Luke Bornn

Statistics

Machine Learning

Sport

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About

My academic research is focused on developing statistics and machine learning methods for high dimensional spatio-temporal data, with a primary focus on extracting insights from player tracking data in sports. I completed my PhD at UBC under the co-supervison of Arnaud Doucet and Jim Zidek in 2012, then subsequently spent a few years on the tenure-track in the Harvard Statistics Department before returning to Vancouver via Simon Fraser, where I was awarded tenure in 2019.

In addition to my academic work, I have also worked closely with sports teams, coaches, athletes, and sports scientists to measure and evaluate athletes, strategy, and performance. I have worked with teams spanning numerous professional sports since completing my PhD, the most pertinent being roles as Head of Analytics for AS Roma and Vice President, Strategy and Analytics for the Sacramento Kings.

This site primarily serves as a repository for my academic research.

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The Bornn Lab

Luke Bornn

Principal Investigator

Luke's research focuses on spatial and spatio-temporal modeling, with applications in sports analytics and beyond.

Javier Fernandez

PhD Candidate

Javier's research focuses on quantitative measures to improve our understanding of football tactics and player valuation.

Jacob Mortensen

Alumni

Jacob defended his PhD in 2020 and is now a Senior Data Scientist at Zelus Analytics.

Nathan Sandholtz

Alumni

Nate defended his PhD in 2020 and is now an Assistant Professor at Brigham Young University.

Daniel Daly-Grafstein

Alumni

Daniel defended his MSc in 2019 and is now a PhD student at the University of British Columbia.

Patrick Ward

Alumni

Patrick defended his PhD in 2018 and now leads R&D efforts at the Seattle Seahawks.

Andrew Miller

Alumni

Andy defended his PhD in 2018 and is now a Research Scientist at Apple.

Matthew van Bommel

Alumni

Matt defended his MSc in 2017 and is now an Analytics Engineer at Zelus Analytics.

Reza Solgi

Alumni

Reza completed his Post-doc in 2017 and is now a Research Scientist at Amazon.

Mathieu Gerber

Alumni

Mathieu completed his Post-doc in 2016 and is now an Assistant Professor at the University of Bristol.

Papers

1. Chrono
2. Alpha
1. All
2. Methods
3. Computation
4. Sports Analytics
5. Structural Health
6. Climate & Environmetrics

A Data-First Approach to Learning Real-World Statistical Modeling

w/ Jacob Mortensen, Daria Ahrensmeier

The Canadian Journal for the Scholarship of Teaching and Learning, 2022

Inverse Bayesian Optimization: Learning Human Acquisition Functions in an Exploration vs Exploitation Search Task

w/ Nate Sandholtz, Yohsuke Miyamoto, and Maurice Smith

Bayesian Analysis, 2022

A Framework for the Fine-Grained Evaluation of the Instantaneous Expected Value of Soccer Possessions

w/ Javier Fernández, Dan Cervone

Machine Learning, 2021

Home Sweet Home: Quantifying Home Court Advantages For NCAA Basketball Statistics

w/ Matthew van Bommel, Peter Chow-White, Chuancong Gao

Journal of Sports Analytics, 2021

Do School Districts Affect NYC House Prices? Identifying Border Differences Using a Bayesian Nonparametric Approach to Geographic Regression Discontinuity Designs

w/ Maxime Rischard, Zach Branson, Luke Miratrix

Journal of the American Statistical Association, 2020

Markov Decision Processes with Dynamic Transition Probabilities: An Analysis of Shooting Strategies in Basketball

w/ Nathan Sandholtz

Annals of Applied Statistics, 2020

SoccerMap: A Deep Learning Architecture for Visually-Interpretable Analysis in Soccer

w/ Javier Fernandez

European Conference on Machine Learning, 2020

Using In-Game Shot Trajectories to Better Understand Defensive Impact in the NBA

w/ Daniel Daly-Grafstein

Journal of Sports Analytics, 2020

Measuring Spatial Allocative Efficiency in Basketball

w/ Nathan Sandholtz, Jacob Mortensen

Journal of Quantitative Analysis in Sports, 2020

Training Load and Injury Part 2: Questionable Research Practices Hijack the Truth and Mislead Well-Intentioned Clinicians

w/ Franco Impellizzeri, Patrick Ward, Aaron Coutts, Alan McCall

Journal of Orthopaedic and Sports Physical Therapy, 2020

Training Load and Injury Part 1: The Devil Is in the Detail—Challenges to Applying the Current Research in the Training Load and Injury Field

w/ Franco Impellizzeri, Patrick Ward, Aaron Coutts, Alan McCall

Journal of Orthopaedic and Sports Physical Therapy, 2020

Moment Conditions and Bayesian Nonparametrics

w/ Neil Shephard, Reza Solgi

Journal of the Royal Statistical Society - Series B, 2019

Rao-Blackwellizing Field Goal Percentage

w/ Daniel Daly-Grafstein

Journal of Quantitative Analysis in Sports, 2019

A Nonparametric Bayesian Methodology for Regression Discontinuity Designs

w/ Zach Branson, Maxime Rischard, Luke Miratrix

Journal of Statistical Planning and Inference, 2019

Decomposing the Immeasurable Sport: A Deep Learning Expected Possession Value Framework for Soccer

w/ Javier Fernandez, Dan Cervone

Sloan Sports Analytics Conference, 2019

Training Schedule Confounds the Relationship Between Acute:Chronic Workload and Injury

w/ Patrick Ward, Darcy Norman

Sloan Sports Analytics Conference, 2019

From Markov models to Poisson point processes: Modeling Movement in the NBA

w/ Jacob Mortensen

Sloan Sports Analytics Conference, 2019

Winning Isn’t Everything: A Contextual Analysis of Hockey Face-Offs

w/ Nick Czuzoj-Shulman, David Yu, Chris Boucher, Mehrsan Javan

Sloan Sports Analytics Conference, 2019

Playing Fast Not Loose: Evaluating Team-Level Pace of Play in Ice Hockey Using Spatio-Temporal Possession Data

w/ David Yu, Chris Boucher, Mehrsan Javan

Sloan Sports Analytics Conference, 2019

Data-Driven Lowlight and Highlight Reel Creation Based on Explainable Temporal Game Models

w/ Evin Keane, Phil Desaulniers, Mehrsan Javan

Sloan Sports Analytics Conference, 2019

Chuckers: Measuring Lineup Shot Distribution Optimality Using Spatial Allocative Efficiency Models

w/ Nate Sandholtz, Jacob Mortensen

Sloan Sports Analytics Conference, 2019

Nonparametric Hierarchical Bayesian Quantiles

w/ Neil Shephard, Reza Solgi

ArXiv, 2016

Robust Structural Health Monitoring Under Environmental and Operational Uncertainty with Switching State-Space Autoregressive Models

w/ Anthony Liu, Lazhi Wang, and Charles R. Farrar

Structural Health Monitoring, 2018

Volume and Intensity are Important Training Related Factors in Injury Incidence in American Football Athletes

w/ Patrick Ward

Sloan Sports Analytics Conference, 2018

Wide Open Spaces: A Statistical Technique for Measuring Space Creation in Professional Soccer

w/ Javier Fernandez

Sloan Sports Analytics Conference, 2018

Deep Learning of Player Trajectory Representations for Team Activity Analysis

w/ Nazanin Mehrasa, Yatao Zhong, and Greg Mori

Sloan Sports Analytics Conference, 2018

Replaying the NBA

w/ Nate Sandholtz

Sloan Sports Analytics Conference, 2018

Modeling Offensive Player Movement in Professional Basketball

w/ Steven Wu

The American Statistician, 2018

Convergence Results for a Class of Time-Varying Simulated Annealing Algorithms

w/ Mathieu Gerber

Stochastic Processes and their Applications, 2018

Possession Sketches: Mapping NBA Strategies

w/ Andy Miller

Sloan Sports Analytics Conference, 2017

Meta-Analytics: Tools for Understanding the Statistical Properties of Sports Metrics

w/ Alex Franks, Alex D'Amour, Dan Cervone

Journal of Quantitative Analysis in Sports, 2017

The Use of a Single Pseudo-Sample in Approximate Bayesian Computation

w/ Natesh Pillai, Aaron Smith, Dawn Woodard

Statistics and Computing, 2017

Adjusting for Scorekeeper Bias in NBA Box Scores

w/ Matthew van Bommel

Data Mining and Knowledge Discovery, 2017

Improving Simulated Annealing through Derandomization

w/ Mathieu Gerber

Journal of Global Optimization, 2017

The positive effects of population-based preferential sampling in environmental epidemiology

w/ Joey Antonelli, Matt Cefalu

Biostatistics, 2016

The Pressing Game: Optimal Defensive Disruption in Soccer

w/ Iavor Bojinov

Sloan Sports Analytics Conference, 2016

NBA Court Realty

w/ Dan Cervone, Kirk Goldsberry

Sloan Sports Analytics Conference, 2016

A Multiresolution Stochastic Process Model for Predicting Basketball Possession Outcomes

w/ Dan Cervone, Alex D’Amour, Kirk Goldsberry

Journal of the American Statistical Association, 2016

Modeling and Diagnosis of Structural Systems through Sparse Dynamic Graphical Models

w/ Chuck Farrar, Dave Higdon, Kevin Murphy

Mechanical Systems and Signal Processing, 2016

Herded Gibbs Sampling

w/ Yutian Chen, Mareija Eskelin, Jing Fang, Nando de Freitas, Max Welling

Journal of Machine Learning Research, 2016

Counterpoints: Advanced Defensive Metrics for NBA Basketball

w/ Alex Franks, Kirk Goldsberry, Andy Miller

Sloan Sports Analytics Conference, 2015

Move or Die: How Ball Movement Creates Open Shots in the NBA

w/ Dan Cervone, Alex D'Amour, Kirk Goldsberry

Sloan Sports Analytics Conference, 2015

Classifying X-ray Binaries:
A Probabilistic Approach

w/ Giri Gopalan, Saku Vrtilek

The Astrophysical Journal, 2015

Connecting Point-Level and Gridded Moments in the Analysis of Climate Data

w/ Hannah Director

Journal of Climate, 2015

Characterizing the Spatial Structure of Defensive Skill in Professional Basketball

w/ Alex Franks, Kirk Goldsberry, Andy Miller

Annals of Applied Statistics, 2015

A Mixture-of-Modelers Approach to Forecasting NCAA Tournament Outcomes

w/ Anthony Liu, Lo-Hua Yuan, et al.

Journal of Quantitative Analysis in Sports, 2015

Fast and optimal nonparametric sequential design for astronomical observations

w/ Justin Yang, Xufei Wang, Pavlos Protopapas

Unpublished, 2015

Diversifying Sparsity Using Variational Determinantal Point Processes

w/ Kayhan Batmanghelich, Gerald Quon, Alex Kulesza, Manolis Kellis, Polina Golland

Unpublished, 2015

POINTWISE: Predicting Points and Valuing Decisions in Real Time with NBA Optical Tracking Data

w/ Dan Cervone, Alex D'Amour, Kirk Goldsberry

Sloan Sports Analytics Conference, 2014

Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball

w/ Ryan Adams, Kirk Goldsberry, Andy Miller

International Conference on Machine Learning, 2014

Understanding the Effect of Gerrymandering on Voter Influence through Shape-based Metrics

w/ Jack Cackler

Unpublished, 2014

PAWL-Forced Simulated Tempering

Proc. Bayesian Young Statisticians Meeting, 2013

An Adaptive Interacting Wang-Landau Algorithm for Automatic Density Exploration

w/ Pierre Del Moral, Arnaud Doucet, Pierre Jacob

Journal of Computational and Graphical Statistics, 2013

Sequential Monte Carlo Bandits

w/ Michael Cherkassky

Unpublished, 2013

Modeling Non-Stationary Processes Through Dimension Expansion

w/ Gavin Shaddick, Jim Zidek

Journal of the American Statistical Association, 2012

Bayesian Clustering in Decomposable Graphs

w/ Francois Caron

Bayesian Analysis, 2012

Forecasting with Historical Data or Process Knowledge under Misspecification: A Comparison

w/ Marian Anghel, Ingo Steinwart

Unpublished, 2012

Sparsity-Promoting Bayesian Dynamic Linear Models

w/ Francois Caron, Arnaud Doucet

Unpublished, 2012

Efficient Stabilization of Crop Yield Prediction in the Canadian Prairies

w/ Jim Zidek

Agricultural and Forest Meteorology, 2011

Vibration Characteristics of Vaulted Masonry Monuments Undergoing Differential Support Settlement

w/ Sezer Atamturktur, Francois Hemez

Engineering Structures, 2011

Assessment and Management of Anemia in a Population of Children Living in the Indian Himalayas: A Student-Led Initiative

w/ Diala El-Zammar, Matthew Yan, et al.

UBC Medical Journal, 2011

Damage Detection in Initially Nonlinear Systems

w/ Charles Farrar, Gyuhae Park

International Journal of Engineering Science, 2010

An Efficient Computational Approach for Prior Sensitivity and Cross-validation

w/ Arnaud Doucet, Raphael Gottardo

Canadian Journal of Statistics, 2010

Grouping Priors and the Bayesian Elastic Net

w/ Arnaud Doucet, Raphael Gottardo

Unpublished, 2010

Structural Health Monitoring with Autoregressive Support Vector Machines

w/ Kevin Farinholt, Charles Farrar, Gyuhae Park

Journal of Vibration and Acoustics, 2009

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