Research

We present a machine learning framework for classifying NCAA tennis player playstyles using match data.

To examine the effectiveness of the defensive shift in the MLB, we analyzed team defensive statistics over the past four seasons to see which variables were most correlated to shift usage.

In this paper, we are going to point out the unfairness of the NBA conference system and outline our visions for this issue.

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In this paper, we introduce the Skill Player Downfield Blocking

Effectiveness Score, a novel metric derived from player tracking data, not human evaluation.

Why are the players who are chosen to the All-NBA teams the ones selected? Can specific stats be used to predict the set of players to make the All-NBA teams?

This paper presents a possible solution to the old of problem of creating the best possible performing sports team while at the same time minimizing the cost of the team.

This paper presents a quantification of the entertainment level of Spikeball and Roundnet and searches for rule changes to maximize the entertainment factor of the sport.

As basketball fans, we are curious how the Player Efficiency Rating, a rating of a player’s per minute productivity, is calculated since it is so popular and official to be use by fans or medias.

The purpose of the study was to discover patterns characteristic of top seeded teams in the NBA, particularly looking at the patterns in the Eastern V. Western division.