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High School Swimming Success

High School Swimming Success. Using ArcGIS to predict the success of Fairfax County high school swim teams. Executive Summary. Predict the success of a high school swim team based on the quantity of summer league swimmers that feed a particular school

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High School Swimming Success

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  1. High School Swimming Success Using ArcGIS to predict the success of Fairfax County high school swim teams

  2. Executive Summary • Predict the success of a high school swim team based on the quantity of summer league swimmers that feed a particular school • Determine how high schools are actually performing based on these predictions

  3. Goals • Use ArcGIS to plot the number of summer league swimmers that feed each high school • Use ArcGIS to plot the success of each high school at the 2009 Regional Swim meet • Determine if there is a correlation between the number of summer league swimmers and the success of the high school team at the 2009 Regional championships

  4. Method • Gather Fairfax County Public high schools boundary .shp file • Gather Fairfax County Public high schools location .shp file • Determine summer swim leagues in Fairfax County • Collect pool addresses, and number of swimmers for each summer pool in Fairfax County • Determine which high school boundary each pool is in • Collect scores from the 2009 Regional Swim meet • Geocode pool addresses to Fairfax County schools map • Join geocoded pool addresses .shp file to high school boundary map • Create a chroropleth map showing the results

  5. Data Summer Swim Leagues • Northern Virginia Swim League – 102 Pools, 15,000 Swimmers • Colonial Swim League - 24 Pools, 2,500 Swimmers • Herndon Swim League - 9 pools, 500 Swimmers • Reston Swim League – 9 pools, 900 Swimmers

  6. Analysis / Problems • Pool Boundary does not fit high school Boundary (Several Examples) • Geocoding could not find and address (Example) • Thomas Jefferson High School

  7. Analysis

  8. Conclusions - Results

  9. Conclusions - Results

  10. Pool exists, but is so new that it could not be geocoded because the roads maps are not new enough

  11. Conclusions - Results • Highest number of swimmers *McLean * Woodson * West Springfield • Lowest number of swimmers *Edison * Hayfield * Mount Vernon

  12. Conclusions - Results

  13. Conclusions - Results • Highest combined scores at Regionals *Robinson * Fairfax * Langley • Lowest combined scores at Regionals *Hayfield * Mount Vernon * Stuart * Falls Church

  14. Conclusion - Results • Very difficult to predict which school will be the best (too many other factors) • Very easy to predict which schools will not do well

  15. Further Research • Plot the number of year round swimmers that feed each high school • Plot the individual addresses for each swimmer onto the high school boundary map • Remove the dive scores from the regional meet scores

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