Estimating Wind Effects at SunTrust Park

In what direction will the wind travel at SunTrust Park?

The Braves opened their brand SunTrust Park this season (reviewed here yesterday), and everyone has been talking about how the park may play in the long term. Their old stomping grounds, Turner Field, was not exactly a hitter-friendly haven, which may have been a response to Fulton-County Stadium, which was affectionately referred to as The Launching Pad due to its penchant for home runs. Will SunTrust be another pitcher’s park, another Launching Pad, or somewhere in between? Let’s take a look.

Differences Between SunTrust Park and Turner Field

When compared to Turner Field, SunTrust Park has a much more shallow right field fence, especially in the gap. There aren’t many differences between SunTrust and Turner in left or center field. The left field corner of SunTrust has a shorter six-foot fence and a slightly taller 8-foot-8 wall in center field, whereas Turner was 8-foot-4 all the way around.

SunTrust Park And Turner Field

Right field marks the largest change. The fence is between 10 and 15 feet more shallow in SunTrust. By my estimation, this amounts to roughly 3700 fewer square feet of play area. To put that into perspective, a doubles sized tennis court is roughly 2800 feet.

Of course, SunTrust also has a 16-foot fence from the right field corner up to the bullpen area in right center field. The top of this wall is constructed of exposed brick, similar to AT&T Park in San Francisco. The impact this wall may have on batted balls is certainly going to be a primary point of interest in the analysis to follow.

Finally, SunTrust has significantly less foul territory, roughly 4700 fewer square feet by my estimation. You should take this number with a grain of salt, but the reduction is very noticeable. The reduced area is roughly equal to two and a half tennis courts, or perhaps half a basketball court. Foul territory will not be part of this analysis, but it is something to keep in mind going forward.

The Model

For this analysis, I created a simple model of the stadium in SketchUp using satellite photography for scale and various other photographs and renderings for details. The model isn’t especially sophisticated, but it is a reasonably accurate depiction of the outer shape of the structure: left, center, and right field fences; primary and auxiliary scoreboards; Chop House restaurant; batter’s eye; outfield seating; bullpens; and the various wind barriers around the center field parameter.

I didn’t model the inner part of the stadium, including the seating areas behind home plate, down the lines, or the upper decks. This model isn’t perfect—it doesn’t have every last detail—but it should be accurate enough to get somewhat reliable results for the wind analysis. After all, we’re only interested in wind patterns that will change the flight of fly balls to the deep outfield and not as much pop-ups or things of that ilk.

Above the stadium there is a wind wall, presumably to help control how the wind curves around the top of the stadium. I did not include this in my model. I didn’t know the exact geometry of this structure, so I figured it may be better to exclude it from the analysis.

I also included three large pre-existing structures that are close enough to the park to influence wind conditions within the stadium.

Seasonal Variations

Weather varies considerably season to season, obviously, so I searched for a few good resources for seasonal temperature, humidity, and wind patterns for the Atlanta area. For the wind direction and speed information, I used Wind Climate Analyses for National Weather Service Stations in the Southeast, published by Westinghouse Savannah River Company for the U.S. Department of Energy. It is especially nice that this source uses evening wind direction and speed, since games most often occur during that time. For temperature and humidity data, I used Current Results, which is a curator of weather data around the country. All of the data for this analysis can be viewed in the attached data document.

3D simulations

For this analysis, I used Flow Design, a stand-alone program created by Autodesk to run basic wind tunnel simulations. I ran the simulations with 3.78 m/s (8.45 mph) wind speed, which is roughly average wind speed for the city of Atlanta. I repeated the analysis sixteen times, once for each of the sixteen points on a compass.

I would have liked to have varied wind velocities with these simulations, but they are exceptionally time consuming, taking my machine upward of five hours to complete each. However, with the conclusion of these simulations I have approximate wind direction and speed all along the stadium broken into 30 ft. x 30 ft. x 30 ft. cubes—roughly 2700 data points per simulation. This should be enough data to estimate how wind may impact fly balls.

Analysis of Simulations

I used a modified version of the Trajectory Calculator created by Alan Nathan for this analysis. The modifications include:

  • Corrected the X coordinate system to measure movement on that axis. This is the axis that runs from first to third base.
  • Wind speed and direction change with respect to field position and height according to the results of the simulations.
  • Added capability to produce results in large batches to save time.

Other than these three changes, the calculator is effectively identical to the one Alan Nathan created.

A Hardball Times Update
Goodbye for now.

I referenced a topologic map of Atlanta and found the location of the stadium has an elevation of 981 feet. I have seen other sources claim a 900-foot elevation, but I am siding with the map on this one. Either way, I’m not sure an 81-foot variance would make a large difference.

For all of my analysis, batted balls are assumed to have a backspin equal to cos(x)*2400 rpm and a side spin equal to sin(x)*2400 rpm, where x is the horizontal launch angle.

Spray Angles, Vertical Angles, Exit Velocities

I decided to use five horizontal trajectories (spray angles) for my analysis. You can see the trajectories marked by black lines below.


I also have decided to use five vertical launch angles: 15, 20, 25, 30, 35. A 15-degree launch angle roughly approximates a high line drive, 20 degrees a low line drive, 25 and 30 degrees are ideal fly balls that maximize distance, and 35 degrees is a high fly ball.

I used four exit velocities: 90, 95, 100, 105. This range should give a good cross-section for the higher value batted balls in the game.

Scaling Wind Speed

Although I couldn’t run the wind tunnel tests with varying wind speeds, I did scale the results of the testing with respect to the wind you would expect during each season. This isn’t perfect, since the wind may have different behaviors at higher and lower speeds, but I did make an attempt to correct for the varying speeds Atlanta experiences during the course of the year.

Wall Height

It isn’t enough to know if a ball travels far enough to reach the wall, we need to know if the ball is high enough to go over the wall, especially in right field, which has a 16-foot-high fence. So, not only have I calculated the distance of batted balls, but I have calculated their height as they cross the wall.

Averaging and Frequency

This analysis took lots of data from lots of sources, so the key here is combining it correctly. I took the relative frequencies of each event and used them to create weighted averages. For example, I know in summer wind blows from the west 9.5 percent of the time. And I know 7.6 percent of batted balls are hit between 20 and 25 vertical degrees. I used all of this information to form a weighted average to calculate home run rates for each launch angle, exit velocity, spray angle, and season.


SunTrust Park has rather large scoreboards in center field—above the batter eye—and left field. There are other smaller scoreboards scattered around the stadium, but these two are freestanding structures that impede airflow. When the wind blows in from center field, both of these scoreboards serve to hinder wind speed to much of the park while simultaneously creating a thin stream of air through the middle of the field. You can see this in the image below.

Simulated Wind From The Southeast

This street of air between the scoreboards should have some upward velocity. You can imagine waves crashing against rocks; the liquid is pushed up and around the barrier. In this case, much of the fastest-moving air should go up and over the stadium, although certainly some will enter the field of play, as well.

You can see vortices forming in both left and right field, along with a bunch of turbulent air around the Chop House restaurant. In left field, roughly speaking, these vortices blow out, while in right field they tend to blow towards center field. In right field, these vortices also hinder airflow that would otherwise spill onto the field from the Chop House area.

Right field doesn’t have a large scoreboard to break up wind, but it does have the Chop House. Wind coming in from this direction flows around the restaurant, creating a smaller stream of air that cuts across the field from right to left field. This stream of air creates vortices on the field level, as you can see in the image blow.

Simulated Wind From The Southwest

There are large vortices in right and center field as a result of this wind current bending around the Chop House. These vortices take up much of the area in the outfield, forcing the faster-moving air outside to go up and over the stadium rather than entering it and knocking down fly balls, similar to wind from the southeast.

Simulated Wind From The South

Whenever the wind blows in from center field, whether it is from dead center, the left or the right, the stadium design appears to mitigate the problems by creating a large amount of turbulent air in the outfield. This seems to cushion the playing area, limiting the impact of the wind on potential home run balls.

Home Run Rates with Respect to Spray Angle and Season

The seasonal effects include wind and direction, temperature, and humidity. We’re defining spring as March, April, and May, summer as June, July, and August, and autumn as September, October, and November. In summer, the home run rates increase, but not to all parts of the ballpark. in left center, home runs decreased ever so slightly, while right center remained steady. Down the lines, summer increased home run rates about about half a percent, with an increase to center field a bit smaller than that.

Estimated Home Run Rates Around The Field
Left Field Left Center Center Right Center Right Field
Total 13.0% 5.9% 2.4% 5.9% 14.2%
Spring 12.8% 6.0% 2.2% 5.9% 14.0%
Summer 13.3% 5.9% 2.6% 5.9% 14.5%
Autumn 12.7% 6.0% 2.1% 5.9% 14.0%

Please note that these home run rates are for all batted balls hit above 87 mph. If you include batted balls of all exit velocities, the numbers roughly cut in half. However, this and all analysis in this piece will assume an exit velocity of at least 87 mph.

Estimated SunTrust Park HR% VS Turner Field Actual HR%

Compared to Turner Field, SunTrust Park could see a 42 percent increase in home runs to left field, 55 percent increase to left center, 29 percent decrease to center field, seven percent decrease to right center, and a 67 percent increase to right field.

Overall Home Run Rates

Combining the various spray angles with respect to their frequency, I calculated an overall home run rate of 7.4 percent in SunTrust Park. In other words. 7.4 percent of balls hit above 87 miles per hour will, according to this analysis, become home runs.

This is a weird way to express home run rate, I admit, so you’re probably wondering how this relates to the rest of the league.

Home Run Rates In All MLB Parks
Camden Yards  218  2271  9.6%
Yankee Stadium  222  2433  9.1%
Great American Ball Park  197  2362  8.3%
Safeco Field  199  2389  8.3%
Miller Park  183  2216  8.2%
Minute Maid Park  184  2256  8.1%
Rogers Centre  211  2639  8.0%
Chase Field  181  2283  7.9%
Wrigley Field  178  2259  7.9%
Tropicana Field  182  2306  7.9%
Citizens Bank Park  179  2331  7.7%
Coors Field  200  2604  7.7%
Globe Life Park  195  2584  7.5%
Dodger Stadium  169  2257  7.5%
Citi Field  181  2425  7.5%
SunTrust Park 178* 2394* 7.4%*
Comerica Park  178  2446  7.3%
Guaranteed Rate Field  165  2280  7.2%
Target Field  183  2522  7.2%
MLB Average 5158 71803  7.2%
Petco Park  167  2351  7.1%
Angel Stadium of Anaheim  169  2386  7.1%
Progressive Field  179  2556  7.0%
Nationals Park  171  2450  7.0%
Fenway Park  169  2479  6.8%
Busch Stadium  147  2424  6.1%
Oakland Coliseum  140  2422  5.8%
Kauffman Stadium  145  2544  5.7%
PNC Park  131  2352  5.5%
Turner Field  120  2365  5.1%
Marlins Park  114  2306  4.9%
AT&T Park  108  2310  4.7%
* Estimated
On Batted Balls Hit Above 87mph

Turner Field was ranked 28th in MLB with a 5.1 percent home run rate on balls hit above 87 mph. The MLB average is 7.2 percent, and SunTrust, according to this analysis, should be closer to 7.4 percent, roughly on par with Citi Field, Comerica Park, Dodger Stadium, and Globe Life Park. During the course of a season, SunTrust Field could average 178 home runs on balls, up from 120 in Turner Field.

If this analysis turns out to be accurate, SunTrust Field may turn out to be a roughly average ballpark in terms of home runs, a significant improvement from Turner Field, and something I am sure Freddie Freeman is very excited to experience first hand.

Hits Added By The Tall Right Field Wall

The home run rate in right field is certainly suppressed by the taller wall, even though the distance to the wall is relatively short compared to many other ballparks. This isn’t all bad, though, since balls bouncing off the wall will, in most cases, be hits.

In the analysis, I counted balls that hit the wall between eight and 16 feet and found that roughly 1.9 percent of batted balls in right center will bounce off this section of the wall. This figure rises to 3.1 percent in right field.

BIP% Bouncing Off the 16-Foot Wall
Right Center Right Field
Total 1.9% 3.1%
Spring 2.3% 3.2%
Summer 1.5% 2.9%
Autumn 2.4% 3.2%
On Batted Balls Hit Above 87mph
Only balls that hit above the 8 foot mark on the wall

Some of these may be caught, but not an especially large number. The vast majority will land as singles and doubles, while some may even become triples. Given the wall is made of brick and was almost intentionally designed to create odd bounces and caroms, similar to AT&T Park, it might be fair to assume most of these balls will be doubles.

However, if you were to assume the wall itself were only eight feet tall, the home run rate in right field would leap to 15.3 percent and right center to 7.8 percent. You can see how these rates compare to other stadiums in the linked appendix.


SunTrust Park is a beautiful, well-designed ballpark every Braves fan should be proud to call home. My model is consistent with a much more hitter-friendly ballpark when compared to Turner Field, but not to the extent where it might be considered an extreme hitter’s park. It should be very fair for both hitters and pitchers, offering roughly league-average success rates with respect to exit velocity and launch angle.

The right field fence is tall, and the nature of its brick construction could add doubles, singles, and perhaps even triples in a reasonably unpredictable manner. On one hand, the ball may bounce very hard off the wall, limiting clear doubles to mere singles. Other times it may take unexpected bounces and turn doubles into triples. It is difficult to forecast exactly which scenario is more likely.

This study is not scientific but rather more for entertainment purposes. In a year or two, we can look back and see how well this model matches up to real-world results.

References & Resources

Andrew Perpetua is the creator of and, and plays around with Statcast data for fun. Follow him on Twitter @AndrewPerpetua.
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Brian L Cartwright
7 years ago

With the games through yesterday, I calculate a regressed HR park factor of 1.28 for LHB & 0.90 for RHB. It’s still a small sample but I wouldn’t be surprised if those stay above average for lefties & below average righties.

Assuming 2/3 of batters are right handed, that gives a weighted mean of 1.02, and multiplying that times the MLB average HR% of 7.2% quoted above gives 7.4%, exactly as predicted by the author.

Matt Butler
7 years ago

this is great work. Thanks so much

Dr Doom
7 years ago

You write, “This model isn’t perfect—it doesn’t have every last detail—but it should be accurate enough to get somewhat reliable results for the wind analysis.”

You qualify what you write with the word “somewhat.” Then you continue, “Above the stadium there is a wind wall, presumably to help control how the wind curves around the top of the stadium. I did not include this in my model. I didn’t know the exact geometry of this structure, so I figured it may be better to exclude it from the analysis.”

My god, man! You EXCLUDE the WIND WALL and have the AUDACITY to attempt a prediction as to what the WIND will do to the flight of a ball? Then you obtain wind patterns for the Atlanta area when the ballpark is NOT EVEN IN THE ATLANTA AREA!!!
Are you out of your mind? Why anyone in his right mind would publish something like this is way beyond my mind. Did you go to TrumPet university?

The only thing you wrote that may give us a clue as to whether or not the ballpark named after a bank will be a hitter’s, or pitcher’s, park is, “Finally, SunTrust has significantly less foul territory, roughly 4700 fewer square feet by my estimation.” Maybe you should have spent your time comparing Bank Park to the old Oakland Coliseum, where foul balls went to die…

7 years ago

What about the Omni and Comcast buildings? I would think that they would have significant effect on right and right-center, as both are substantially taller than the Chop House.

Woody Guthrie
7 years ago

You don’t need no weatherman

To know which way the wind blows

Alan Nathan
7 years ago

I’m curious as to how the Flow Design software works. I am thinking it is something like this: You specify wind speed and direction at some location far enough from the stadium so that the effect of the latter is small. Then you provide all the relevant dimensions/obstructions/etc. for the stadium. Then it generates the air flow (in 3D) inside the stadium. Is that essentially correct?

Regarding one of the previous comments, I do agree that the Wind Wall might be important. However, I also am of the view that solving complex problems such as this requires a staged approach. One doesn’t solve the most complicated version in the first step. One does a simplified version first, then adds layers of complexity. I think the approach used here by Andrew is an excellent first step. That’s just my view, for whatever it’s worth.

7 years ago

How many years did you use to calc. the “actual” HR rates? There’s going to be a lot of noise if it’s just one season…

Michael Bacon
7 years ago

While watching the Braves play the Mets at the new park in Marietta, Georgia, tonight, Brandon Phillips hit a scorcher to CF. Chip commented on how the ball carried to center as the cameraman showed the tunnel. Chip said something about the tunnel causing a jet stream toward CF and Tom Glavine commented about there being the same effect at the old Atlanta-Fulton County stadium. FreedieFree, as he is now known down South, followed with another long drive to CF that doubled in BP, who had also made it to second base with a double. No comment was made concerning Freeman’s drive. Yet another factor to put into your computer program…
Speaking of the number of years needed to calculate home run rates…can someone explain how it is possible that B-Ref shows different numbers for the new stadium when it comes to “multi-year” vs “one year.” It changes each game; today it shows 100-100 multi, and 103-103 for only this year. Since this year is all they have to go on, why is the multi-year different?

6 years ago

Is there a way to export numerical results from Flow Design or did you have to visually determine the wind speed and direction in each 30x30x30 cube from looking at the simulation?

6 years ago

I for one think this is very interesting analysis, and similar to something I’ve been contemplating for the Rockies. I think Dr. Nathan’s point about starting simple and adding complexity is a very good one, and the comment above deprecating your work should be ignored.

I do have a few questions. Could you describe the CFD a bit more? It sounds like it used a Cartesian grid; do you recall how many cells or what the dimensions were? Did it use a turbulence model, and if so which one? With respect to the trajectories, did you calculate C_D and C_L as a function of Reynolds number and spin rate, and did you use some sort of interpolation to calculate local wind velocity?

One aspect I’ve been interested in for the Rockies is how balls in play are affected by weather. At Coors, the lower air density causes balls to travel a little farther, which means fielders have farther to run. I think it would be interesting to look at a distribution of batted balls, and see how weather conditions affect the outcomes. You’d need some data about fielder range and positioning too.