At the beginning of March COO Adam and lead data engineer Kishant were in Boston for the 16th annual MIT Sloan Sports Analytics Conference. This is the premier sports analytics conference in North America and was a fantastic opportunity to connect with industry peers, share and discuss the latest trends and technology.
Drive One of Three Finalists in NHL Hackathon
The big draw for us was the Hackathon Presented by ESPN and the National Hockey League. Krishant represented Drive and impressed expert industry judges from ESPN and the NHL. The task was to use data from a six game NHL playoff series to model predictive outcomes. Krishant focus on zone entries and created a compelling predictive model that could accurately forecast time in the opposition zone, shots on net, and high threat scoring chances based on the circumstances of a controlled zone entry. The judges were as impressed as we were and Krishant was selected as a finalist to present his model to a larger audience on the second day of the conference. Huge congratulations to Krishant on his awesome work.
Industry Highlights and Trends
In addition to the Hackathon, the conference included many insightful panel discussions and presentations and was an opportunity to see what some of the leading sports technology companies are developing.
A highlight for us was the panel on The State of Hockey Analytics, where we were treated to a discussion on how the NHL implemented and outfitted each area with cameras that could track player and puck movement to the millisecond, and how puck tracking has already started to shape decisions, and what it will mean even further down the road. A couple of take-aways for us were the excitement around a new broadcast capability to predict faceoff wins, and the fact that in the data collection process video alone is insufficient, validating the critical importance of sensor tracking technology. You can watch the entire panel discussion here.
Overall the sports best represented at the conference were those that generate the most revenue globally, with basketball and soccer being most prominent. The developments in basketball are the most intriguing for us as sensors are beginning to be used in the balls as well as on the players, along with video analysis, and the sport is certainly the most advanced in terms of being able to predict complex sequences of play. Across all sports the general focus was primarily on using analytics to develop team capabilities and improve team performance. Finally, a curious trend we noticed was the high level of focus on chess, which was the first complex game to have competitive machine learning algorithms.
Overall, this was a great event. We learned a lot, made some good connections and plan to be back next year, when we will have our MVP product in the market.