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NFL Puts GIS in Play to Analyze Youth Football Programs
By Rob Layton, Jeff Smith, and Teresa Penbrooke, GRASP Team Principals
According to the National Sporting Goods Association, participation in youth football in America grew significantly from 2001 to 2006, outpacing other team sports, including soccer, baseball, ice hockey, and basketball. When calculated as a percentage, the increase in the number of youths participating in football grew at a rate several times that of the other sports.
This news was considered good by the National Football League (NFL) and other organizations interested in promoting youth football, but this news did not explain the reasons for the rise in the sport's popularity. Nor did it answer many other questions posed by the NFL: How many kids are participating in youth football programs? Who runs these programs? Where are the programs located? What kinds of fields are being used for youth football? Where are the fields located and who owns them? What factors encourage or discourage participation?
Through its NFL Youth Football Fund, the NFL partnered with USA Football and the National Recreation and Parks Association (NRPA) to commission a study of youth football in the United States. When complete, the results of the study will be used to determine where monies can best be spent to improve youth football programs and facilities across the country. The technical team challenged with conducting the study is nearing the end zone, as the second year of the three-year study was recently completed.
The technical team elected to conduct its work by utilizing a variety of tools, such as Web-based surveys, Esri's StreetMap USA map data, and ArcGIS Desktop software. These software tools are readily available; are affordable; and can be run on standard office computing equipment, including laptops. For these reasons, the team has been utilizing these tools, integrating and automating them to work together in what is called the Geo-Referenced Amenities Standards Process (GRASP) methodology. GRASP is a GIS-based approach that has been used in the parks and recreation industry for several years as a means to collect, manage, analyze, and display information on parks, recreation, and related systems and to measure and evaluate levels of service for public infrastructure and programs.
National Inventory Survey
A primary tool of the project is the National Inventory Survey. The data captured through this Web-based survey provides a baseline for determining geographic distribution and types of playing fields across the United States. This information is used to generate maps and analyses using a GIS that provides a clear picture of the footprint of youth football in the country. The primary database format from the online survey is exported into SPSS for statistical evaluation, Microsoft Excel, and dBASE4.
At the completion of the second year, the National Inventory Survey contained responses from 1,075 of the 3,141 counties in the United States. The project team conducted further analysis and determined that the respondent counties comprised the primary population centers for the United States and accounted for approximately 75 percent of the total U.S. population.
The technical team is using ArcGIS Desktop for all geographic analysis and cartographic materials. The software has been used to perform a number of analytic tasks throughout the project and allows the team to input and output data in a variety of ways at the database and cartographic levels.
Maps and Databases
Since the study requires a consistent basemap at all scales, including state boundaries, county boundaries, road networks, and points of interest, Esri's StreetMap USA map data is being used extensively throughout the study. Esri has developed a dataset that integrates a multitude of sourcesmost importantly for this project, the U.S. Census Bureau. This dataset is a well-accepted, geography-based resource for census-related demographic data. The team also wanted to ensure a consistent level of detail for all population-based analysis and cartography as the project progressed. It acknowledged that respondent data in the National Inventory Survey is highly variable with regard to the population-based questions and, assuming that the respondent data may contain some degree of error and neighboring agency replication, it used Esri's 2004 population figures at the county level for the final study.
Python Scripting Language
During the study, the technical team developed a variety of tools using the Python programming language to automate the data processing required for such a large-scale analysis project. The tools are designed to operate with the most basic ArcGIS Desktop license, which means they can be operated with minimal investment. The automation tools incorporate a variety of sophisticated processes that produce reports, tables, and analytic/cartographic datasets. The technical team designed the tools to be adaptable as the project matures and grows more complex.
GIS Technical Specifications
A major lesson learned from the first year of the study is that GIS technical specifications are crucial and must be incorporated and followed from data collection through creation of the surveying instruments and transmittal and analysis of the data. Team members worked together closely to ensure that the marriage between the National Inventory Survey dataset and the GIS would be seamless. This proved to be a successful process. For example, the team developed an advanced interface to ensure a quality capture of the respondents' data. This exercise speeds up data input for the respondent and ensures a higher level of completion upon each visit to the survey site.
The technical team established a number of lookup databases that can be used to quickly capture location information such as two-character state names and a listing of all county names. These tools have reduced the quality control efforts required before output and analysis. To test their effectiveness, team members ran a number of independent summary reports. Each came up with the same figures, indicating the data was successfully merged from the National Inventory Survey database to the GIS database, proving the importance of a well-managed data collection and analysis process when dealing with a database of this nature.
Work from the first two years provided a clear picture of the imprint of youth football in America. Among the key findings, it was determined that providing football fields alone does not ensure the growth and success of youth football. While new fields are indeed needed in some areas, investments in good coaching are more likely to yield significant results in other areas. As the study concludes its second year and enters the third and final year, several tasks are expected to be completed:
About the Authors
The authors are principals of three firms that have collaborated to develop the GRASP methodology. GRASP blends GIS and other technologies into a process that is used to plan and manage service infrastructures, such as park and recreation systems. The three firms include Design Concepts, CLA, Inc., a planning and landscape architecture firm; Geowest Inc., a GIS data analysis and management firm; and GreenPlay LLC, planners and management consultants. RRC Associates, a research and information firm, also contributed material for this article.
For more information, contact Rob Layton, principal, Design Concepts (e-mail: firstname.lastname@example.org); Jeff Smith, CEO/principal, Geowest (e-mail: email@example.com); or Teresa Penbrooke, CPRP, president/founder, GreenPlay LLC (e-mail: firstname.lastname@example.org). For more information on the GRASP methodology, visit www.dcla.net/portfolio.grasp.html.