Final Results
Volleycomps 2.0
Advisor: Eric Alexander
Times: Fall-Winter 1,2c
Background
While data-driven analysis has always had a place in sports, the past decade has seen a dramatic uptick in how data is featured in rostering, coaching decisions, and even the fan experience. However, there is a wide variance in the resources available to programs at different levels. While professional teams and massive D-I programs often have the staff and funding to be able to track the actions and locations of literally every player at all times, other teams may be limited to just the data that one person is able to collect themselves.
At the D-III collegiate level, many stats are taken about the performance of both opposing teams and one’s own team. Most of this data is taken by hand--some mid-game, some while watching film after the fact--and must then be later collected, aggregated, and analyzed (see an example below). As such, it is very difficult for coaches to make decisions based on this data in the moment--to act upon it when it is most relevant. Interactive tools for data collection, analysis, and presentation could change this.
In 2017-2018, a group of five seniors worked with the Carleton varsity volleyball team to create an application for tracking and visualizing shot type and placement during a volleyball match. While this app was used for a while after the completion of the project, it is now sadly out-of-date and inoperable. What’s more, Carleton has a new coach with different ideas about which stats will be most valuable to helping the team win. This project will seek to build a tool capable of helping volleyball coaches collect, analyze, and act upon novel player statistics.
The project
For this project, you will develop a tablet app that can be used by the coaches and staff of the Carleton volleyball program. This app will be responsible for affording both the collection of in-game statistics and the presentation of data that can inform decision making in real time.
Important pieces of this project will include:
- Problem analysis: What are the questions that coaches want to ask of the data? This will involve working in collaboration with Coach Abby Monson and her staff and players to develop a set of needs and requirements.
- Data analysis: What models will help answer these questions? How can these models be updated to reflect new data in real time? This will require research into the different algorithms that can be employed to compute aggregate statistics, cluster types of player behavior, etc.
- Data collection: How can data be collected both accurately and efficiently while play is happening? This will involve iterative design and development of an interactive tablet interface.
- Data presentation: How can models of the data and recommendations be presented in a way that will support in-game decision making? This will likely warrant the design and implementation of visualizations to convey relevant data or models.
Deliverables
The deliverables for this project will be the app and associated documentation.
Recommended experience
This project will involve a combination of working with data and working with humans. Previous experience in extracting insight from numerical data (e.g., CS 32X, Data Visualization, statistics) will be valuable, as will experience in human-centric design (e.g., Software Design, Human-Computer Interaction, etc.). All of this experience need not reside in any single person! Most important is an enthusiasm for bridging this gap, as well as hopefully an interest in the problem domain.