Balls In Play Expected Homers Leaderboard
Mike Podhorzer and Chad Young embarked on a journey–quest to find an offensive expected (x)HR/FB rate.
Based on batted ball distance and angle, you can go to Baseball Heatmaps (BHM) and find expected versus actual homers or verify HR/FB ratios through HR+FB average distance.
Here’s an uber simple descriptive balls-in-play (BIP) expected homer (xHR) formula:
xHR = PA*Contact%*OFFB%*HR/FB. Looking at the outcomes from last year we have the following list first ordered by the most likely regressions:
I think it’s safe to say Albert Pujols, Alexei Ramirez, Nelson Cruz are likely to regress in the homer department. BHM agrees with Pujols, Cruz and Adam Jones who are all top 20 likely to regress by angle and distance as well. On the other hand, BHM presents Trout as the 2nd largest differential after Chris Carter. From a BIP xHR perspective, Mike Trout is on the exact other side of the spectrum:
The above verifies Trout’s HR total and then some. It’s nice to see Anthony Rizzo up there as well.
Using this formula (xHR = PA*Contact%*OFFB%*HR/FB), let’s see what are largest xHR totals are if everyone had exactly 600 PA:
Madison Grand Slam Bumgarner! Number 5 overall!
Who is this Ben Paulsen guy at #6? I’ll tell you who he is. He is your deep, NL only or daily fantasy platoon lefty bat if something happens to Justin Morneau.
Dilson Herrera?! Not bad for a 20-year old second baseman. Sample-size-schmample-size.
In our Mock Draft, J.D. Martinez went in the 5th round. He should have ample opportunities to drive guys in, sure, but we are now in round 17 and Brandon Belt is still available. From a homer perspective, they were almost identical last year.
Nelson Cruz didn’t even crack 30 HR. It took luck, Baltimore and almost 680 Plate Appearances for him to hit 40 last year. This and a move to Seattle should help you appreciate Steamer’s projection of 26 HR for him next year in 570 PA.
When evaluating this list, keep in mind that guys like Paulsen and Scott Van Slyke are assets in a platoon or for daily fantasy sites. Their stats can’t be extrapolated as depicted, but the list is still fun and helps present sleeper HR options.
Daniel Schwartz contributes for RotoGraphs when he's not selling industry leading thermal packaging. You can follow him on twitter @RotoBanter
It seems a little unlikely that there would be that much more downward regression expected than upwards. Were there really 275 too many home runs last year?
I apologize if I’ve incorrectly interpreted this, but a couple things seem wrong here.
1) Are you using FB%-IFFB% = OFFB%? Because IFFB% = IFFB/FB, not IFFB/BIP, so that’s not correct.
2) Why are you using contact rate? I understand that if you just used BIP/PA then you’d get an xHR = actual HR, but it seems wrong because it ignores pitches not swung at and their outcomes (walks and looking strike outs).
Wouldn’t your best bet be to use projected PA, BB%, K%, SF%, etc, to determine a projected BIP number, apply the correctly calculated FB% to determine #FB, and then use Mike and Chad’s xHR/FB numbers to determine xHR?
this is what I do in my own projection system, yes:
“Wouldn’t your best bet be to use projected PA, BB%, K%, SF%, etc, to determine a projected BIP number, apply the correctly calculated FB% to determine #FB, and then use Mike and Chad’s xHR/FB numbers to determine xHR?”
Before their xHR/FB, i went trending/career HR/FB or regressed based on avg. distance (manual vs. formula)
Get some Dilson, get some Dilson, get some Dilson, WHOOOOAAAAA gimme some!
I don’t think Adam Dunn will hit more homers this year.
Just to pass the eye test…in 2013, 13 player hit 30HR. In ’14, 11 players hit 30 or more HR, but this excludes Goldy and Trumbo, so 13 is basically my mark for this year. Eliminating the P and platoon guys, the list produces around 13, maybe 15, so yeah, it’s obviously passed the eye test as does most the work coming from this crew. Hope this isn’t taken anyway, but a birds eye of the situation. The players I accrued also have the skills and situations that work in their favor, so I’ll defiantly be tracking this chart come ’16. Thanks guys. The information here is just incredible.
so I am holding on to Mesoraco for $1….
Holy cow Zach Walters! I’ll take the over on Miguel Cabrera and 21 HR / 600 PA.
I want to use this for fantasy valuations as much as the next guy, but when I try to look at these stats from a team perspective, everything looks about where it should be. Using the equation Team Sum(HRdiff*PA)/Team PA with your spreadsheet I tried to find what the average HRdiff per player per National League team was once you normalize for PA. I see that the average Rockies player far and away hit more HR than expected (-2.96), followed by the Reds (-1.95), and then everyone else . At the other extreme, the teams that were the most unlucky were the Mets (0.10), Giants (-0.07), and Padres (-0.26), all of whom play in notorious pitchers’ parks. To take the next step, you may want to refine the data using park factors to make the data more predictive of future home run rates.
Actually, the Mets don’t play in such a notorious pitcher’s park anymore. For 2014 Citi Field finished 18th, but in 2013 it finished 10th in park factors. (Granted, 2014 was a strange year in some respects for park factors: Safeco finished 12th and Camden Yards finished 20th, something I don’t think we’ll see again in 2015.)
They’ve moved the fences at Citi Field once, and they will again for 2015.
Which should be good news for those people who have rostered Lucas Duda and Dilson Herrera (though the latter may not see much playing time in 2015).
Crazy that Domonic Brown only hit 10 HR and that was still higher than his xHR.