Graduate Feature: Sean Hellingman

Introduction

We asked our current Graduate students to tell us a bit about themselves and what kind of things they are researching.  Below is an overview of Sean Hellingman's work.  Sean has combined his interest in soccer with his research, as he enjoys using mathematical and statistical tools to solve real life problems.

Name: Sean Hellingman

Program: Mathematical and Statistical Modelling (PhD)

Educational Background:

• M.Sc. Quantitative Economic Analysis, Prague University of Economics and Business (2018)
• B.A. Mathematics, Daemen College (2013)

Current Project/Thesis/Field of Study:  Dissertation Title: Statistical models for decision-making in professional soccer

Tell me about yourself and how you became passionate about your field of study? 

So far, I have been lucky enough to earn two academic degrees that facilitate my enjoyment of problem solving. Being able to use mathematical and statistical tools to solve real life problems is something that really excites me. Soccer is something I have been very passionate about since I was a child and I have played competitively in five countries. Combining two things that are very important to me for my PhD research keeps things exciting. Developing and applying statistical models to a game that I love makes all the work that much more rewarding.

Provide a brief overview about your research.

My current research focuses on statistical models for decision-making in professional soccer. The first portion of my research focused on amateur player drafting by Major League Soccer (MLS) clubs. Statistical methods to compare two groups and logistic regression were used to identify and quantify possible impacts of rule changes implemented by the MLS. When analysing drafting, an important aspect of managing a team is being able to make well informed decisions surrounding draft selections. 

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. Mixed effects logistic regression models were used to identify desirable player characteristics and to predict the career outcomes of future drafted players.

I have also been developing stochastic models for high frequency player tracking data from F.C. Barcelona’s games. Validated through simulations, these models provide a deeper understanding for how the ball transitions between teams and moves into certain areas of the field conditioned on past in-game events such as goals and substitutions. The high-dimension stochastic models may be used to develop substitution strategies based on the current status of an individual game. I am currently working on identifying suitable models to accomplish this objective. 

I am also part of an international research project that aims to elucidate the relationship between psychosocial factors and cancer risk.

Papers: http://dx.doi.org/10.1002/brb3.2340

What one piece of advice would you give to other students interested in pursuing graduate studies? 

Like many situations in life, being surrounded by the right people is very important. Being able to work under thoughtful, dedicated, and intelligent supervisors can make all the difference in your research experiences.