Back to Search
Start Over
Predictive analytics for University of Virginia football recruiting
- Source :
- 2018 Systems and Information Engineering Design Symposium (SIEDS).
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- College football programs rely on recruiting to attract high-quality talent, which helps build a team's foundation and ensure success year after year. By conducting systems analysis of the current University of Virginia recruiting process and building upon Walter et al.'s work [1], the Virginia recruiting staff can gain a competitive advantage in the recruiting landscape. Analyzing Virginia's football recruiting and utilizing data analytics could provide the coaching staff with powerful tools to gain such a competitive edge. This study uses a database encompassing over 53,000 football recruits and over 200 predictive attributes to model the four aspects of collegiate football recruiting, as defined by Virginia's football coaches. Specifically, a desirable athlete is defined as one who 1) would succeed on the field at the collegiate level, 2) will meet Virginia's strict academic standards to achieve four years of playing eligibility, 3) fit Virginia football's “gritty” team culture, which is characterized by players who are resilient and able to overcome challenges, and 4) would commit to Virginia if given an offer.
- Subjects :
- ComputingMilieux_THECOMPUTINGPROFESSION
business.industry
05 social sciences
ComputingMilieux_PERSONALCOMPUTING
Football
Commit
Public relations
Predictive analytics
Academic standards
Coaching
Competitive advantage
Systems analysis
Work (electrical)
0502 economics and business
ComputingMilieux_COMPUTERSANDEDUCATION
Sociology
050207 economics
business
050212 sport, leisure & tourism
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2018 Systems and Information Engineering Design Symposium (SIEDS)
- Accession number :
- edsair.doi...........5f67b13b0cdb95b51bb1486a9e9c9318