This presentation summarizes a thesis defense examining suitable relocation sites for the Tampa Bay Rays baseball stadium. The presentation introduces the background on the Rays' struggles with attendance despite on-field success. It then discusses the research gap in focusing more on stadium location rather than just economics. The methods section outlines a scoring system used to analyze targeted and non-targeted potential sites based on variables like travel time and population. The results found that a non-targeted site at the old Tampa Stadium location scored highest. The significance is that this research fills gaps in objectively studying stadium placement and identifies a repeatable method for quantifying suitable sites.

1. A presentation by
Carlos Osiris Martinez
to the
University of Southern California
Geographic Information Science and Technology Department
THESIS DEFENSE
RELOCATION BAY:
IDENTIFYING A SUITABLE SITE FOR THE TAMPA BAY RAYS

2. CONTENT
• Introduction
• Background
• Research Gap
• Methods
• Results
• Significance of Findings
• Questions

3. INTRODUCTION
• The Tampa Bay Rays arrived to the Tampa Bay area with
great fanfare
• Soon thereafter, average game attendance dwindled
• Team has revitalized itself and created a winning product
since 2008
• Unfortunately, winning on the field has not boosted revenue
• Current stadium location has been declared root of the
problem

4. BACKGROUND
• Stadium placement hasn’t always been a scientific process
• Early vs. Late 20th Century
• CBDs and Suburbs
• Golden Age of Capitalism
• Stadium design and functionality changes
• Single use vs. Multi-use
• Current Trends
• Downtown Revitalization
• Cost over location

5. BACKGROUND
• The Tampa Bay Rays are struggling
• Winners (on the field) and Losers (off the field)
• Solutions?
• Create a winning product
• Incentivize the fans
• Relocate stadium
• Relocate franchise

6. RESEARCH GAP
• Gap exists in stadium location research
• Most research focuses on the economics of stadiums rather than
location
• Public financing
• Financial impact after construction
• Economic factors cannot be unmarried from location
research
• Sports tourism
• Tax breaks/impact

7. METHODS:
TARGETED VS. NON-TARGETED SITES
• Targeted Sites
• Potential sties derived from Tampa Bay Times online database of
debated possible stadium sites
• Sites have been discussed anecdotally but have not been officially
identified as plausible relocation sites
• Non-Targeted Sites
• These sites have not been identified previously in any capacity.
• The sites are identified through the analysis of the Targeted sites

8. METHODS:
SITE SUITABILITY SCORING SYSTEM
• To determine site suitability, a Scoring System was
developed for this project
• Scoring System developed score through analysis of
possible sites referred against established variables and
subsequent parameters
• Time/Distance Variable
• Population Variable
• Critical Infrastructure Variable
• Parcel Variable

9. METHODS:
SITE SUITABILITY SCORING SYSTEM
• First, all Targeted sites were
analyzed using Time/Distance and
Population Variables
• Next, the Targeted sites were
analyzed using remaining Variables
and Parameters
• Finally, sites were ranked based on
scoring outcomes with top scoring
sites being focus of in-depth review
• Non-Targeted sites were analyzed
using this same method to
determine site score and rank.

10. METHODS:
VARIABLE AND PARAMETER ANALYSIS
• Traffic/Distance
• Network Analyst tool was used
analyzed road network to
establish drive time/distance
• < 30 Minutes is “ideal”
• 45 Minutes is “reasonable”
• > 60 Minutes is “unlikely to
attend”
• Population
• Spatial Analyst tool was used to
establish population density and
percentages for the region
• Ideal stadium site in area
where more than 80% of
the population resides.

11. METHODS:
VARIABLE AND PARAMETER ANALYSIS
• Critical Infrastructure
• Traffic
• 5 mile buffer
• Public Services
• 3 mile buffer
• Accommodations
• 2 mile buffer
• Recreation
• 1 mile buffer
• Parcels
• County/City Owned
• Fits Stadium
• Occupied
• Size in Acres (Not Scored)

12. METHODS:
PROCESS DIAGRAM

13. RESULTS
• Analysis began with study of Tropicana Field using established
methods for Targeted and Non-Targeted sites
• Acts as a ‘Control’ for analyzed site comparison
• The selected Targeted sites were analyzed and scored
according to the Scoring System
• Yankees Complex, Channelside Plaza, Carillon Area, Derby Lane, and
Florida State Fair Grounds
• Non-Targeted Sites Identified
• Tampa Stadium Site, Westshore Area, Channelside Area

14. RESULTS:
TIME/ DISTANCE AND POPULATION – TARGETED

15. RESULTS:
CRITICAL INFRASTRUCTURE – TARGETED

16. RESULTS:
PARCELS – TARGETED

17. RESULTS:
TOTAL SCORE – TARGETED SITES

18. RESULTS:
TIME/ DISTANCE AND POPULATION – NON-TARGETED

19. RESULTS:
CRITICAL INFRASTRUCTURE – NON-TARGETED

20. RESULTS:
PARCELS – NON-TARGETED

21. RESULTS:
TOTAL SCORE – NON-TARGETED SITES

22. RESULTS:
TARGETED VS. NON-TARGETED

23. RESULTS
• Final analysis indicates the highest scoring site is the Non-
Targeted site at Tampa Stadium
• Score: 94/100
• Yankees Complex and Channelside Plaza rank second and
third respectively
• Score: 88/100 and 85/100
• Tropicana Field scored second lowest overall score
• Score: 50.5/100

24. SIGNIFICANCE OF FINDINGS
• Results from Scoring System reinforce theory that
Tropicana Field is too far from population center
• Moving the stadium’s location to Hillsborough county
and within the city of Tampa will increase population
servicing by more than 31% for those traveling less
than 30 minutes and 12% for those within 45 minutes.

25. SIGNIFICANCE OF FINDINGS
• Results fill the void in existing stadium location
research by indicating that stadium placement within a
community is just as important as its financial impact
• Stadium location and stadium financing should be
treated as two independent subjects and researched
independently

26. SIGNIFICANCE OF FINDINGS
• Research identifies a repeatable method for
scientifically quantifying a possible stadium site
• Scoring System Parameters can be adjusted to
accommodate almost any location
• Possible connection between Scoring System results
and average attendance percentages

27. QUESTIONS?