Last April, I developed home run park factors based using a combination of home run per barrel rate (HR/BRL%) and non-barreled home runs. The data I used was from Baseball Savant. I gathered the data from each season 2015 through 2018 at each ballpark. Essentially how it worked was any park that allowed higher than league-average HR/BRL rates and allowed more non-barreled home runs were more favorable and vice-versa for parks that scored below-average. This was relatively simplistic but it allowed me to determine that Great American Ballpark in Cincinnati was the most friendly park in MLB for home runs and that Fenway Park in Boston is indeed a poor park for home runs. Naturally, the next step was to breakdown each park directionally (left field, centerfield, right field).







I pulled data from the last three seasons to determine directional home run park factors. I choose a three-year sample for two reasons. First, some of the sample sizes seemed a little small using just a single season of data. Second, combining two juiced ball seasons with one “dead ball” season may be a good way to aggregate how the 2020 ball might respond if there is a slight adjustment to the ball. Of course, it’s anyone’s guess as to how or if the properties of the ball will change, but at minimum I’m accounting for the range of possibilities here. Before I get down into the final park factors, below are the directional HR/BRL% for both right-handed hitters and left-handed hitters.

Left Field Centerfield Right Field Right-Handed Hitters 75.82% 42.3% 49.65% Left-Handed Hitters 46.80% 43.2% 73.55%

Not surprisingly, pulling the ball yields a much high home run percentage compared to balls hit to center or balls hit to the opposite field. Based on this information, I separated right-handed and left-handed hitters when determining the directional park factors due to the large discrepancies in HR/BRL%. For example, I ran home run park factors to left field for pulled fly balls by right-handed hitters and opposite-field fly balls hit by left-handed hitters. Then, I created a formula to combine the two for a final left-field park factor. I did the same thing for right field park factors. Hopefully, this makes sense. Just to be clear, these park factors are for home runs only. OK, enough of the boring explanations, let’s get to the Home Run Park Factors.







Note: 1.0 is neutral, less than 1.0 is below-average, over 1.0 is above-average

Home Run Park Factors Using Statcast (FreezeStats)

Venue/Park Team LF PF CF PF RF PF GABP CIN 1.107 1.136 1.176 Oriole Park BAL 1.113 1.144 1.012 Miller Park MIL 0.984 1.145 1.108 Coors Field COL 1.008 1.144 1.055 Guaranteed Rate Fld CWS 1.051 1.032 1.114 Dodger Stadium LAD 1.004 1.215 0.976 Citi Field NYM 1.064 1.027 1.057 Minute Maid Park HOU 1.102 0.886 1.155 Citizens Bank Park PHI 1.079 0.965 1.084 Angel Stadium LAA 0.911 1.197 1.010 Petco Park SDP 1.077 1.055 0.981 Globe Life Park TEX 0.973 1.048 1.087 Yankee Stadium NYY 0.948 0.931 1.212 Nationals Park WSH 1.020 1.102 0.936 Progressive Field CLE 0.956 1.031 1.054 T-Mobile Park SEA 0.988 1.026 1.006 Rogers Centre TOR 1.012 1.006 0.995 Oakland Coliseum OAK 1.025 1.008 0.943 SunTrust Park ATL 0.965 0.999 1.003 Chase Field ARI 1.073 0.861 1.006 Tropicana Field TBR 1.018 0.927 0.985 Wrigley Field CHC 0.992 1.027 0.909 PNC Park PIT 0.880 1.022 0.962 Target Field MIN 0.966 0.925 0.954 Busch Stadium STL 0.914 1.025 0.887 Marlins Park MIA 0.929 0.917 0.961 Kauffman Stadium KCR 0.955 0.856 0.874 Comerica Park DET 1.007 0.692 0.958 Fenway Park BOS 0.912 0.862 0.844 Oracle Park SFG 0.940 0.854 0.717

Some things that jumped out at me upon seeing the results is that both Los Angeles ballparks are extremely favorable to centerfield. Dodger Stadium and Angel Stadium rank one and two, respectively for home runs to centerfield based on my HR Park Factors. Without diving in too deep, I noticed that Angel Stadium is perfect for Shohei Ohtani (the batter). Ohtani hits nearly 37% of his fly balls to centerfield and he absolutely crushes balls up the middle. It partially explains how he has maintained an insanely high 40.4% HR/FB on fly balls to center compared to league-average 10.5%. Another player who benefited from playing half his games in Angel Stadium over the last couple of seasons is Justin Upton (2019 injury notwithstanding). He’s hit a whopping 45.4% of his fly balls to centerfield since the start of 2018. There’s a reason that his HR/FB rate jumped once he was traded from Detroit to LA (23.4% w/ LAA compared to his career 16.6% HR/FB%).

On the flip side, centerfield at Comerica Park in Detroit is where fly balls go to die. That tweet was from back in April, so I had a feeling Detroit was awful to center but it’s worse than I thought compared to other parks. Consider this, since the start of 2017, no park has seen more barreled balls to centerfield than Comerica Park (404 barrels), but only 12.13% of those barreled balls turned into home runs (49 home runs). That is the fewest number of barreled home runs to centerfield since 2017 in all of baseball. That’s crazy! Just for fun, if Comerica played neutral to center, there would have been an ADDITIONAL 127 home runs hit over the last three seasons. If it played as favorable as Dodger Stadium has over that time frame, we would have seen a whopping 222 additional home runs to centerfield alone! It’s amazing Miguel Cabrera surpassed the 40-homer plateau multiple times while playing in Detroit despite hitting 35-40% of his fly balls to center. Nick Castellanos gets a huge boost wherever he lands in 2020 because he hit 41.5% of his fly balls to center in 2019.







A few other interesting observations that jumped out at me is that Oakland Collusiem and Petco Park in San Diego actually play somewhat favorable for home runs. Both play above-average to centerfield and left field. So, let’s give Manny Machado another chance to bounce back in 2020 even though Petco is still a downgrade compared to Oriole Park. I’ll touch on Yankee Stadium’s right field but the park is below-average to center and left field. I’m beginning to understand why Aaron Judge hits so many balls to the opposite field. Citi Field, the other park in New York, ranks as the seventh most favorable park for home runs by my park factors. If you recall, they moved the fences in before the 2015 season, so that modification has done wonders for their hitters. It also makes what Jacob deGrom’s done over the last two seasons extremely impressive.

Oriole Park, Great American Ballpark (GABP), and Minute Maid Park are the top three parks for home runs to left field. I’m not surprised, because GABP is favorable to all fields and Minute Maid has the short porch in left thanks to the Crawford Boxes (84.14% HR/BRL for pulled FB to left). Although Minute Maid is even better for left-handed pull power but below-average to center. Oriole Park has proven to be more favorable for right-handed pull power and straight-away center but plays neutral to right field. We should shift our analysis for left-handed pull hitters and right-handed hitters who favor the opposite field in Baltimore as they may not see a boost in power numbers. PNC Park in Pittsburgh is the worst for home runs to left field but is OK to center and right. More on this in a future article.

Oracle Park is a nightmare for power hitters who favor right field. That’s a well-known fact of course. However, the fences are indeed coming in as the bullpen is now moving behind the right field wall! It’s hard to say how much this will improve the home run park factors in Oracle because the entire park plays unfavorable. Either way, I’m intrigued by Brandon belt (if he stays in SF), Mike Yastrzemski , and Alex Dickerson. In fact, one of my bold predictions involves Alex Dickerson surpassing 20 home runs in 2020. The number-one venue to right field is Yankee Stadium. Along with the juiced ball, it helped boost Didi Gregorius’ power numbers and resurrect Brett Gardner’s power. Great American Smallpark comes in at number two and how about Minute Maid Park ranking third to right field. It’s actually MORE favorable than left field with the Crawford Boxes!

I had to dig a little deeper to find out why Minute Maid was so favorable to right field. It ranked second in HR/BRL% to right field and allowed the fourth-most non-barreled home runs. Minute Maid is only 326 feet down the right field line which is 11 feet deeper than the short porch in left field, however, the height of the wall is only seven feet high in right field as opposed to the 19 and 25-foot walls in left and left-center. In the power alley (right-center), the fence is 373 feet from home plate and 10-feet in height. Again, this is 11 feet further than left-center but with a much shorter wall. In other words, batted balls with a lower trajectory have a higher probability to be a home run to right field than to left field in Houston. Meanwhile, non-barreled fly balls with high launch angles to left field have left Minute Maid 113 times in three seasons, most in MLB.







My next article will look at hitters and some pitchers who are changing parks and how we should evaluate each player based on the park change. Obviously, we need to see more signings before that happens. To reiterate, these park factors do not consider singles, doubles, or triples, so they are not complete park factors. They are strictly measuring how favorable/unfavorable each park is for home runs to each part of the field using Statcast metrics (barrels and on-barrels). ESPN and FanGraphs along with several other sites have overall park factors, but we care about the long ball!

This metric can be extremely helpful for the evaluation of certain players who have extreme pull or oppo tendencies on their batted balls. Heavy pull hitters or hitters with a higher percentage of opposite-field fly balls can be analyzed and projected more accurately. I could also see where this metric could provide value for DFS purposes. For example, imagine righty-masher Joc Pederson in Yankee Stadium against a right-handed pitcher. That’s easy money right there. I’m open to any questions or ideas you may have as well. Feel free to hit me up on Twitter @FreezeStats.

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