Skip navigation
Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01jh343w04q
Full metadata record
DC FieldValueLanguage
dc.contributor.advisorVanderbei, Robert-
dc.contributor.authorSchafer, Ben-
dc.date.accessioned2018-08-20T13:04:44Z-
dc.date.available2018-08-20T13:04:44Z-
dc.date.created2018-04-17-
dc.date.issued2018-08-20-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01jh343w04q-
dc.description.abstractEvery year, college varsity swim teams undergo the process of recruiting the best young talent they can find to swim competitively at their institutions. This is a major time commitment for any college team, as this process is paramount for a team’s future success. This process is different for every school and every team as different coaches have varied goals when evaluating young student athletes, attempting to get an edge over their competition and find the most successful athletes for their program. These coaches can look at any number of different metrics when deciding which students to pick for their team. Typically, the student’s technique, effort in practice, ability to race, physical attributes and actual swim times are all examined in detail as desirable traits for a potential recruit. When evaluating prospects, there is never a unanimous consensus of who will do well, and a coach will often go with an instinctive decision due to the lack of clear concise information available to them. However, if this guesswork and subjectivity could be eliminated or toned down significantly, it would therefore lead to a much more streamlined and efficient recruiting process. Coaches would be more confident earlier on in their ability to go after specific talent, and the students themselves would have more confidence in their value as a recruit. This would hopefully result in a more successful outcome for all involved parties, while taking far less time than the current method. I am proposing for my thesis, to create such a predictive model, one which decides how much time any given swimmer should theoretically be able to, and be expected to, drop in a collegiate career. If successful, college teams around the country would be able to utilize the technology, be more confident in the recruiting process, and be able to create specific teams compromised of the exact swimmers required for championship success. Reducing the guesswork in the recruiting process reduces the stress on both coaches, wishing to focus on current team success, and on student athletes, who are focused on achieving consistent success in and out of the pool.en_US
dc.format.mimetypeapplication/pdf-
dc.language.isoenen_US
dc.titleSmall Fish in a Big Pond: Using Data to predict the success of Swimmers in Collegeen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2018en_US
pu.departmentOperations Research and Financial Engineeringen_US
pu.pdf.coverpageSeniorThesisCoverPage-
pu.contributor.authorid960760678-
Appears in Collections:Operations Research and Financial Engineering, 2000-2023

Files in This Item:
File Description SizeFormat 
SCHAFER-BEN-THESIS.pdf564.12 kBAdobe PDF    Request a copy


Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.