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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

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GIS Assistance in Choosing Locations for New Sports Teams


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    Presentation Transcript
    1. GIS Assistance in Choosing Locations for New Sports Teams

    2. 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

    3. 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

    4. 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

    5. 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

    6. 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

    7. Scope of Data • Calculations made only with contiguous U.S. data • Alaska and Hawaii radically throw off distance calculations

    8. Conic Projection of MLB Stadiums

    9. Fan Base Maps: MLB

    10. Fan Base Maps: NBA

    11. Fan Base Maps: NFL

    12. Fan Base Maps: NHL

    13. 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

    14. MLB Map Detail

    15. 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

    16. Sample Calculations Table: MLB

    17. Calculation: Furthest Tract • Calculation of how far the fan base spreads

    18. MLB Extents

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

    20. 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

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

    22. MLB In-State Fan Base

    23. MLB In-StateFan Base (Detail)

    24. 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:

    25. NBA Total Population

    26. 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)

    27. NBA Total Money

    28. Calculation: Populationand 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

    29. Per Capita Income by Census Tract

    30. Denver Broncos (NFL)Population distance: 326 kmWealth distance: 287 km

    31. 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

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

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

    34. 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)

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

    36. 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

    37. U.S. City 40 km Buffers

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

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

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

    41. 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