NHL analytics powered by
real statistical modeling

What We Do

We build data-driven tools that make NHL statistics more useful and accessible. Our models pull from publicly available data and apply statistical techniques to surface insights that go beyond the box score.

Our Methodology

Our contract valuation model is built on Wins Above Replacement (WAR), drawing inspiration from the publicly available research at Evolving-Hockey. We model expected AAV as a function of WAR and market conditions, then compare it against each player's actual cap hit to produce a value rating.

Our draft model uses CSS scouting ranks as a Bayesian prior, adjusted by NHLe (NHL equivalency) production. NHLer% represents the probability a prospect plays 164 or more NHL games. Star% represents the conditional probability of becoming a top-line contributor, given they reach the NHL.

Our expected goals (xG) model estimates the probability that any given shot becomes a goal, using shot distance, angle, shot type, and whether the shot came off a rebound or off the rush. It is deliberately blind to who took the shot, so comparing a player's actual goals against his expected goals measures how he finished the chances he generated. On a like-for-like basis, excluding empty-net situations, the model currently lands within half a percent of the league's real goal total.

All data is sourced from publicly available NHL APIs, CSS rankings, and official transaction records. Models are updated regularly throughout the season.

Contact

Questions, feedback, or data inquiries — we'd love to hear from you.