Mapping the Hometowns of University of Nebraska-Lincoln Football Recruits, 2000-2018
Introduction
You can jot notes about the introduction here as you see fit, but I would encourage you to wait until the analysis is complete before you finish the introduction section.
Background
The purpose of this study is to understand geographic variability in the University of Nebraska’s football recruiting. The University of Nebraska switched athletic conferences in 2011, from the Big Twelve Conference to the Big Ten Conference. Schools in the Big XII Conference include states with high prevelance of high school football culture, like Texas. With Nebraska’s switch into the Big Ten, I hypothesize the mean center of recruits has shifted north. Dumand, Lynch, and Platania (2008) state the number one factor in a high school recruits’ choice in college is the geographic distance between hometown and college. Although Nebraska and Texas aren’t that close geographically, Nebraska did travel down to Texas at least once a year for an away game, which Texas recruits can invite their family and friends to those games. However, with Nebraska’s switch into the Big Ten Conference, they stopped traveling to Texas on an annual basis, which may have affected their ability to recruit in Texas.
This study is important because of the enormous financial impact college athletics have on universities. College athletics provide direct financial gain for universities, in that universites directly profit off of their football programs (given they are successful). Collegiate athletics also can increase exposure for universities, which in turn increases financial contributions from people and increase enrollmen numbers (Goff 2002). And the more successful the program, the more financially successful the university is.
Methods and Data
19 years of recruits’ hometowns were compared between 2000 and 2018. Those years were selected because they represent Nebraska in the Big XII conference, their transition into the Big Ten Conference, and Nebraska rooted in the Big Ten Conferene. The University of Nebraska’s football website was used, in which they have an extensive database on every player and their hometown throughout their football history.
Once the years were determined, the data was extracted using R, specifically the package “Rvest.” The package Rvest is used to scrape data from webpages, and using the code below I extracted the hometowns of football players.
Once the data was collected, it was geocoded using the Nominatim geocoding API. However, some hometowns did not geocode correctly for an unknown reason. For example, some states with a three letter abbreviation (i.e. Neb. for Nebraska) did not locate correctly. Due to this, the players hometowns had to be subsuited using the code below.
Once the data was geocoded, various kinds of maps were created for analysis. A time change map was created to see the change in recruits’ hometowns over time. A heat map observed, to see the density of Nebraska’s football recruits. Geographic mean center and standard deviation were also calculated, to see the spatial change and variability in recruits from 2000 to 2018.
The data used for this study is from the University of Nebraska Football roster page. For the study years, the season was just changed from the current year, to the years desired for the study.
For spatial reference, this is a map of the University of Nebraska within the context of the United States.
Study Area Map
Results
The data produced relatively accurate geocoded results, as evident by the map below. The map below is an example for the year 2000. There were a couple of inaccurate geocodes, which points in Czech Republic and Namibia, however the vast majority of points geocoded correctly.
Geocoded Result Map of Nebraska Recruit’s Hometowns, 2000
The geocode map is hard to analyze based on points alone, so I created a cluster map to better analyze the data.
2000 Cluster Map of Nebraska Recruit’s Hometowns
Most of Nebraska’s recruits come from Nebraska and the surrounding (Missouri, Kansas, Iowa, and Colorado). Texas has the highest number of recruits out of states that do not border Nebraska, with eight recruits.
I created a cluster geocode map for the year 2018 as well (see below)
2018 Cluster Map of Nebraska Recruits’s Hometowns
For the year 2018, most of Nebraska’s recruits hail from Nebraska and the tri-state area (Missouri, Kansas, and Iowa). Six recruits hailed from the Texas area, six came from Georgia, and five came from Colorado.
A mean center map was also created, with green markers representing Nebraska recruits before the conference switch, while red represents after.
Mean Center Map
The green markers generally seem more west compared to the red markers, meaning there might be some change in where Nebraska obtained their recruits. The mean center isn’t moving east consistently every year, however the general trend seems to be moving east.
Standard deviations were also calculated in the table below.
Standard Deviation Table
| Year | Lon SD (degrees) | Lat SD (degrees) |
|---|---|---|
| 2000 | 17.81 | 6.53 |
| 2001 | 18.36 | 7.24 |
| 2002 | 19.19 | 7.19 |
| 2003 | 20.74 | 7.05 |
| 2004 | 19.18 | 5.55 |
| 2005 | 21.70 | 6.85 |
| 2006 | 19.38 | 6.99 |
| 2007 | 16.18 | 6.77 |
| 2008 | 14.56 | 7.09 |
| 2009 | 14.13 | 7.12 |
| 2010 | 11.94 | 4.86 |
| 2011 | 18.28 | 7.65 |
| 2012 | 15.40 | 4.65 |
| 2013 | 17.13 | 4.73 |
| 2014 | 18.01 | 5.10 |
| 2015 | 18.46 | 5.06 |
| 2016 | 12.97 | 5.03 |
| 2017 | 13.19 | 5.24 |
| 2018 | 11.94 | 4.86 |
Discussion
Conclusion
References
Dumond, J. Michael, Allen K. Lynch, and Jennifer Platania. 2008. “An Economic Model of the College Football Recruiting Process.” Journal of Sports Economics 9, no. 1 (February): 67-87.
Goff, B. 2000. “Effects of University Athletics on the University: A Review and Extension of Empirical Assessment.” Journal of Sports Management 14, no. 2 (April): 85-104.