Success in the MLS SuperDraft: evaluating player characteristics and performance using mixed effects models

Sean Hellingman (), Zilin Wang () and Mary Thompson ()
Additional contact information
Sean Hellingman: Thompson Rivers University
Zilin Wang: Wilfrid Laurier University
Mary Thompson: University of Waterloo

Computational Statistics, 2025, vol. 40, issue 9, No 10, 5135-5161

Abstract: Abstract Drafting is a common way for many North American professional sports teams to obtain new players. The Major League Soccer (MLS) SuperDraft takes place prior to the start of each season to select valuable players. Being able to make well informed decisions surrounding draft selections is an important aspect of managing a team. This paper seeks to identify desirable characteristics of players drafted by MLS teams. Modelling the number of MLS games played and the probability of playing at least 30 MLS games, Cox proportional hazards models and mixed effects Logistic regression models were used to identify desirable characteristics and attempt to predict the success of future drafted players in MLS. The performances of the techniques have been evaluated and compared through 10-fold cross-validation. Results reveal significant player characteristics and multiple significant sources of variability during drafting. Furthermore, predictions were made for players who were selected in the 2018 and 2019 MLS SuperDrafts.

Keywords: Major league soccer; Mixed effects logistic regression; Cox proportional hazards models; Sports drafting; Player scouting (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s00180-025-01601-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:40:y:2025:i:9:d:10.1007_s00180-025-01601-w

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/180/PS2

DOI: 10.1007/s00180-025-01601-w

Access Statistics for this article

Computational Statistics is currently edited by Wataru Sakamoto, Ricardo Cao and Jürgen Symanzik

More articles in Computational Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().