Coors Field: Blessing or Curse?

Being a Rockies fan for most of my life, I’ve had my fair share of discussions about how a ballpark can affect not only the performance of the home team, but also that of the visiting team. At this point, I don’t think anyone has any doubt that Coors Field is a hitter’s park. However, there are a couple of questions regarding this park I’d like to address. First of all, is Coors Field alone in its capacity of enhancing offense, or is it comparable to other parks around the league? And secondly, is this effect stronger among Rockies’ hitters than it is for hitters from other teams?

To answer the first question, let’s compare offensive production at home versus on the road for each team, so we can see where the Rockies stand among the rest of the league in this regard. I selected a time frame from 1995 to 2015, simply because it is the same time frame that Coors Field has been hosting baseball games. For teams that moved to a new park during that time, we’ll consider only the seasons played in the newest stadium. The comparing stat we’ll use is OPS. I chose OPS instead of runs scored (which many park factors out there use) to take sequencing out of the equation. The order in which individual events occur in baseball can depend on things like lineup construction or managerial in-game decisions, but mostly it’s just random chance. I could have chosen a sounder, more sophisticated stat like wOBA, but OPS is more readily available, and a wider array of audiences are familiar with it.

After constructing a table for each team, consisting of year by year home and away OPS, I calculated the percent change of the two means, using the away value as the base. But simply comparing means can be very misleading. Randomness will always create a difference between two means, even if there is no actual effect causing it. In order to have some confidence that the differences we observe are statistically significant, I ran a Student’s t-test to each set of data (i.e. yearly home and away OPS for each team). The threshold of significance was set at 0.10, which means that there would be a 10% chance of seeing these differences if there were no real effect.  Anything above that value was considered not significant.

The following table contains the percent change for every team, along with its p-value. Red values don’t satisfy the significance criterion.

Park Change p-value Park Change p-value
COL 27.01% <0.01 BAL 4.10% 0.01
TEX 10.44% <0.01 DET 3.92% 0.03
ARI 9.52% <0.01 PIT 3.45% 0.02
BOS 8.39% <0.01 ATL 2.61% 0.10
HOU 7.48% <0.01 STL 2.30% 0.13
NYY 6.86% 0.07 MIA 2.20% 0.29
MIN 6.10% 0.04 CLE 1.81% 0.21
CIN 6.00% <0.01 OAK 1.33% 0.23
TOR 5.85% <0.01 TB 1.22% 0.20
CHC 5.70% <0.01 LAA 0.36% 0.41
CWS 5.12% 0.01 SF 0.22% 0.46
MIL 4.86% <0.01 LAD -1.64% 0.14
KC 4.76% <0.01 NYM -2.69% 0.15
WAS 4.65% 0.01 SEA -3.11% 0.12
PHI 4.55% 0.06 SD -5.46% 0.01

According to these numbers, 19 out of 30 ballparks have a statistically-significant positive effect on the home team’s offense, while 10 of them can be considered “neutral” due to the non-significant nature of the data, and just one (San Diego) has a significant negative effect on the home team’s offense.

At first glance, Coors Field seems to be in a league of its own when it comes to enhancing the home team’s offensive production. A common rule of thumb is that in a normally distributed data set, 99.7% of its values fall within three standard deviations of the mean. Any value outside of that range is considered an outlier. In this case, that range goes from -12.43% to 20.96%. Colorado, with its variation of 27.01%, falls way outside these limits, making it the only outlier of the group. This answers our first question, confirming that there’s no park that increases offense for the home team quite like Coors does. Which takes us to the second question: does it have a similar effect on visiting teams? Let’s crunch some numbers and see what they tell us.

The idea is to repeat the same process we used for answering the first question, only this time we’re going to use opponents OPS or OPS against, instead of the team’s own OPS. Basically, what we’re trying to do is compare how opponents’ offenses as a whole, change when they visit a particular park. In other words, and using Colorado as an example, we want to know how the league’s OPS against the Rockies is affected by playing at Coors Field as opposed to anywhere else.

Using the same methodology, here’s the opponents OPS change by park:

Park Change p-value Park Change p-value
COL 9.00% <0.01 WAS -4.28% 0.14
ARI 1.41% 0.18 MIN -4.37% 0.01
TEX 0.32% 0.43 LAA -4.53% 0.01
KC -0.13% 0.47 SEA -4.67% 0.14
BOS -0.62% 0.32 DET -4.76% 0.01
NYY -0.92% 0.27 ATL -4.76% 0.01
CIN -1.09% 0.35 TB -6.29% 0.01
PHI -1.86% 0.23 MIA -7.02% <0.01
TOR -1.95% 0.12 NYM -7.26% 0.01
CWS -2.05% 0.08 PIT -7.57% <0.01
CHC -2.33% 0.09 SF -7.60% <0.01
BAL -2.96% 0.04 OAK -8.34% <0.01
MIL -3.21% 0.07 STL -8.74% <0.01
CLE -3.58% 0.02 LAD -9.21% <0.01
HOU -3.85% 0.03 SD -11.79% <0.01

There are a couple of things to digest from of this table. First off, the fact that Colorado has the only park in which visiting hitters significantly increase their offensive production is pretty mind-blowing. It seems to me that we’ve been using the term “hitter’s park” way too lightly. Out of the 30 ballparks actively housing an MLB team, 19 have a statistically-significant negative effect on the visiting team’s offense. Just like in our first analysis, 10 of them can be considered “neutral”, with p-values above 0.10, and just one (of course, Coors Field) has a positive effect with a good degree of significance.

This seems to contradict the numbers showed in our first table. In fact, out of the 19 parks that enhanced offensive performance for the home team, 10 of them also have a negative effect on visiting hitters. How can this apparent contradiction be explained? Well, it probably has a lot to do with the all-encompassing concept that is Home Field Advantage. For whatever combination of reasons (familiarity with the park, sleeping in their own beds, having dinner with their families), playing at home seems to get the best out of most players. If you think of the visiting teams’ OPS as a pitching stat for the home team (which it is), then you can interpret the numbers in the second table as having 19 out of 30 parks with a positive effect on the home-team pitching staff, 10 being neutral, while just one of them having a negative effect. Coincidentally, that’s precisely a mirror image of the results we got when analyzing the first table.

Going back to the second question, does Coors Field have a greater impact on Rockies’ hitters than on the rest of the teams? The short answer is yes. The variation in OPS for Colorado players is 27.01%, while the equivalent for non-Rockies players is “just” 9.00%. So by just comparing these two values, it seems evident that the effect is in fact greater among Rockies’ hitters. The explanation could be again simply Home Field Advantage, but the difference is just too big. If we merge both tables in one, and consider the visiting hitters as a control group, then a simple subtraction should give us a rough estimate of the net effect of Home Field Advantage on home-team hitters.

Here’s that table. Red values were not considered in the subtraction since they were deemed non-significant.

Park Home Visiting Net Effect Park Home Visiting Net Effect
COL 27.01% 9.00% 18.01% NYM -2.69% -7.26% 7.26%
HOU 7.48% -3.85% 11.33% CWS 5.12% -2.05% 7.17%
PIT 3.45% -7.57% 11.02% BAL 4.10% -2.96% 7.05%
MIN 6.10% -4.37% 10.47% MIA 2.20% -7.02% 7.02%
TEX 10.44% 0.32% 10.44% NYY 6.86% -0.92% 6.86%
ARI 9.52% 1.41% 9.52% SD -5.46% -11.79% 6.33%
LAD -1.64% -9.21% 9.21% TB 1.22% -6.29% 6.29%
STL 2.30% -8.74% 8.74% CIN 6.00% -1.09% 6.00%
DET 3.92% -4.76% 8.68% TOR 5.85% -1.95% 5.85%
BOS 8.39% -0.62% 8.39% KC 4.76% -0.13% 4.76%
OAK 1.33% -8.34% 8.34% WAS 4.65% -4.28% 4.65%
MIL 4.86% -3.21% 8.06% PHI 4.55% -1.86% 4.55%
CHC 5.70% -2.33% 8.03% LAA 0.36% -4.53% 4.53%
SF 0.22% -7.60% 7.60% CLE 1.81% -3.58% 3.58%
ATL 2.61% -4.76% 7.37% SEA -3.11% -4.67% 0.00%

Coors Field sits comfortably at the top, way ahead of Minute Maid, the second park on the list. Applying the same criteria for outliers we used before, Colorado’s Net Effect of 18.01% is not within the range of three standard deviations around the mean (-1.60% , 16.74%), once again being the lone outlier. It doesn’t look like that this is simply a result of Home Field Advantage; it seems there’s something else. This brings up a new question, one for which I’m not sure I have a definite answer: Does Coors Field undermine the Rockies’ ability to have a healthy offense on the road?

Let’s go back for a moment to the 27% increase in OPS for Rockies’ hitters at home. That number could mean a huge spike in offensive production when they play at Coors Field or a massive collapse when they hit the road; it depends on how you see it. Colorado ranks dead last in the majors in OPS away from home in the same time span we’re studying, so either they have been the worse offensive team in two decades (which is certainly an option) or something is causing them to consistently under-perform on the road. Of course, it doesn’t help that almost half of their games away from Denver are played in places like San Diego, Los Angeles, and San Francisco. In fact, according to the numbers in the second table presented in this piece, Colorado’s division rivals have the toughest combination of parks for visiting hitters. The average drop-off in opponents OPS in NL West parks (excluding Coors Field) is -7.15%. The following table shows that value for every team in the majors (for the purpose of this exercise, Houston was considered an NL Central team).

Team

Average Change in division rivals’ parks

Team

Average Change in division rivals’ parks

COL -7.15% MIA -3.01%
CIN -5.14% SF -3.00%
ARI -4.90% NYM -2.95%
PHI -4.76% CLE -2.79%
WAS -4.76% LAA -2.78%
CHC -4.68% LAD -2.60%
MIL -4.50% MIN -2.60%
HOU -4.37% DET -2.50%
SEA -4.29% BOS -2.31%
TEX -4.29% NYY -2.31%
KC -3.69% TOR -2.31%
PIT -3.63% SD -1.95%
ATL -3.57% BAL -1.57%
STL -3.39% OAK -1.51%
CWS -3.18% TB -0.74%

This definitely helps explain, at least partially, the abnormal home/away splits that Rockies’ hitters have had historically. Not only do they play their home games in the biggest, if not the only true hitter’s park in the game, but they also play a big chunk of their road games in three of the toughest pitcher’s parks in MLB.

The last question remains unanswered; the thesis of a Coors Field Hangover effect is largely unproven. Still, there’s a good amount of circumstantial evidence that points to the existence of something like it.



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Juan Pablo is a Venezuelan Chemical Engineer who spends unhealthy amounts of time watching, reading and writing about baseball. You can also read him at: www.theimperfectgame.com

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Chris Walker
Member
Chris Walker

Excellent job. That last question is a big cliffhanger, but the lead up was stunning.

Baseball4ever
Member
Baseball4ever

After the 2014 season, I created a couple of stats that identify park factors in a totally different way.

1) the first stat answered a hypothetical question and that question was: IF every major league team could have a perfect season, winning all 162 games, going 162 and 0, how many runs would they need to win all those games by a single run apiece?

The answer for the Rockies was 938 runs in 2014. To put that in perspective, the average team needed only 660 to 680 runs a year. The Rockies were the worst. NL teams needed 37 runs less than the average AL team.

2) The second stat was how “slugfest games were each team a part of in a given year whether won or lost? The Rockies? 32 games, the most in MLB, 2014, the Twins were second with 30.

How did I define a slugfest? Where BOTH teams playing score at least 5 runs apiece. In the 32 games the Rockies were a part of an average of 16.5 runs per game were scored between both teams in each of the 32 contests.

So to put it mildly, Coors field park and its rarefied air sucks.

scotman144
Member

Great read. I wonder if one could do a study of pitchers that lose movement on their pitches season to season and try to assign a run value per unit increment of movement lost. If you could then calculate the average movement loss for a COL pitcher away vs home you may have a decent proxy measurement for the run value of ROX hitters seeing better movement in an away game vs. the same pitcher they’d see in a home game at Coors and vice versa.

Joe
Member
Joe

It is also hard for a pitcher who pitches a lot of games (and practices/throws bullpen sessions) at Coors to suddenly adjust to sea-level and have pinpoint accuracy to locate breaking balls and off-speed pitches. Yes, the ball moves more and is therefore harder to hit, but the pitcher still has to locate and throw strikes…I would like to see how effective Rockies pitchers are at throwing strikes home versus away.

scotman144
Member

Great point: tough to nail the low-outside corner with your slider if it has 6 inches of gloveside break at sea level and only 3-4 in Coors.

BaconBall
Guest
BaconBall

You write, “For whatever combination of reasons (familiarity with the park, sleeping in their own beds, having dinner with their families), playing at home seems to get the best out of most players.” You left out the most obvious one, which is “umpire bias.”

You write, “If you think of the visiting teams’ OPS as a pitching stat for the home team (which it is)…” This has been obvious since the very first season, 1993, when the Rocks pitching staff led the league in BABIP, allowing an average of .319. Second that year were the Reds at .305. The league average was .294.

Coorz Effect
Guest
Coorz Effect

Very interesting read. The only problem I see is the fact that your date range is too big…Coors Field today is a completely different park since they added the humidor after 2001. If you restricted the data to only post-humidor dates, I’m sure Coors is still the top of the list, just much less of an “outlier” than it appears here.

1908
Member
Member

Re: home field advantage – for 4 of the last 5 years hitters across MLB have had their lowest collective OPS in the 9th inning See, e.g. here:

http://www.baseball-reference.com/leagues/split.cgi?t=b&lg=MLB&year=2015#innng::18

My guess is that this trend is not new, at least since the advent of reliever hyper-specialization. The home team gets to avoid this Inning of Offensive Doom at least some of the time, while the road team never does. And the Rockies never have the advantage (if that’s the right word) of batting in the 9th on the road at Coors.

Not sure this helps explain some of the findings in the post, but seems like it might be relevant.