when wOBAcon and xwOBAcon become predictive/stabilize. As a general note, I probably don’t have enough information to do a good stabilization point, but these can be a starting point.
- wOBAcon (season 1) to wOBAcon (season 2): 315 batted balls
- xwOBAcon (season 1) to xwOBAcon (season 2): 145 batted balls
- xwOBAcon (season 1) to wOBAcon (season 1): 70 batted balls
We are getting closer to the 70 batted ball value in the 2015 season so the two in season values can be used. Targeting players whose production may change is getting close to being significant.
Other
Is there anything else you would like changed from the previous format seen here? I am going to use the same basic format for the rest of the season.
Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR twice, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.
The re-grouping makes sense to me, but are the batted-ball percentages based on just results from this year, and if so, are there enough events to make you comfortable that they’ll stabilize at about the same hierarchy going forward? You could consider sticking with the nine categories a bit longer to see if the distribution stays about the same.
The data is from 2012 to 2015, not just 2015.
Do we have this data on a player level? If so, couldn’t it be used to paint a clearer FIP and xFIP picture?
For instance maybe Sabathia is giving up really well hit grounders and that’s the difference in his awful early season ERA and FIP difference. Right now it looks like bad luck but if everything is well hit maybe it’s bad skill.
I found nothing:
“In small year-to-year samples with Inside Edge data, pitchers have no ability to allow or prevent hits. This is really no surprise, since batting average on balls in play (BABIP), which takes the defense behind the pitcher into account, stabilizes around 2,000 balls in play.”
http://www.hardballtimes.com/looking-at-pitcher-war/
I can accept that a weakly hit ground ball is out of the pitchers control what happens to it once it has left the bat. The fact that we have FIP suggests the pitcher has control over grounder/line drive/fly ball. Are you saying that a pitcher has no control over well hit or weakly hit balls in each category(according to the data)?
That may have been confusing. If a pitcher gives up a significantly greater percentage of well hit grounders, should that be considered bad luck, or could we find a correlation elsewhere for why he give up more well hit ground balls than average?
I really don’t like conceptually, the idea of lumping ground balls in with line drives due to similarity of rate, a ground ball is not a line drive, and I don’t think it should be treated as such no matter how hard it was hit, the similar values for two different categories of balls doesn’t really bother me at all, the fact that a ground ball is not a line drive does.
As an aside, what is wOBAcon?