MLB Needs to Expand; Here’s Where

by Chris Mitchell

Could Jersey City be the next MLB expansion location? (via Eden, Janine and Jim)

Nearly two decades have passed since Major League Baseball’s last expansion, when the Arizona Diamondbacks and Tampa Bay (Devil) Rays became baseball’s 29th and 30th teams. That may not seem like a particularly long time, but by historical standards, it’s a relative eternity.

In the 20th century, expansions happened all the time. Baseball averaged one multi-team expansion every 6.2 years between 1961 and 1998, which kept pace with U.S. population growth. Since then, expansions have stopped, but population growth has not. In 2017, there were 10.8 million U.S. citizens for each major league team. That was the most since 1960, the year before MLB expanded from 16 teams to 18.

All that population growth means the pool of potential fans has grown, especially since much of the growth has taken place in the country’s metropolitan regions, which happen to be where the baseball teams are located. Not only are there more people, but there are a lot more people who live within spitting distance of a major league team.

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Furthermore, baseball has expanded its footprint into foreign markets. While the majority of baseball players still come from the U.S., the player pool is growing increasingly diverse. The number of players born outside the traditional hotbeds — the U.S., Canada, the Dominican Republic and Venezuela — has grown 50 percent since 1998. Baseball’s talent pool is growing, yet the number of spots for talented players has remained fixed.

Rob Manfred understands the need for expansion. Since becoming commissioner in 2015, he’s said on several occasions that he intends to add more teams. In 2015, MLB compiled a list of potential relocation or expansion options, including Montreal, Charlotte, San Antonio, Portland, Las Vegas, Oklahoma City, New Jersey, Mexico City and Monterrey.

There are plenty of locales where a major league team would thrive, but there are plenty more where it wouldn’t. The following analysis attempts to identify the cities best- and worst-suited to support a big-league club based on city-specific data. I performed a similar exercise in 2015, but have realized my methodology was a little sloppy. Now that I’m older and wiser, I’m ready to do better.

Building a Model

This is about to get semi-technical. If you are not interested in reading about me doing math, feel free to skip to the “Winning” subtitle.

To identify ideal landing spots, I ran a regression analysis with each city-season since 2005 serving as a data point. I excluded Toronto since my model uses data from the U.S. government, which obviously isn’t available for Canada. I tested my model out of sample to ensure I was not overfitting the data. Rather than simply getting a best fit on my 29-team model, I also built all 29 possible 28-team models to ensure one or two teams (or cities) were not driving the correlation. When all the regression-induced dust settled, I was left with a total of 12 variables and an R2 of .76.

My dependent variable is an estimate of attendance revenue. Unfortunately, most major league teams do not release their financial information to the public. So to estimate each organization’s ticket revenue, I multiplied its per-game attendance by its average ticket price according to Team Marketing Report’s Fan Cost Index reports. It should be noted that this does not yield a perfect estimate of revenue, as the TMR’s data does not include luxury suites. This is not a huge problem for estimation purposes, as the errors are unlikely to be heavily correlated with any of the variables used in the model. On the downside, this precludes my model from being able to answer precise questions about revenue generation, such as how much revenue an extra 500,000 residents are worth.

The model includes several variables that help predict attendance revenue. Some relate to the city’s characteristics, which do all of the heavy lifting in the model’s application to unoccupied cities. Others relate to the city’s occupying team and were included as controls to accurately zero in on the city-specific characteristics.

Let’s start with the team-specific ones. These are centered appropriately in the model’s application to unoccupied cities and therefore have no direct bearing on the end result. But when looking backwards, they yield interesting insights that are worth digging into a bit.

Winning

It isn’t exactly news that winning attracts fans to the ballpark. Making the playoffs leads to a bump in attendance revenue that lasts for years. That bump is even bigger if a team wins the World Series. Interestingly, the playoff bump is bigger for teams that have been in the city for a long time, which is measured by my next variable.

Having a long history in a Metropolitan Statistical Area

Brand loyalty is a powerful force. Kids who grow up fans of a particular team often remain fans into their adult lives. However, it can take years for a sports franchise to become woven into the fabric of a city. Many baseball fans inherit their fandom from their parents, many of whom inherited it from their parents. So teams that have been around for several decades naturally have a leg up on their newer counterparts.

Even among teams over 50 years old, this trend holds strong, explaining why the oldest teams – such as the Cubs, Red Sox, Cardinals and Tigers – draw well every year. This jibes with a 2014 New York Times study that used Facebook data to estimate each ZIP code’s breakdown of fandom. Their data show that for many of the newer teams – such as the Nationals, Diamondbacks and Marlins – only about one-third of area residents are fans of the home team. For some of the very old teams – such as the Reds, Cardinals, Phillies and Tigers – it is over 75 percent.

Having at least one superstar player

The “Superstar Effect” is a real phenomenon in baseball, as teams with a star player (hitter or pitcher) gross more than one would otherwise expect. Specifically, the highest WAR total on a particular team helps predict attendance revenue. Mike Trout’s Angels are the most explicit example of this. Without the WAR variable, the Angels underperform the model literally every year until 2012 and then over-perform every year from 2012 through 2016. Albert Pujols, Carlos Beltran and Hanley Ramirez seemingly had similar impacts in their primes.

Next, the variables that predict which unoccupied cities have the most revenue-generating potential.

Large MSA population

Unsurprisingly, teams tend to attract more fans when more people live close to the stadium. Cities with large populations tend to draw very well, as do teams with a large number of people within five miles of their stadium. In other words, large and dense cities – such as New York, Chicago, Los Angeles and Boston – do best. Meanwhile, the Royals, Tigers, Rays, Cardinals, Indians and Reds are all hurt by a lack of nearby residents from which to draw.

High median family income in MSA

The sheer number of people isn’t the only driver, however, as those people’s relative financial wealth also matters. More disposable income means more income spent on baseball games. Pretty straightforward. The Giants, Athletics, Nationals and Red Sox all grade out well in this area, while the Marlins, Rays, Diamondbacks and Indians fare very poorly.

Driving distance from nearest major league team

Businesses don’t generally like competition, as it forces them to split a relatively fixed pool of potential customers. The same is true among major league teams, who compete for fans in regional markets. Having two teams in an MSA is not good for either team’s revenues. A team in a neighboring metropolis also adversely affects revenue, as it gives fans who live in-between the option of which team to support. The Mariners, Rockies, Braves and Diamondbacks benefit from their remoteness.

No NFL team in MSA

In addition to their regional baseball rivals, baseball teams must also contend with teams from other sports. Sadly, football — not baseball — is the most popular sport in America. Therefore, it makes sense that a local NFL team would eat into a baseball team’s market share. Baseball teams gross more when there is no football team in town to lure their fans away. Milwaukee and St. Louis currently benefit from football-less situations, as did Los Angeles until the Rams returned in 2016.

Minutes from downtown

Teams benefit from being located relatively close to the places people congregate. This helps explain why teams situated far outside of the MSA’s primary city, such as the Athletics and Angels, have had lackluster attendance figures in recent years. However, teams located too close to downtown also appear to be adversely impacted. Perhaps this has something to do with stadiums in city centers not being easily accessible. Recent examples of this phenomenon include the Pirates, Diamondbacks, Indians, Braves, Reds and Padres. The sweet spot is around 20 minutes from downtown — nearby, but not right on top of it. As a proxy for downtown, I used Google Maps’ default location point for each MSA’s central city.

Applying the Model

Those findings are interesting, but they are really just means to an end. That end, of course, is gauging how well an expansion (or re-location) team would draw if it were plopped down in an unoccupied city. Now for the fun part: applying the model every big city in America (including Puerto Rico!) to answer that question.

I applied this model to all 53 unoccupied cities (cities proper, not MSAs) with populations of at least 260,000 — the size of the Rays’ hometown of St. Petersburg, the smallest occupied city.

Below, you will find a graphical representation of the projected attendance revenues for all unoccupied cities along with actual revenues for all 30 major league teams.

Now, let’s look at the top 15 cities. Well, most of the top 15. Not included in this section are cities located outside the continental United States. More on them later.

No. 1: Jersey City, and No. 3: Newark, N.J.

A team in New Jersey may seem far-fetched at first blush, as there are two well-established teams right across the river in New York City. But there’s reason to think the greater New York area could support a third. New York City’s regional economy accounts for 6.2 percent of the nation’s population and generates 8.9 percent of its economic output. Simply put, there are a lot of people in and around the city and many of them have a lot of money to spend on baseball games. Even with two teams, New York has substantially more population per team than any other city.

Scott Boras came to the same conclusion about northern New Jersey, citing the regional TV market and the region’s fan base. However, he also rightly noted that the Yankees and Mets would likely use their territorial rights in an effort block a potential New Jersey team. A New Jersey team may not be terribly likely, but the greater New York City area could easily support one.

No. 2: San Jose

Thanks to Silicon Valley, many San Jose residents have exorbitantly high incomes. The median San Jose family earned over $122,000 in 2016, which was easily the highest among U.S. MSAs. As a large, densely-populated MSA with high incomes, San Jose has all the ingredients needed to support a major league team. It does get dinged for being just an hour outside of Oakland, but the city’s numerous benefits far outweigh that one downside. A baseball team in San Jose is not a novel idea: The Oakland Athletics considered relocating there a few years ago, but were blocked by the San Francisco Giants, who own San Jose’s territorial rights.

No. 4: Portland, Ore.

With over 2.4 million residents and a high median income, Portland almost certainly has an economy capable of supporting a team. It is also situated a good three hours from the Mariners, which would give a Portland-based team plenty of space to operate. Portland appears to be a serious contender, as it has a “legitimate ownership group” in place with the necessary financing for a potential stadium.

No. 6: Austin, and No. 9: San Antonio, Tex.

Texas already has two teams, but might be big enough for a third. Both Austin and San Antonio are well over two hours away from both Houston and Arlington, meaning a third Texas team would not necessarily be directly competing with its Texas counterparts. With over two million residents and high incomes, Austin would be a great fit for a baseball team.

In some ways, San Antonio seems like a superior choice to Austin. Not only is it further removed from the Astros and Rangers, but it is also the larger MSA. However, San Antonio’s low median family income — under $67,000 — does not bode well for its revenue-generating potential.

No. 7: Raleigh, N.C.

Raleigh’s biggest strength is its distance from existing major league teams. The closest teams — the Nationals, Orioles and Braves — are all over four hours away. Raleigh is not a terribly large MSA, but it has the second largest population and highest median family income in the untapped Carolinas region.

No. 8: Las Vegas, Nev.

Las Vegas’ largest advantage is that it is situated comfortably far from the Diamondbacks and all of the California teams. However, with low incomes and an NFL team in the works, Vegas also has some forces working against it. The data suggest Vegas might be large enough and detached enough to support both a football team and a baseball team, but it is no slam dunk.

No. 10: Sacramento, Calif.

Sacramento MSA is a bustling metropolis with 2.3 million residents and relatively high incomes. In a vacuum, that would make for a fine landing spot for a team. Sacramento doesn’t exist in a vacuum, however; it exists less than two hours northeast of Oakland, which weakens its case.

No, 11 Nashville, Tenn.

Nashville’s case closely mirrors Raleigh’s. Though it isn’t a particularly large MSA, Nashville benefits from being one of the largest cities from an untapped region — in this case, Tennessee and Kentucky. Although Nashville is a larger city than Raleigh, it ranks lower because its resident’s incomes are significantly more modest.

No. 12: Omaha, Neb.

Located three hours north of Kansas City, the Omaha area is a relatively unpenetrated market. The Omaha MSA also has a high median family income — over $81,000 in 2016. However, with less than a  million residents, Omaha’s population is over 40 percent smaller than all currently occupied MSAs. If Omaha had three times as many people, it would fall right behind Austin.

No. 13: Columbus, Ohio

With over 2 million residents, Columbus is much larger than many of the MSAs ranked above it. However, those residents’ incomes are comparatively low. The fact that the Cincinnati Reds are less than two hours away also does not help Columbus’ case.

No. 14: Albuquerque, N.M.

Located in the middle of spacious New Mexico, Albuquerque is nearly seven hours from the nearest team in Phoenix. That is about all Albuquerque has going for it, however. With less than a million residents and a median family income under $62,000, Albuquerque’s economy pales in comparison to other cities in the top-15. Though it is hundreds of miles from its nearest competitors, Albuquerque may not have enough going on to support a team.

No. 15: Charlotte, N.C.

Charlotte cracks the top-15 simply by being a large city that is far from existing teams. However, Charlotte does not do well in the density department, as relatively few of those people live within a five-mile radius of Charlotte proper. The presence of an NFL team — the Carolina Panthers — also takes a substantial bite out of the city’s revenue-generating potential. Despite having a large population with decent incomes, Charlotte might be too sprawling a city to support both a baseball team and a football team.

Cities that are too close to an existing major league team

These 15 cities do not project to draw many fans, largely because they are situated less than 90 minutes from an existing team. These cities all have their merits, and some would be good expansion candidates if only they existed elsewhere in the country. But their proximity to an existing team outweighs their other strengths.

  • Mesa, Ariz.
  • Irvine, Calif.
  • Long Beach, Calif.
  • Santa Ana, Calif.
  • Riverside, Calif.
  • Chula Vista, Calif.
  • Stockton, Calif.
  • Aurora, Colo.
  • Colorado Springs, Colo.
  • Tampa, Fla.*
  • St. Paul, Minn.
  • Toledo, Ohio
  • Dallas, Texas
  • Fort Worth, Texas
  • Plano, Texas

Major cities that don’t grade out well

Below are the remaining MSAs with over 1.5 million residents – roughly the size of Milwaukee, the smallest occupied MSA. I also included Oklahoma City (1.37 million residents) since it appeared on MLB’s list of candidates. Although these cities are relatively large and are at least an hour and a half from every existing team, they still do not grade out particularly well.

No. 16: Oklahoma City, Okla.

Aside from being far away from existing teams, Oklahoma City does not check any of my model’s boxes (aside from not having a NFL team). As a small MSA with very low incomes, it is not at all clear that OKC has enough disposable income sloshing around to support a big-league team.

No. 20: Virginia Beach, Va.

Although it is relatively far from existing team, my model projects Virginia Beach for middling revenue figures due to its small, sprawling population and modest incomes.

No. 25: Orlando, Fla.

With 2.44 million residents, Orlando is one of the nation’s largest MSAs without a team. However, it also has the second lowest median family income of any MSA with over 1.1 million people (trailing only Miami). It is also hurt by the Rays, who are located less than two hours southwest.

No. 29: Indianapolis, Ind.

Similar to Virginia Beach and Orlando, Indianapolis rates very poorly despite its size. The math suggests a sprawling city with barely two million residents and modest incomes would not be able to accommodate both a football team and a baseball team. It also does not help that Indianapolis is located less than two hours from Cincinnati.

Cities outside the continental United States

I left these for last because I am skeptical of how the model handles these cities. My model was built  using data exclusively on cities within the continental United States. Since none of the cities in my sample looked much like Honolulu, Anchorage or San Juan, we cannot know how well relationships established for continental U.S. cities will hold up. For one, since these cities are largely surrounded by water, they do not have much of a potential fan base beyond their regional economies. And most glaringly, the variable measuring the driving distance from the nearest team does not apply here for obvious reasons. For these cities, I set this variable to the flight distance to the nearest major league team, but that decision was admittedly arbitrary.

No. 5: Honolulu, Hawaii

In addition to being quite far from existing teams, Honolulu boasts a median family income over $93,000.  Honolulu is chock-full of well-off, baseball-starved residents.  The only question is whether there are enough of them to support a big league club,  Honolulu’s population is a lean 993,000, while  the smallest currently occupied MSA — Milwaukee — has over 1.5 times that amount.

Furthermore, a team in Hawaii would come with a slew of travel-related complications. Chartering flights to and from Honolulu for every road trip would presumably cost a fortune, while the travel schedule would be daunting for players. Rob Manfred has said he would consider cities with “realistic travel distances… outside of the 48 contiguous states.” Honolulu does not appear to meet the former condition.

No. 17: Anchorage, Alaska

Everything written above about Honolulu also applies to Anchorage, including the travel complications. However, Anchorage is even smaller than Honolulu. With just 403,000 residents, it is roughly one-fourth the size of Milwaukee. Furthermore, although I found no convincing relationship between climate and attendance revenue, Anchorage’s subarctic climate might be an exception to that rule.

No. 44: San Juan, P.R.

Proximity to other teams may not a problem for Puerto Rico, but its low incomes likely are. San Juan’s median family income was just $26,607 in 2016 — less than half of Miami’s and one-fifth of San Jose’s. Nearly 40 percent of San Juan’s residents live below the poverty line. The data suggest a team in an MSA with so little disposable income would not draw a respectable number of fans.

However, since the model was built using cities with $60,000+ in median income, it is hard to predict what would happen with incomes less than half of that amount. The relationship between median income and revenue might break down at a certain point. For instance, the model’s underlying assumption that major league stadiums sell a lot of expensive seats and accommodate around 40,000 fans may not necessarily apply. A team in San Juan might charge $10 per ticket and fill a college football-style stadium that seats 100,000, which might generate more respectable revenue totals. The same logic would likely apply to Mexico City, Monterrey, or any other cities in Mexico.

Canadian cities

My model is built on U.S. data, much of which come from the U.S. government. Across all cities, these  numbers come from the same sources, cover the same time periods, and are collected and compiled using the same methodologies. This makes it relatively straightforward to compare U.S. cities, since the data are apples-to-apples. Unfortunately, this also renders my model near-useless outside of U.S. borders. While other countries have their own data sources, they are not necessarily comparable to the ones I gathered for U.S. cities.

That being said, Canada has a similar standard of living to the United States and the government publishes similar data. For these reasons, I felt semi-comfortable applying my model to the two Canadian cities with at least 1.5 million residents —but not comfortable enough to directly compare them to U.S. cities. While I can’t analyze these cities as rigorously as I would like, I can make some informed comments using the lessons gleaned from my analysis.

No. 1: Vancouver

Although its population is just 60 percent of Montreal’s, Vancouver actually appears to be a better fit than Montreal in some ways. Vancouver is a denser city and has $8,000 USD on Montreal’s median family income. However, Vancouver is relatively close to an existing team: the Seattle Mariners. Vancouver to Seattle is quite a trek, but is not as far as Montreal to Toronto. However, if MLB ultimately decides to add a team in Portland, adding another Vancouver would not make much sense – and would not be particularly fair to the Seattle Mariners.

No. 2: Montreal

Although Montreal technically ranks behind Vancouver, the cities are basically tied – the projected difference in revenue is just over $1,000 per game. With 4.1 million residents, Montreal is easily Canada’s largest city outside of Toronto. Pair that with its distance from existing teams and population density, and Montreal seems like a solid choice. The model suggests Montreal may be ready to house a baseball team again.

Concluding thoughts

Good attendance is obviously a prerequisite for a successful baseball team, but by no means should it be the only yardstick used in location decisions. For example, my model almost exclusively favors cities with high incomes, but that shouldn’t discourage MLB from considering locations like Puerto Rico or Mexico, where incomes are considerably lower. A team in, say, San Juan or Mexico City might not do well by the measure of attendance revenue, but would obviously go a long way toward expanding baseball’s reach. For MLB, the benefit of establishing itself in a new country and diversifying its fan base might outweigh the forgone ticket revenue from one stadium.

Other factors should be considered, but a city’s ability to generate attendance revenue should play a large role in the decision-making process. Ticket sales make up roughly 30 percent of teams’ revenue streams, so if people aren’t coming to the ballpark, the team suffers — both on and off the field. The last thing baseball needs is another Rays-like situation, where a team struggles to sell 20,000 dirt-cheap tickets per game, even when the team is winning.

Expansion is coming. It’s a matter of when, rather than if. Rob Manfred and company should consider their decision carefully, as there are several cities — including a few very large ones — that may not have the right mix of people and geographic remoteness to support a team. A city’s ability to generate attendance shouldn’t be the only factor taken into consideration, but it should be one of the major ones.

References & Resources


Chris works in economic development by day, but spends most of his nights thinking about baseball. He writes for Pinstripe Pundits, FanGraphs and The Hardball Times. He's also on the twitter machine: @_chris_mitchell None of the views expressed in his articles reflect those of his daytime employer.