Luke Bornn


Vice President, Strategy and Analytics
Sacramento Kings

Assistant Professor of Statistics
Simon Fraser University

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About


I am Vice President, Strategy and Analytics at the Sacramento Kings and an Assistant Professor of Statistics at Simon Fraser University (currently on leave). 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.

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. While I have worked with teams spanning numerous professional sports since completing my PhD, I most recently worked with AS Roma, where I was Head of Analytics.

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The Bornn Lab


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Luke Bornn
Principal Investigator

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

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Jacob Mortensen
PhD Candidate

Jacob's research focuses on developing statistical and machine learning methods applied to problems in basketball and other sports.

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Javier Fernandez
PhD Candidate

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

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Nathan Sandholtz
PhD Candidate

Nate's research focuses on developing statistical and machine learning methods applied to problems in basketball and other sports.

Papers


Moment Conditions and Bayesian Nonparametrics
w/ Neil Shephard, Reza Solgi
Journal of the Royal Statistical Society - Series B, 2019
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Rao-Blackwellizing Field Goal Percentage
w/ Daniel Daly-Grafstein
Journal of Quantitative Analysis in Sports, 2019
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A Nonparametric Bayesian Methodology for Regression Discontinuity Designs
w/ Zach Branson, Maxime Rischard, Luke Miratrix
Journal of Statistical Planning and Inference, 2019
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Decomposing the Immeasurable Sport: A Deep Learning Expected Possession Value Framework for Soccer
w/ Javier Fernandez, Dan Cervone
Sloan Sports Analytics Conference, 2019
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Training Schedule Confounds the Relationship Between Acute:Chronic Workload and Injury
w/ Patrick Ward, Darcy Norman
Sloan Sports Analytics Conference, 2019
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From Markov models to Poisson point processes: Modeling Movement in the NBA
w/ Jacob Mortensen
Sloan Sports Analytics Conference, 2019
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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
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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
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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
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Chuckers: Measuring Lineup Shot Distribution Optimality Using Spatial Allocative Efficiency Models
w/ Nate Sandholtz, Jacob Mortensen
Sloan Sports Analytics Conference, 2019
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Nonparametric Hierarchical Bayesian Quantiles
w/ Neil Shephard, Reza Solgi
ArXiv, 2016
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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
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Volume and Intensity are Important Training Related Factors in Injury Incidence in American Football Athletes
w/ Patrick Ward
Sloan Sports Analytics Conference, 2018
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Wide Open Spaces: A Statistical Technique for Measuring Space Creation in Professional Soccer
w/ Javier Fernandez
Sloan Sports Analytics Conference, 2018
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Deep Learning of Player Trajectory Representations for Team Activity Analysis
w/ Nazanin Mehrasa, Yatao Zhong, and Greg Mori
Sloan Sports Analytics Conference, 2018
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Replaying the NBA
w/ Nate Sandholtz
Sloan Sports Analytics Conference, 2018
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Modeling Offensive Player Movement in Professional Basketball
w/ Steven Wu
The American Statistician, 2018
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Convergence Results for a Class of Time-Varying Simulated Annealing Algorithms
w/ Mathieu Gerber
Stochastic Processes and their Applications, 2018
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Possession Sketches: Mapping NBA Strategies
w/ Andy Miller
Sloan Sports Analytics Conference, 2017
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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
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The Use of a Single Pseudo-Sample in Approximate Bayesian Computation
w/ Natesh Pillai, Aaron Smith, Dawn Woodard
Statistics and Computing, 2017
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Adjusting for Scorekeeper Bias in NBA Box Scores
w/ Matthew van Bommel
Data Mining and Knowledge Discovery, 2017
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Improving Simulated Annealing through Derandomization
w/ Mathieu Gerber
Journal of Global Optimization, 2017
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The positive effects of population-based preferential sampling in environmental epidemiology
w/ Joey Antonelli, Matt Cefalu
Biostatistics, 2016
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The Pressing Game: Optimal Defensive Disruption in Soccer
w/ Iavor Bojinov
Sloan Sports Analytics Conference, 2016
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NBA Court Realty
w/ Dan Cervone, Kirk Goldsberry
Sloan Sports Analytics Conference, 2016
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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
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Modeling and Diagnosis of Structural Systems through Sparse Dynamic Graphical Models
w/ Chuck Farrar, Dave Higdon, Kevin Murphy
Mechanical Systems and Signal Processing, 2016
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Herded Gibbs Sampling
w/ Yutian Chen, Mareija Eskelin, Jing Fang, Nando de Freitas, Max Welling
Journal of Machine Learning Research, 2016
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Counterpoints: Advanced Defensive Metrics for NBA Basketball
w/ Alex Franks, Kirk Goldsberry, Andy Miller
Sloan Sports Analytics Conference, 2015
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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
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Classifying X-ray Binaries:
A Probabilistic Approach
w/ Giri Gopalan, Saku Vrtilek
The Astrophysical Journal, 2015
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Connecting Point-Level and Gridded Moments in the Analysis of Climate Data
w/ Hannah Director
Journal of Climate, 2015
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Characterizing the Spatial Structure of Defensive Skill in Professional Basketball
w/ Alex Franks, Kirk Goldsberry, Andy Miller
Annals of Applied Statistics, 2015
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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
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Fast and optimal nonparametric sequential design for astronomical observations
w/ Justin Yang, Xufei Wang, Pavlos Protopapas
Unpublished, 2015
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Diversifying Sparsity Using Variational Determinantal Point Processes
w/ Kayhan Batmanghelich, Gerald Quon, Alex Kulesza, Manolis Kellis, Polina Golland
Unpublished, 2015
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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
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Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball
w/ Ryan Adams, Kirk Goldsberry, Andy Miller
International Conference on Machine Learning, 2014
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Understanding the Effect of Gerrymandering on Voter Influence through Shape-based Metrics
w/ Jack Cackler
Unpublished, 2014
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PAWL-Forced Simulated Tempering
Proc. Bayesian Young Statisticians Meeting, 2013
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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
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Sequential Monte Carlo Bandits
w/ Michael Cherkassky
Unpublished, 2013
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Modeling Non-Stationary Processes Through Dimension Expansion
w/ Gavin Shaddick, Jim Zidek
Journal of the American Statistical Association, 2012
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Bayesian Clustering in Decomposable Graphs
w/ Francois Caron
Bayesian Analysis, 2012
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Forecasting with Historical Data or Process Knowledge under Misspecification: A Comparison
w/ Marian Anghel, Ingo Steinwart
Unpublished, 2012
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Sparsity-Promoting Bayesian Dynamic Linear Models
w/ Francois Caron, Arnaud Doucet
Unpublished, 2012
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Efficient Stabilization of Crop Yield Prediction in the Canadian Prairies
w/ Jim Zidek
Agricultural and Forest Meteorology, 2011
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Vibration Characteristics of Vaulted Masonry Monuments Undergoing Differential Support Settlement
w/ Sezer Atamturktur, Francois Hemez
Engineering Structures, 2011
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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
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Damage Detection in Initially Nonlinear Systems
w/ Charles Farrar, Gyuhae Park
International Journal of Engineering Science, 2010
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An Efficient Computational Approach for Prior Sensitivity and Cross-validation
w/ Arnaud Doucet, Raphael Gottardo
Canadian Journal of Statistics, 2010
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Grouping Priors and the Bayesian Elastic Net
w/ Arnaud Doucet, Raphael Gottardo
Unpublished, 2010
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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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