activity
20132023
most citedA comparison of machine learning techniques for taxonomic classification of teeth from the Family Bovidae

16 citations · 25 across the 6 of their papers we have counts for

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Showing stat.APShow all

7 papers · 1 filter

stat.AP2023★ 8 cited

Here Comes the STRAIN: Analyzing Defensive Pass Rush in American Football with Player Tracking Data

Quang Nguyen, Ronald Yurko, Gregory J. Matthews

In American football, a pass rush is an attempt by the defensive team to disrupt the offense and prevent the quarterback (QB) from completing a pass. Existing metrics for assessing…

stat.AP2023★ 1 cited

Big Ideas in Sports Analytics and Statistical Tools for their Investigation

Benjamin S. Baumer, Gregory J. Matthews, Quang Nguyen

Sports analytics -- broadly defined as the pursuit of improvement in athletic performance through the analysis of data -- has expanded its footprint both in the professional sports…

stat.AP2018

Confidence intervals for the area under the receiver operating characteristic curve in the presence of ignorable missing data

Hunyong Cho, Gregory J. Matthews, Ofer Harel

Receiver operating characteristic (ROC) curves are widely used as a measure of accuracy of diagnostic tests and can be summarized using the area under the ROC curve (AUC). Often, i…

stat.AP2018★ 16 cited

A comparison of machine learning techniques for taxonomic classification of teeth from the Family Bovidae

Gregory J Matthews, Juliet K. Brophy, Maxwell P. Luetkemeier +2

This study explores the performance of modern, accurate machine learning algorithms on the classification of fossil teeth in the Family Bovidae. Isolated bovid teeth are typically…

stat.AP2017

How often does the best team win? A unified approach to understanding randomness in North American sport

Michael J. Lopez, Gregory J. Matthews, Benjamin S. Baumer

Statistical applications in sports have long centered on how to best separate signal (e.g. team talent) from random noise. However, most of this work has concentrated on a single s…

stat.AP2014

Building an NCAA mens basketball predictive model and quantifying its success

Michael J. Lopez, Gregory Matthews

The old adage says that it is better to be lucky than to be good, but when it comes to winning NCAA tournament pools, do you need to be both? This paper attempts to answer this que…

stat.AP2013

openWAR: An Open Source System for Evaluating Overall Player Performance in Major League Baseball

Benjamin S. Baumer, Shane T. Jensen, Gregory J. Matthews

Within baseball analytics, there is substantial interest in comprehensive statistics intended to capture overall player performance. One such measure is Wins Above Replacement (WAR…