NHL's new in-game faceoff probability combines data, technology to enhance viewer experience

The NHL is adopting in-game faceoff win probabilities for broadcasts, a significant leap for the league in data analysis and technology.

«Face-off Probability» leverages data collected by NHL Edge, the league's puck and player tracking technology, to create a graphic that displays the chances that a player wins a faceoff or a team gains possession of the puck.

It's one of the first machine-learning stats the league has developed in partnership with Amazon Web Services, whose artificial intelligence can create in-game probabilities in subsecond speed.

«It's the first time that the NHL and AWS have come together to build something that will precede an event and offer a probability for whether or not that event will occur,» Dave Lehanski, NHL executive vice president for business development and innovation, told ESPN on Monday. «Typically, we're taking data from an event and quickly analyzing it to present some type of insight. Even if we're doing that in real time, we've yet to do it in advance of an event.»

Priya Ponnapalli, senior manager at Amazon Machine Learning Solutions Lab, said Face-off Probability uses more than 70 different data points, from historic and in-game stats, as well as contextual data. Ponnapalli said the artificial intelligence takes 10 years of faceoff results — more than 200,000 draws for all the players in the league today — and uses data that includes a player's success rate based on faceoff location, home games vs. away games and history against specific opponents. It also factors in personal data such as handedness, height and weight.

The NHL then adds in-game faceoff stats to round out the data. In both the historical and in-game stats, there's additional context such as game situations, score