Last month I introduced a new metric, earned home runs (eHR). For the background and origin of the metric, feel free to check it out here. I’ve made a few slight adjustments to the equation after determining that pulled fly balls and park factors had a more significant impact on home runs than I originally accounted for. Based on this information, I’ve adjusted the weights for each factor accordingly in my formula A more complete list of 2019 earned home runs is shown at the bottom of this article. The purpose of this article is to determine if the eHR metric has any predictive power.







I’ve received some requests about the year-to-year correlation of eHR. Unfortunately, I’m not proficient in r, not even a little bit, so pulling data takes time for a caveman, like myself. Additionally, the properties of the ball seem to change every year during the Statcast Era which began in 2015 making it difficult to accurately determine the year-to-year correlations. With this in mind, I only went back one year to 2018 (year 1), 2019 being year 2.

After calculating the 2018 eHR, I compared 2018 earned home run per plate appearance (eHR/PA) and 2018 earned home run per fly ball (eHR/FB) to 2019 HR/PA and 2019 HR/FB. Due to the large increase in HR/FB% from year 1 to year 2, I had to adjust the baseline from year 1 to year 2. I then compared the players that appear in both samples to determine the year 1 to year 2 correlation of HR/PA and HR/FB. Now, there is one caveat. I only utilized players within my sample which is much smaller than 100% of the player pool. I did this as an attempt to eliminate small samples because barrels are a major variable in my equation. Players with either a low number of plate appearances (under 200) or low barrel totals seemed to skew the results. So, they gone. It’s not perfect, but at least it utilizes the same sample of players from year 1 (2018) to year 2 (2019). Here are the results:

Year-to-Year Metrics r-squared 2018 HR/PA-2019 HR/PA 0.213 2018 eHR/PA-2019 HR/PA 0.231 2018 HR/FB-2019 HR/FB 0.303 2018 eHR/FB-2019 HR/FB 0.342









So, what does this mean? You may be wondering why are the correlations so low. I thought the same thing because in the past HR/PA and HR/FB year-to-year correlations were typically stronger. But, remember, I used a limited sample, so this data in no way mimic’s the league as a whole. Secondly, the change in HR/FB% from 2018 to 2019 was 2.6% (12.7% to 15.3%). Between 2015 and 2018, the year-to-year difference in HR/FB% was never more than 1.4%. The stark difference in home run rate between 2018 to 2019 partially explains the weaker correlation.

OK, back to the correlations in the table above. Let’s not get carried away. It’s just one year where the eHR metric performed slightly better than using actual home runs. It’s difficult to say at this point that the eHR metric has more predictability than strictly looking at HR/PA or HR/FB but it’s a start. What it can do with more confidence is help identify outliers. Based on this information we can expect a large portion of the players identified in my original article to regress towards the mean rather than continue to be extreme outliers. Additionally, it can help establish breakouts that don’t register by just looking at a player’s Statcast page because eHR utilized home run park factors (home), pulled fly ball rate, etc.

Year 1 to Year 2 HR/FB Predictions based on eHR

Year 2 Correct Prediction year 1 HR/FB over-perf 55.6% year 1 HR/FB under-perf 55.7% year 1 HR/FB over (outliers) 72.0% year 1 HR/FB under (outliers) 60.0%

Let’s start with the HR/PA metric first. Just over 56% of both 2018 over and under-performers regressed toward the mean based on my eHR metric in 2019. While these results don’t scream breakthrough, it’s a decent start. Based on the year 1 data, more than half of the players performed the way the metric expected them to perform in year 2, so that’s good. Moving over the HR/FB, we see the results are a little bit better. While once again, just under 56% of the under-performers regressed toward the mean and just over 66% of the over-performers regressed the following year! That’s two-thirds fam! I’ll take that all day but I can’t explain why the stark difference. More research to follow, I just need to either learn r or find some to scrape data for me. Any takers?







As I mentioned earlier, the most important way to digest this analysis is to focus on the outliers. After adjusting for the league-wide increase in HR/FB rate from 2018 to 2019, 15 of the top 25 players under-performed outliers from 2018 improved their HR/FB rate in 2019. That’s a modest 60%. On the other end, 18 of the top 25 over-performed outliers from 2018 decreased their HR/FB rate in 2019. That’s a more optimistic 72%. The year one to year two correlations are moderate-to-weak but they are not completely useless. I plan on interpreting Alex Chamberlain’s Deserved Barrel metric in conjunction with my eHR metric to determine a more concrete list of players I feel confident about going into 2020.

If you’ve made it this far, thank you for reading and your patience is appreciated. Below is the complete list of earned home runs from players in my sample. I’ve also included a Google Sheet that has the 2018 data along with 2019. Remember, for reference, the league average home run per barrel rate (HR/BRL%) in 2019 was 59.59%.

Player BRL HR/BRL HR eHR Delta Jorge Soler 70 61.43% 48 49.38 1.38 Ronald Acuna Jr. 66 60.61% 41 44.44 3.44 Mike Trout 66 65.15% 45 51.53 6.53 Pete Alonso 66 72.73% 53 55.13 2.13 Nelson Cruz 65 56.92% 41 48.39 7.39 Jose Abreu 63 47.62% 33 47.09 14.09 Christian Yelich 59 62.71% 44 44.94 0.94 Freddie Freeman 59 57.63% 38 36.97 -1.03 Cody Bellinger 59 71.19% 47 46.94 -0.06 Josh Donaldson 62 56.45% 37 47.39 10.39 Bryce Harper 59 57.63% 35 45.93 10.93 Anthony Rendon 56 48.21% 34 43.99 9.99 Eugenio Suarez 55 80.00% 49 48.39 -0.61 Kyle Schwarber 55 63.64% 38 40.14 2.14 Josh Bell 53 60.38% 37 37.56 0.56 Nicholas Castellanos 53 39.62% 27 33.18 6.18 Matt Chapman 54 61.11% 36 39.99 3.99 J.D. Martinez 53 60.38% 36 35.90 -0.10 C.J. Cron 53 45.28% 25 39.47 14.47 Gary Sanchez 52 63.46% 34 43.88 9.88 George Springer 53 64.15% 39 39.54 0.54 Juan Soto 51 52.94% 34 37.30 3.30 Mookie Betts 52 38.46% 29 33.86 4.86 Matt Olson 50 64.00% 36 41.54 5.54 Franmil Reyes 51 66.67% 37 38.15 1.15 Austin Meadows 50 50.00% 33 36.43 3.43 Christian Walker 49 53.06% 29 33.08 4.08 Rafael Devers 48 54.17% 32 32.34 0.34 Javier Baez 48 56.25% 29 35.09 6.09 Michael Conforto 48 64.58% 33 36.96 3.96 Paul Goldschmidt 49 67.35% 34 35.01 1.01 Trey Mancini 48 62.50% 35 35.12 0.12 Marcus Semien 47 61.70% 33 32.63 -0.37 Miguel Sano 47 68.09% 34 38.65 4.65 Marcell Ozuna 47 61.70% 29 36.40 7.40 Aaron Judge 48 52.08% 27 35.21 8.21 Ketel Marte 45 57.78% 32 34.66 2.66 Rougned Odor 47 55.32% 30 40.00 10.00 Yoan Moncada 44 54.55% 25 31.51 6.51 Carlos Santana 45 64.44% 34 35.21 1.21 Kole Calhoun 44 70.45% 33 34.62 1.62 Renato Nunez 43 67.44% 31 36.15 5.15 Avisail Garcia 43 41.86% 20 28.07 8.07 Mike Moustakas 44 65.91% 35 36.03 1.03 Eloy Jimenez 43 65.12% 31 31.92 0.92 Yasmani Grandal 43 58.14% 28 32.12 4.12 Xander Bogaerts 43 60.47% 33 31.79 -1.21 Gleyber Torres 43 74.42% 38 36.35 -1.65 Max Muncy 42 73.81% 35 31.75 -3.25 Yasiel Puig 41 51.22% 24 29.56 5.56 Charlie Blackmon 40 57.50% 32 32.44 0.44 Eddie Rosario 41 60.98% 32 34.23 2.23 Edwin Encarnacion 40 72.50% 34 34.90 0.90 Rhys Hoskins 39 51.28% 29 32.52 3.52 Nolan Arenado 40 72.50% 41 37.84 -3.16 Francisco Lindor 38 60.53% 32 30.48 -1.52 Luke Voit 38 52.63% 21 26.99 5.99 Hunter Dozier 38 52.63% 26 24.24 -1.76 DJ LeMahieu 39 51.28% 26 26.71 0.71 Paul DeJong 38 68.42% 30 32.57 2.57 Max Kepler 38 68.42% 36 34.70 -1.30 Kris Bryant 37 72.97% 31 26.71 -4.29 Yordan Alvarez 38 57.89% 27 29.03 2.03 Dansby Swanson 37 43.24% 17 21.55 4.55 Manny Machado 37 67.57% 32 29.22 -2.78 Starling Marte 37 62.16% 23 23.33 0.33 Randal Grichuk 36 66.67% 31 32.30 1.30 Eduardo Escobar 36 66.67% 35 27.83 -7.17 J.T. Realmuto 37 48.65% 25 27.23 2.23 J.D. Davis 36 58.33% 22 25.00 3.00 Domingo Santana 36 55.56% 21 25.02 4.02 Mitch Garver 35 71.43% 31 28.28 -2.72 Trevor Story 36 69.44% 35 25.80 -9.20 Jorge Polanco 35 51.43% 22 23.14 1.14 Tommy Pham 35 51.43% 21 22.89 1.89 Shin-Soo Choo 35 60.00% 24 24.16 0.16 Ji-Man Choi 35 42.86% 19 24.48 5.48 Brandon Belt 35 28.57% 17 20.71 3.71 Ryan Braun 35 60.00% 22 25.82 3.82 Hunter Renfroe 35 80.00% 33 33.63 0.63 Nomar Mazara 35 45.71% 19 23.23 4.23 Joc Pederson 35 85.71% 36 31.36 -4.64 Justin Smoak 34 58.82% 22 24.76 2.76 Rowdy Tellez 34 50.00% 21 25.55 4.55 Ozzie Albies 35 54.29% 24 19.52 -4.48 Jose Altuve 34 76.47% 31 28.35 -2.65 Daniel Vogelbach 34 73.53% 30 26.59 -3.41 Ian Desmond 34 55.88% 20 24.62 4.62 Khris Davis 34 61.76% 23 22.37 -0.63 Jackie Bradley Jr. 34 52.94% 21 21.27 0.27 Shohei Ohtani 34 52.94% 18 24.46 6.46 Joey Gallo 34 61.76% 22 27.75 5.75 Eric Hosmer 33 63.64% 22 21.76 -0.24 Howie Kendrick 33 51.52% 17 23.18 6.18 Andrew Benintendi 33 30.30% 13 18.76 5.76 Starlin Castro 33 57.58% 22 18.56 -3.44 Jorge Alfaro 32 53.13% 18 21.74 3.74 Jonathan Villar 32 71.88% 24 24.17 0.17 Teoscar Hernandez 31 64.52% 26 23.08 -2.92 Justin Turner 31 67.74% 27 24.17 -2.83 Willy Adames 32 53.13% 20 21.30 1.30 Danny Santana 31 74.19% 28 23.15 -4.85 Ramon Laureano 31 64.52% 24 24.60 0.60 Brian Anderson 31 48.39% 20 19.64 -0.36 Brandon Lowe 30 50.00% 17 22.03 5.03 Nick Ahmed 30 60.00% 19 16.65 -2.35 Fernando Tatis Jr. 30 66.67% 22 23.79 1.79 Roberto Perez 30 63.33% 24 20.88 -3.12 Wil Myers 30 53.33% 18 23.76 5.76 Willson Contreras 30 63.33% 24 21.93 -2.07 Anthony Rizzo 30 70.00% 27 23.50 -3.50 Jay Bruce 31 70.97% 26 24.48 -1.52 Mike Yastrzemski 30 63.33% 21 18.39 -2.61 Ryan McMahon 29 75.86% 25 21.33 -3.67 Vladimir Guerrero Jr. 29 51.72% 15 20.87 5.87 Corey Seager 29 55.17% 19 17.42 -1.58 Brandon Dixon 29 44.83% 15 17.98 2.98 Michael Brantley 30 56.67% 22 22.60 0.60 Keston Hiura 29 62.07% 19 19.56 0.56 Matt Adams 29 58.62% 20 24.98 4.98 Mark Canha 29 79.31% 26 23.45 -2.55 Trea Turner 28 57.14% 19 19.47 0.47 Joey Votto 28 50.00% 15 18.77 3.77 David Dahl 28 46.43% 15 21.25 6.25 James McCann 28 60.71% 18 19.23 1.23 Jonathan Schoop 28 67.86% 23 22.89 -0.11 Brandon Drury 28 46.43% 15 20.47 5.47 Evan Longoria 26 69.23% 20 13.40 -6.60 Kyle Seager 26 61.54% 23 19.89 -3.11 Carlos Correa 28 64.29% 21 21.42 0.42 Mitch Moreland 26 57.69% 19 18.18 -0.82 Adam Jones 26 57.69% 16 16.31 0.31 Colin Moran 26 38.46% 13 16.55 3.55 Yandy Diaz 26 42.31% 14 18.03 4.03 Lourdes Gurriel Jr. 26 65.38% 20 18.99 -1.01 Garrett Cooper 26 57.69% 15 15.85 0.85 Dexter Fowler 26 61.54% 19 16.70 -2.30 Kevin Pillar 26 65.38% 21 13.21 -7.79 Albert Pujols 26 69.23% 23 23.78 0.78 Jose Ramirez 26 61.54% 23 23.90 0.90 Alex Bregman 26 84.62% 41 26.61 -14.39 Michael Chavis 25 64.00% 18 17.55 -0.45 Scott Kingery 25 60.00% 19 18.33 -0.67 Alex Gordon 25 44.00% 13 13.87 0.87 Todd Frazier 25 40.00% 21 24.22 3.22 Jason Castro 26 50.00% 13 17.87 4.87 Gio Urshela 25 72.00% 21 19.73 -1.27 Miguel Cabrera 25 32.00% 12 10.27 -1.73 Pablo Sandoval 24 50.00% 14 14.44 0.44 Christian Vazquez 24 66.67% 23 17.28 -5.72 Bryan Reynolds 25 60.00% 16 15.93 -0.07 Jason Heyward 24 70.83% 21 14.80 -6.20 Eric Thames 24 66.67% 25 19.64 -5.36 Whit Merrifield 24 45.83% 16 9.87 -6.13 Adalberto Mondesi 24 37.50% 9 14.70 5.70 Jurickson Profar 24 58.33% 20 17.60 -2.40 Harrison Bader 23 47.83% 12 15.03 3.03 Anthony Santander 23 78.26% 20 20.15 0.15 Robinson Cano 24 50.00% 13 16.01 3.01 Maikel Franco 23 69.57% 17 20.21 3.21 Austin Riley 23 73.91% 18 16.33 -1.67 Freddy Galvis 23 60.87% 23 17.58 -5.42 Stephen Piscotty 22 59.09% 13 11.83 -1.17 JaCoby Jones 22 50.00% 11 14.88 3.88 Matt Carpenter 23 47.83% 15 12.45 -2.55 Ryan O'Hearn 21 66.67% 14 11.81 -2.19 Carson Kelly 21 66.67% 18 13.78 -4.22 Nick Senzel 22 50.00% 12 16.87 4.87 Jeff McNeil 21 61.90% 23 18.45 -4.55 Marwin Gonzalez 21 66.67% 15 14.77 -0.23 Harold Ramirez 21 47.62% 11 11.57 0.57 Chad Pinder 21 52.38% 13 14.01 1.01 Cavan Biggio 21 66.67% 16 16.25 0.25 Jason Kipnis 21 66.67% 17 13.34 -3.66 Brian Dozier 21 71.43% 20 18.98 -1.02 Travis d'Arnaud 21 61.90% 16 12.69 -3.31 Brandon Crawford 21 42.86% 11 12.43 1.43 Derek Dietrich 21 71.43% 19 19.72 0.72 Hunter Pence 20 60.00% 18 14.96 -3.04 Asdrubal Cabrera 20 55.00% 18 15.95 -2.05 Tim Anderson 20 60.00% 18 12.42 -5.58 Pedro Severino 20 50.00% 13 16.06 3.06 Stephen Vogt 20 40.00% 10 12.52 2.52 Aristides Aquino 20 80.00% 19 19.58 0.58 Jordan Luplow 20 70.00% 15 15.72 0.72 Christin Stewart 20 40.00% 10 12.67 2.67 Robinson Chirinos 20 65.00% 17 17.86 0.86 Mitch Haniger 20 75.00% 15 17.17 2.17 Amed Rosario 21 52.38% 15 12.21 -2.79 A.J. Pollock 19 63.16% 15 14.39 -0.61 Enrique Hernandez 19 68.42% 17 18.84 1.84 Victor Robles 20 65.00% 17 15.06 -1.94 Mike Zunino 19 47.37% 9 14.97 5.97 Yuli Gurriel 19 84.21% 31 21.33 -9.67 Tyler Naquin 19 47.37% 10 12.89 2.89 Lorenzo Cain 19 47.37% 11 11.62 0.62 Martin Maldonado 19 42.11% 12 15.72 3.72 Wilson Ramos 19 68.42% 14 13.57 -0.43 Tyler Flowers 19 52.63% 11 14.07 3.07 Tom Murphy 19 57.89% 13 17.08 4.08 Tim Beckham 18 72.22% 15 14.03 -0.97 Brian Goodwin 18 77.78% 17 13.59 -3.41 Kevin Kiermaier 19 68.42% 14 10.76 -3.24 Chris Davis 18 55.56% 12 13.88 1.88 Jesus Aguilar 18 61.11% 12 10.68 -1.32 Niko Goodrum 18 44.44% 12 11.24 -0.76 Omar Narvaez 18 88.89% 22 12.74 -9.26 Adam Eaton 18 61.11% 15 8.43 -6.57 Jose Martinez 18 50.00% 10 10.64 0.64 David Freese 18 55.56% 11 11.94 0.94 Elvis Andrus 18 44.44% 12 8.82 -3.18 Byron Buxton 17 52.94% 10 15.75 5.75 Alex Verdugo 17 47.06% 12 11.45 -0.55 Orlando Arcia 18 55.56% 15 14.04 -0.96 Danny Jansen 16 75.00% 13 14.50 1.50 Justin Upton 17 70.59% 12 13.57 1.57 Didi Gregorius 16 68.75% 16 14.34 -1.66 Buster Posey 16 43.75% 7 5.37 -1.63 Brett Gardner 16 87.50% 28 17.58 -10.42 Ian Happ 14 71.43% 11 8.86 -2.14 Tommy La Stella 14 100.00% 16 9.73 -6.27 Josh Reddick 15 60.00% 14 8.66 -5.34 Aaron Hicks 15 66.67% 12 13.88 1.88 Oscar Mercado 15 53.33% 15 9.42 -5.58 Bo Bichette 13 76.92% 11 9.53 -1.47 Willie Calhoun 16 87.50% 21 18.64 -2.36 Jesse Winker 14 78.57% 16 9.12 -6.88 Chris Taylor 15 60.00% 12 9.39 -2.61 Mike Tauchman 12 83.33% 13 8.71 -4.29 Ronny Rodriguez 15 73.33% 14 12.57 -1.43 Alex Dickerson 12 41.67% 6 6.52 0.52 Matt Beaty 11 72.73% 9 8.47 -0.53 Maunel Margot 11 54.55% 12 9.48 -2.52 Nate Lowe 11 54.55% 7 6.59 -0.41

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