Tennis AiP (Analytics integration Platform) is envisioned as both a repository for crowdsourced data capturing point-play during tennis matches as well as a platform for the integration of a diverse range of data sources which can be related to the game of tennis.
As a parent of young players, I was inspired to begin this project as a way of better understanding the game. I have found that tracking matches is a great way to lessen the stress that many parents feel watching their children on the court.
I am also intrigued by the use of technology in Sport. Tennis is behind the curve relative to other sports, but it is clear that more technology is coming to the court and that there will be ever larger quantities of data available over time. I wanted to be "early in the game" to understand what benefits are to be derived from these technologies and how they might be applied to the coaching of younger players who don't have access to systems such as Hawkeye.
There are other, lower-cost systems emerging, such as PlaySight, but these systems have a large footprint, are not generally portable, and can't be used to regularly capture data from tournament play at the Junior or Youth level where players must travel to a different venue each week.
As a parent of young players, I was inspired to begin this project as a way of better understanding the game. I have found that tracking matches is a great way to lessen the stress that many parents feel watching their children on the court.
I am also intrigued by the use of technology in Sport. Tennis is behind the curve relative to other sports, but it is clear that more technology is coming to the court and that there will be ever larger quantities of data available over time. I wanted to be "early in the game" to understand what benefits are to be derived from these technologies and how they might be applied to the coaching of younger players who don't have access to systems such as Hawkeye.
There are other, lower-cost systems emerging, such as PlaySight, but these systems have a large footprint, are not generally portable, and can't be used to regularly capture data from tournament play at the Junior or Youth level where players must travel to a different venue each week.
At the time of this post TAVA is capable of presenting visualizations of match data which originates from ProTracker Tennis, an app for iPhones and iPads, as well as match data compiled by The Match Charting Project, which was created by Jeff Sackmann and which can be found at Tennis Abstract.
The TAVA interface is fairly crude at this point. When I began this project I had no experience with either Javascript or the D3 libraries which make the visualizations possible. Phase One is entirely a hack, assembled by deconstructing, rejigging and pasting together some of the great examples available from sites such as Christophe Viau's D3 Gallery and Mike Bostock's D3 Blocks.
In the development of Phase One I was primarily focused on making my first visualizations and spent very little time on documentation and usability. At present only Chrome and Safari browsers support all of the functionality. This will be remedied with Phase Two of the web interface design.
I am currently working on development of a Node.js server with a Mongo database to store match data (in JSON format). Once the server is completed I will completely re-write the TAVA interface (with proper Javascript closures), beginning with the visualization of cross-match statistics.
The next stage will explore the integration of data that is available from a number of sensors either worn by players, or attached to racquets. I already have a good dataset of matches tracked with ProTracker Tennis where sensor data was also captured.
One of the long term goals is to add tracking of player training sessions so that match outcomes can be correlated with training goals. I have not yet found an app suitable for capturing this data.
The next stage will explore the integration of data that is available from a number of sensors either worn by players, or attached to racquets. I already have a good dataset of matches tracked with ProTracker Tennis where sensor data was also captured.
One of the long term goals is to add tracking of player training sessions so that match outcomes can be correlated with training goals. I have not yet found an app suitable for capturing this data.
The list of future functionality is large and growing. I welcome conversations and collaboration.
No comments:
Post a Comment