MLS R Presentation

14
Predicting the Future of MLS Locations Trey Belew, Brian Moore, James Moore, and Mike Oczypok

Transcript of MLS R Presentation

Page 1: MLS R Presentation

Predicting the Future of MLS LocationsTrey Belew, Brian Moore,

James Moore, and Mike Oczypok

Page 2: MLS R Presentation

Prediction

Current major US sports markets will end up as finalists

Our Guess:Phoenix

San Antonio

Austin

Oklahoma City

St. Louis

Memphis

Page 3: MLS R Presentation

Methodology

DataFrom: Census, American Community Survey, Wikipedia, Google

Used DataPopulation, Income, CBSA Codes, Lat/Lon, Team Locations

WhyPopulation and Income main predictors for expansion

Page 4: MLS R Presentation

Methodology Continued

OutliersCalculated outliers for MHI, MFI, PCI, and Total Population in order to

filterdown list of citiesFormula: Mean - 1.5*standard deviation

SiteScoreWeighted table of MHI, MFI, PCI, and Total PopulationEach factor given equal weight of 0.25

Page 5: MLS R Presentation

Current MLS CitiesCurrent MLS Cities

Page 6: MLS R Presentation
Page 7: MLS R Presentation

Predicting Future MLS Cities

Page 8: MLS R Presentation

Predicting Future MLS Cities

Notable Expansion CitiesPhoenix, Detroit, St. Louis

Increase Geographic ExposureMore teams in:Southeast, Midwest, and

Southwest

Page 9: MLS R Presentation

Comparing Currentand Expansion CitiesTakeaways

Every metro area with a Top 10 site

score already has a teamNYC and LA have two

Several areas suffer from alreadyhaving teams in the state

San Diego, Pittsburgh, San Antonio

Page 10: MLS R Presentation

Looking Back and Moving ForwardPrediction Limitations

Some expansion cities are too close to current cities to be feasible options forexpansion

Qualitative considerations such as between East and West divisions

Improving Future ModelUse CBSA Codes to filter out cities within a

certainrange of each other

Page 11: MLS R Presentation

Looking Back and Moving ForwardPrediction Limitations

Some expansion cities are too close to current cities to be feasible options forexpansion

Qualitative considerations such as between East and West divisions

Improving Future ModelUse CBSA Codes to filter out cities within a

certainrange of each other

Page 12: MLS R Presentation

Wrapping UpConclusion

Further expansion into Midwest and

Southwest

Page 13: MLS R Presentation

Source Data

Populations, Age, Gender, and Race BreakdownsProfile of General Population and Housing Characteristics: 2010 - U.S. Census

Income and Insurance InfoSelected Economic Characteristics - 2014 American Community Survey1-Year Estimates

MLS CitiesWikipedia.com

Latitude and LongitudeGoogle.com

Page 14: MLS R Presentation

Questions?