Unlocking Critical Program and Market Details with Sports Data Analysis

Estimated reading time: 6 minutes, 41 seconds.

By Jack Hogan

From feasibility studies and pro formas to building information models and cost estimates, there’s no shortage of data to help guide the sports facility development process. While this information provides independent snapshots of a prospective sports venue project, it often remains siloed and narrowed in scope. What’s more, the process for aggregating data throughout the venue planning stages can be cumbersome, often leaving behind value-added insights and general recommendations.

Connecting the "Data Dots"

Historically, customers would engage a market consultant at the earliest stages of the project to produce a feasibility study, which can vary in quality and consistency depending on the consultancy, project type, and location. Findings might include intelligence about a specific market, communicate survey results of fanbases or stakeholders, and touch upon similar facility projects or general sports facility trends. Broad recommendations might be given around seating capacities and type of premium offerings and amenities, but often exclude critical data around implementation costs, comparable market performance from an entertainment and construction standpoint, or in-depth venue benchmarking. In some cases, a pro forma is produced, which provides forecasts based on high-level assumptions of revenue-generating components. Numbers around seats, ticket cost, and sell-through rates form the basis of the projected revenue but fail to explore other revenue generating program options. For example, if two premium seating products generate similar ticket price points and demand levels—but one costs less to build, an isolated cost-benefit analysis can result in a data-driven decision adding value to the program ROI.

Mortenson’s contemporary approach to data analysis includes a supplemental layer of market data that bridges the gap between feasibility consultants, design firms, and construction partners. As the entity producing the final building product, Mortenson’s ability to connect the “data dots” provides a more accurate glimpse into a facility’s projected performance and return on cost.

Rethinking the Traditional Preconstruction Approach 

Typically, a sports facility development project follows this lifecycle:

1. Needs are identified
2. Early planning and conceptualization start; a design firm is enlisted to create visionary facility drawings, scope options, and program recommendations
3. Market study firms and specialized building consultants are commissioned to produce feasibility studies and facility assessments
4. Creation of initial pro forma and development of project financing options
5. An approximate budget, scope, and schedule is established; advanced design ensues and more explicit conceptual documents are produced that serve as a foundation for the facility and future design development
6. Construction management firms are brought into the fold to provide cost and schedule feedback related to the conceptual design documents
7. Significant gaps exist between customer budget and estimated construction cost(s); steps 2 – 6 are repeated (multiple times in some cases)

Supplementary Market Analytics Ensure Pertinent Facility Visioning 

Mortenson’s catalog of market data canvasses every zip code across the United States. With this information, we can analyze and understand statistical data related to an area’s population, as well as characteristics that define the business, economic, and consumer environments. In the context of planning a sports venue, the juxtaposition of market attributes, detailed facility benchmarking, and revenue performance data can yield powerful, early insights.

Sports facility data analysis and market intelligence allows for easy identification of outliers, i.e., venues that might not be fully capitalizing on their regional characteristics. The facility could be underdeveloped, leaving money on the table, or their facility could be overdeveloped, having excess square footage and amenities that results in misappropriated construction cost.

Layering regionalized construction cost data across labor, material, and supply chain verticals can ensure designs and expectations are appropriately established. By synonymously considering and comparing a range of variables – from consumer income profiles to the regional cost of installing deep foundations – informed decisions can be made early on that have significant downstream cost impacts.  

Market Attributes + Data Analytics in Action

A recent partnership between an NBA organization, a national sports design firm, and Mortenson, highlight how early collaboration and access to information can help drive alignment on a multi-year arena redevelopment plan.

The team is facing a situation all too common with sports properties: renovate an aging arena or build new? Nested within this question are numerous considerations:

• Renovation: To what degree of construction intensity and cost? Fan experience scopes or building systems and back-of-house updates? How many years will the arena’s useful life be extended?
• New Build: At what size, scope, and cost? What new revenue streams could be unlocked and incorporated into a fresh development? What arena and mixed-use development trends need to be understood and implemented into a new build?

In this approach, the design and preconstruction team unpacked the data with the intent to share and sharpen a dynamic plan as information was uncovered:

• The design team studied the current state of the arena, covering roof-to-foundation details. The firm devised various recommendations geared at updating the fan experience and customer amenities throughout the building.
• Shortly after, Mortenson investigated the arena’s “guts and backbone” alongside the design firm and industry consultants. Structural, enclosure, and building system components were reviewed—venue upgrade ‘absolutes’ were identified to ensure the facility could continue to operate effectively over the near-term.
• The team shared ticketing system data with Mortenson so that high-demand products and underutilized areas of the venue could be analyzed and understood.
• In-house market studies were produced by Mortenson as a benchmark of league and market peers and to cross-check various design options.
• The team conducted building studies, data analysis outputs, and cost models to understand next steps given the team’s funding options.

A critical element of the analysis included unique insight into social, economic, demographic, and firmographic data for each Metropolitan Statistical Area that serves as a home market to an NBA franchise.