GIS Assistance in Choosing Locations for New Sports Teams

Goals To examine the layout of current stadiums for the big four sports: MLB: Major League Baseball NBA: National Basketball Association NFL: National Football League NHL: National Hockey League To use GIS to choose locations for new teams in case of league expansion

Data Collection Google Earth used to locate latitude/longitude pairs for stadiums ESRI provided shapefiles of Census tracts (by state) and demographic data for each tract ESRI data had to be joined and appended, and tract identifier numbers had to be reformatted Census Bureau Summary File 3 data for per capita income for all Census tracts “Geo within geo” tool was helpful but downloading data was still very repetitive and time consuming

Game Plan Each Census tract was joined to a sports team based on the shortest distance from an edge of the tract to the stadium Some sports teams share stadiums; in that case, the teams were combined into one entity e.g., Clippers and Lakers, Jets and Giants

Calculations To properly assess the value of a given sports franchise, several data points were calculated: Total population Total annual wealth of population Per capita income of population Average distance of population from stadium Average distance of wealth from stadium Maximum distance in population group from stadium Percentage of fans in the same state as the stadium

Projection Equidistant projection used for accuracy of distance calculations: Map Projection Name: Equidistant Conic Standard Parallel: 33.000000 Standard Parallel: 45.000000 Longitude of Central Meridian: -96.000000 Latitude of Projection Origin: 39.000000

Scope of Data Calculations made only with contiguous U.S. data Alaska and Hawaii radically throw off distance calculations Maximum Distance from Census Tract to Closest Stadium AT&T Park (San Francisco Giants) Safeco Field (Seattle Mariners) All 50 States 5,060 km 5,223 km Lower 48 States 535 km 998 km

Conic Projection of MLB Stadiums

Fan Base Maps: MLB

Fan Base Maps: NBA

Fan Base Maps: NFL

Fan Base Maps: NHL

Calculation Caveats Assumption that people in any given Census tract will root for the team located closest to that tract is not always true e.g., during Michael Jordan’s reign, Chicago Bulls fans were found all over the U.S., not just near Chicago Sometimes driving distances are much greater than “as the crow flies” distance calculations Cities with multiple teams Missing information about Canada

MLB Map Detail

Calculations Data available: 2000 Census population for tracts 2000 Census per capita income for tracts Total money = population * per capita income Population distance = sum (population * distance) / total population Total money distance = sum (total money * distance) / total money

Sample Calculations Table: MLB

Calculation: Furthest Tract Calculation of how far the fan base spreads

MLB Extents

MLB Extents (Detail) (Note gap in Montana Census tracts)

Calculation: In-State Fan Base (1) Percentage of fans who are part of a fan base that live in the same state as the stadium Several problems with this calculation, e.g.: Some New York teams play in New Jersey Count Washington, DC as a state? Missing Canada data

Calculation: In-State Fan Base (2) Not counting Washington, DC teams:

MLB In-State Fan Base

MLB In-State Fan Base (Detail)

Calculation: Total Population Total population indicates the size of a team’s potential fan base Excluding Canadian teams and halving population totals for teams that share a stadium:

NBA Total Population

Calculation: Total Money Total money indicates the wealth of a team’s potential fan base Ranks match those of total population except for the NFL San Francisco 49ers have the highest per capita income in the league ($32,610), so despite having the smallest fan base, they are ranked third from the bottom in total wealth (in front of the Green Bay Packers and the Jacksonville Jaguars)

NBA Total Money

Calculation: Population and Total Money Distances The difference between the average distance of a fan to the stadium and the average distance of wealth to the stadium indicates how wealth is distributed around the stadium’s host city

Per Capita Income by Census Tract

Denver Broncos (NFL) Population distance: 326 km Wealth distance: 287 km

Synthesizing the Data (1) A useful map combines all sports teams of the four major leagues and shows how close Census tracts are to any team Gives a geographic sense of what areas of the country are lacking representative teams

Census Tract Distance to Major Sports Teams (Darker Green Indicates Further Distance)

Least Representative Census Tract Tract 380539624 (population 1,589) is the furthest from any sports team, Watford City, ND is 828 km from the Minnesota Timberwolves

Synthesizing the Data (2) One way to locate where a new stadium should be located (for the NFL): Plot all major cities and towns and then remove those that are within 100 km of a current stadium 100 km is an arbitrary number but stadiums should not be placed too close together (though the Washington Redskins and Baltimore Ravens play 46 km from each other)

U.S. Cities with 100 km NFL Stadium Radii Removed

Synthesizing the Data (3) Create 40 km buffers around each city point Calculate the total population within the buffer 40 km is an arbitrary number but could serve as the size of a city large enough to host a sports team

U.S. City 40 km Buffers

Synthesizing the Data (4) By plotting only buffers that meet a given criterion, possible locations for a sports team can be determined

Metropolitan Areas with a Population Greater than 500,000 without an NFL Team

Metropolitan Areas with a Population Greater than 1,000,000 without an NFL Team Portland Milwaukee Columbus Los Angeles Virginia Beach San Antonio

Final Analysis for Metropolitan Areas with a Population Over 1,000,000 A table with statistics shows that Los Angeles is easily the best choice for a new football team Further analysis could plot how fan base distributions change with the addition of a team to Los Angeles or other cities