Park factors can play a huge role in the fortunes of a baseball team, especially over the course of a long season.

The same impact plays out in fantasy baseball, as well.

However, the nature of that impact depends on a variety of factors. In designing our game, we acknowledge two of the biggest: ballparks are constantly changing, and there is no such thing as an absolute park factor.

Accuracy in Park Factors

To ensure as much accuracy as possible, we limited the number of historical parks using two criteria.

First, we only selected ballparks where we could find a five-year period where the park’s physical dimensions did not change. For fun, we also tried to find five-year periods where the home team did well or something interesting happened.

We did not include any historical park that did not have any five-year period without changes during service as a Major League Ballpark – with one exception. We included Parc Jarry, the home of the Montreal Expos from 1969 to 1976, because we knew fanatical Expos fans would be upset if it wasn’t there! In the case of Parc Jarry, we used a three-year period where the physical dimensions did not change.

In the case of current parks, we update every year to reflect the most recent five-year period. Our goal is to always keep the modern parks updated with the latest changes, and to add any new ballparks.

The Effect of Park Factors

One of the great aspects of baseball is the unique design for each park. Each of these designs has a profound impact on the games played within them.

For example, small parks lead to more home runs. Astroturf tends to increase the number of singles as balls pick up speed when they hit off the field. Small foul ball areas lead to better batting averages, as fewer foul balls are caught for an out, giving batters extra pitches to hit.

Some of the park factors that have the biggest impact include:

  • Size and dimensions of the playing field
  • Elevation of the ballpark above sea level
  • Height of the fences
  • Shape of the fences
  • Foul territory size
  • Quality of the playing field
  • Hitting background

Park Factors in the Game

In the game, we give you five measurements – the ones you see in ballparks along the outfield fence. These include:

  • Distance down the left field foul line
  • Distance down the right field foul line
  • Distance to dead center
  • Distances down the power alleys (halfway between the foul lines and center field)

We also offer information on the height of the fences, as many ballparks have different fence shapes and heights.

We also include a numerical value for park factors in relationship to other parks in the league. A park factor of 100 is neutral, meaning the park produced the average number of a particular kind of offense. For example, a park factor of 120 for home runs means that batters in that park hit 20% more home runs than the average park within the league.

That last part is important to remember. Park factors must be considered within the context of how they were created. For example, if changes are made to other parks in your league, the number will change. Also, if changes are made to the game – such as juicing the ball or putting an emphasis on speed-and-defense players rather than sluggers in your lineups – the number can also change.

Historical Park Factors

The statistics from certain historical periods also play a role. For example, National League hitters had few home runs between 1915 and 1919. That means the larger amount of home runs hit in the Baker Bowl in Philadelphia gives it a higher park factor.

On the flip slide, a lot of home runs were hit in the National League between 2001 and 2005, meaning that the number of home runs hit in Coors Field in Colorado – a home run heaven if there ever was one – do not translate into quite as high of a park factor.

All the above explains what we mean when we say there are no absolute park factors. That’s why it’s important for players to analyze the actual dimensions and location of the park, not just look at the park factor number.

Impact on Your League

Park factors, as mentioned above, also are relative to your league. If everyone chooses Coors Field for their team, then the advantage in home runs is negated. If one player chose Dodgers Stadium, then the park factor for Coors Field would jump for home runs. It’s all relative.

At one point, we considered using a plus/minus system for park factors. Here’s an example of how that would have worked.

Our home run factor for 1915-19 Baker Bowl is 227, meaning that the park increased homers by 127% relative to the other parks of that time. Because homers were relatively scarce in those days, it only took about 27 extra homers per season to produce such a high home run factor. In today’s game, when the average park yields about 175 homers per season, 27 extra homers translates to only a 15% increase in homers.

Our home run factor for 2001-05 US Cellular Field, home of the Chicago White Sox, is 130. In today’s game, this relatively modest park factor represents about 55 extra homers per year. In the 1915-19 environment, when the average park yielded about 20 homers per year, an increase of 55 homers represents an increase of 275%.

Does it make sense that the Baker Bowl would not rank among the top home run parks if it was dropped into the 2005 AL? Does it make sense that US Cellular Field would have more than double the impact of the Baker Bowl if it was transported across time to the deadball era?

It’s hard to say for sure, but these results don’t feel right.

Changes in Baseball

Part of the reason the results from the above example didn’t feel right is because of the changes in baseball over the past 90 years.

In today’s game, the ball is livelier. Parks are a little smaller. Fences are a little lower, but not by as much as you might think. Before 1920, pitchers could manipulate the ball with spit, tobacco juice, and other techniques. Obviously, that’s no longer the case.

Also, the strike zone, mound height and other rules have changed. Teams now place more value on power than speed and defense, so there are more hitters who can take advantage of a favorable environment. The designated hitter rule reduces the number of lost at-bats.

Some of the increase in homers and the decrease in triples can be attributed to the changes in the parks over the past 90 years. But parks are only smaller by about 4% and fences are only a little lower on average. These park changes cannot explain the 700% increase in home run rates and the 60% decrease in triples rates from the 1910s to the 2000s. Because there are so many other factors besides the parks that have driven these major changes in the game, it’s hard to imagine that a simple plus/minus system would give the right answer.

Difference in Eras

Diamond Mind Online customers play games in different eras, and there’s no single set of park factors that will be right for every era.

In a league based in the deadball era, a park factor of 227 for the Baker Bowl is correct. It will add the 25-30 homers per season you’d expect to see. In a league based in the 1990s, a park factor of 227 would dramatically overstate the impact of that park.

Similarly, US Cellular’s home run factor of 130 is the right number for the 2000s, and the wrong number for the deadball era.

One possible approach is to translate all park factors into a more neutral environment. In that case, the Baker Bowl might end up with a homer factor of 150. That would moderate the extreme home run rates that would result when the Baker Bowl is used in the Home Run Era, but it would significantly understate the impact of that park whenever it is used in a league based on the deadball era.

In other words, changing the park factors would eliminate extremes but make them wrong in most any environment.

The better answer was to create a system where the park factors can be adapted to the era in which they are going to be used. Our simulation knows the range of years for which the park was rated, and it knows the range of years for which the era was rated. Using this information, it can decide whether the park factors need to be adjusted.

If the 1915-19 Baker Bowl is used in a deadball era league, the simulation can recognize that nothing needs to change. But if that park is being used in a 1990s era, it can dynamically change the park factors to reflect the differences between those eras.

How It Works

Taking that approach, our system recognizes that in eras where certain events are rare, park factors can have a larger spread around the norm.

Examples would include homers hit in the deadball era and triples hit in the modern game. Today, when home runs are common, it’s rare to see a home run factor above 140 or below 60. Triples are scarce, however, so those factors can range from 40 to 300. The opposite was true in the deadball era when homers were rare and triples common.

An important dynamic adjustment we can make is increase or decrease the spread around 100 based on a comparison of the two eras – the one from which the park was created, and one being used in your league.

If the Baker Bowl is used in the 1990s, we might dynamically reduce the home run factor from 227 to 150. The homer factor for US Cellular might rise from 130 to 175 when that park is used in the deadball era. (These numbers are hypothetical, by the way, just meant to illustrate the principle).

That’s the general idea. Instead of creating a single set of park factors that can survive era changes without creating extreme results, the park factors would continue to reflect the era in which they were created. When games are played in the same era, they can be used as is. When games are played in another era, the simulation will dynamically change them to reflect the differences between the two eras.

How the Math Works

You can skip over this part if you already get it, but we wanted to provide an example of how the math works in a specific case.

In Boston Red Sox home games in 2003, the Sox and their opponents hit 156 home runs in 5,010 at bats, for a frequency of .0311 HR/AB. (You have to exclude interleague games, which really can make sabermetricians’ lives miserable.)

In Red Sox away games, the Sox and their opponents hit 172 dingers in 5,094 ABs, which comes out to .0338 HR/AB. You divide .0311 by .0338, and the resulting number, 92, is the HR factor for Fenway Park in 2003.

A park factor of 92 means that it was 8% tougher to hit a home run in Fenway Park that year than it was in the other American League parks. However, when you break these numbers down further, Fenway has a different HR factor for right-handed batters than for left-handed batters, as most of you know.

We do the same sort of thing for all other categories as well.

Just one more thing! For modern parks, we have the data to give you information about how left-handed and right-handed hitters do. We don’t have that for some of the historical parks, so their LH and RH breakdown are pretty much the same, unless we have some additional information about the park.

We are getting more statistical data all the time and will add that information as we get it.

We hope you enjoy all the game and the different parks – give ‘em all a whirl!