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Yesterday we talked about the Diamondbacks minor league park factors. Today we'll address the major league club's run environment. For years Chase Field was known as a good hitters ballpark due to a dry climate at 1000 foot elevation, a great batter's eye, and a large outfield with angular corners that inflate extra base hits, indeed for many years Chase Field did in fact rate as a good hitters ballpark. 

That began to change in 2018 with the installation of the humidor, which tamped down homers and the overall number of hits. The environment changed even further in 2019 with the installation of the turf. The Chase Field grass, both infield and outfield, was previously known as one of the hardest and fastest in Major League Baseball. The turf installed by Arizona is not your 1980's variety of turf. It plays true, with fewer bad hops, and actually somewhat slower than the previous natural grass infield. The net result of that is Chase field has become a neutral ballpark and may even lean slightly in the pitcher's favor at this point. 

So why does this matter? When looking at baseball statistics in general, it's important to take into account the context of the team's home ballpark. Most fans intuitively understand that numbers put up in extreme batting environments such as Coors Field in Colorado, which is at 5000 feet elevation, are inflated. Conversely, extreme pitching environments like Petco Park in San Diego, which is at sea level, humid, and right on water, suppress those same batting numbers. But by how much, and what about all the other teams? 

Fortunately all of the major websites specializing in analytical statistical data calculate and employ park factors. In park factors, 100 represents a neutral environment, favoring neither hitter or pitcher. Over 100 favors the hitter and under 100 favors the pitcher. So Coors Field, which has a single year park factor of 115 for pitchers at Baseball Reference, and 115 at Baseball Savant's Statcast, inflates offense by roughly 15%. Petco Park has a 92 and 91 park factor respectively, suppressing offense by 8-9%. Chase Field has a 98 Park factor for 2022 at both Baseball Reference and Baseball Savant. The three year average is between 99-101. 

At the Statcast link above you can see factors broken out by category. It may be surprising to some to learn that Chase Field is not a homer friendly ballpark. The three year rolling average for homeruns is just 84, or 16% less than average, and ranks 25th. In 2022 that number was 73, ranking 29th in MLB. Chase Field still is a good place to hit doubles and triples however, thanks to the deep angular corners. 

So how do you use this data? The easiest way is to refer to park and league adjusted metrics, such as OPS+ and ERA+ from Baseball-Reference, which are also set to the same scale, 100 equals average, above is better than average, below is worse. You can also use wRC+ for hitters at Fangraphs, with over 100 being better than average or ERA- from Fangraphs. The one difference with ERA- is in that metric, lower than 100 is better, not higher. Both websites utilize these park factors in all of their WAR calculations as well. 

Another important point when considering context is the league run environment overall. Scoring is down in baseball across the board. And when you take out extra innings, which are inflated now due to starting with a runner on second, it's even more evident that scoring is down. 2022 was the third lowest scoring season in the first nine innings since 2013, with 2013-14 being the lowest.

The reaction to 2013-2014 low scoring rate was for MLB to start juicing the baseball in the second half of 2015. The average home run per fly ball rate jumped in the second half of 2015, from 10.8% to 11.8%, and went up further in 2016 to 12.8%. That continued to accelerate as the hitters got wise to what was going on and altered their approaches to swing for more homers, since clearly that's what MLB wanted and was rewarding. The peak HR/FB rate was 15.3% in 2019. The pendulum has swung back, as MLB deadened the baseball, and HR/FB dropped to 11.4% in 2022. 

It remains to be seen if MLB's calibrations and attempts to now increase balls in play and base hits by implementing the pitch timer and shift ban plays out. MLB batting average was just .243 in 2022. That's the lowest since 1968's low-water mark of .237. It's also the third year in a row MLB batting average was below .250. The last time MLB batting average was over .260 was in 2009.  It's notable however that from 1963-1972 MLB batting average was also below .250 in eight of the 10 seasons. They just didn't have the home run rates of today. 

You can try to mentally adjust and add 10-15 points of batting average in your head to try to put a modern batting average into context, or deduct 10-20 points of batting average from a Coors Field batter if you like. Or you can simply take a look at those park adjusted metrics mentioned above, which are readily available. 

One good example of this is Christian Walker. One may look at his .242 batting average and think that's low, but in fact it was almost exactly league average in 2022. Check out the table below. His 2022 OPS was 21 points lower than his 2019 season, but we can see from his OPS+ he went from 11% above league average to 26% above league average. That's a significant difference, and shows the power of utilizing park and league adjusted metrics based on park factors. 

YearB.A.OBPSLGOPSOPS+

2019

.259

.348

.476

.825

111

2022

.242

.327

.477

.804

126

Here is another example from the pitching side, Cy Young contender Zac Gallen. His ERA is 27 points lower this year compared to 2019, yet once adjusted for the proper context, his ERA+ is virtually the same. 

YearIPERAERA+

2019

80

2.81

156

2022

184

2.54

158

One last example of how of ballparks can distort our view. C.J. Cron for Colorado, Nico Hoerner for the Chicago Cubs, and Ha-Seong Kim for the San Diego Padres all had the same 107 OPS+ despite a wide separation in their raw unadjusted OPS. That's the power of the park factor. 

PlayerHome Park FactorOPSOPS+

C.J. Cron

113

.783

107

Nico Hoerner

100

.736

107

Ha-Seong Kim

92

.708

107