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A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions
The expected possession value (EPV) of a soccer possession represents th...
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SoccerMap: A Deep Learning Architecture for Visually-Interpretable Analysis in Soccer
We present a fully convolutional neural network architecture that is cap...
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Estimating locomotor demands during team play from broadcast-derived tracking data
The introduction of optical tracking data across sports has given rise t...
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Measuring Spatial Allocative Efficiency in Basketball
Every shot in basketball has an opportunity cost; one player's shot elim...
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Home Sweet Home: Quantifying Home Court Advantages For NCAA Basketball Statistics
Box score statistics are the baseline measures of performance for Nation...
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Using In-Game Shot Trajectories to Better Understand Defensive Impact in the NBA
As 3-point shooting in the NBA continues to increase, the importance of ...
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Winning Is Not Everything: A contextual analysis of hockey face-offs
This paper takes a different approach to evaluating face-offs in ice hoc...
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Playing Fast Not Loose: Evaluating team-level pace of play in ice hockey using spatio-temporal possession data
Pace of play is an important characteristic in hockey as well as other t...
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Transition Tensor Markov Decision Processes: Analyzing Shot Policies in Professional Basketball
In this paper we model basketball plays as episodes from team-specific n...
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Rao-Blackwellizing Field Goal Percentage
Shooting skill in the NBA is typically measured by field goal percentage...
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Time Perception Machine: Temporal Point Processes for the When, Where and What of Activity Prediction
Numerous powerful point process models have been developed to understand...
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Time Perception Machine: Temporal PointProcesses for the When, Where and What ofActivity Prediction
Numerous powerful point process models have been developed to understand...
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A Bayesian Nonparametric Approach to Geographic Regression Discontinuity Designs: Do School Districts Affect NYC House Prices?
Most research on regression discontinuity designs (RDDs) has focused on ...
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Learning Person Trajectory Representations for Team Activity Analysis
Activity analysis in which multiple people interact across a large space...
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Fast and optimal nonparametric sequential design for astronomical observations
The spectral energy distribution (SED) is a relatively easy way for astr...
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Diversifying Sparsity Using Variational Determinantal Point Processes
We propose a novel diverse feature selection method based on determinant...
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Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball
We develop a machine learning approach to represent and analyze the unde...
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Sequential Monte Carlo Bandits
In this paper we propose a flexible and efficient framework for handling...
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PAWL-Forced Simulated Tempering
In this short note, we show how the parallel adaptive Wang-Landau (PAWL)...
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Herded Gibbs Sampling
The Gibbs sampler is one of the most popular algorithms for inference in...
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Sparsity-Promoting Bayesian Dynamic Linear Models
Sparsity-promoting priors have become increasingly popular over recent y...
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Discussion of "Riemann manifold Langevin and Hamiltonian Monte Carlo methods" by M. Girolami and B. Calderhead
This technical report is the union of two contributions to the discussio...
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