On Saturday, Micah Blake McCurdy released his work quantifying the relative amount of pressure faced by players during their ice time. His full article can be read here. Micah does a great job of explaining a fairly complex idea in simple terms.
As he explains in his write-up, his new model measures the amount of pressure during a given point in a game. The basic way he accomplishes this is by measuring the importance of a goal for and the importance of a goal against at each moment in a game. As an example, if a team is trailing by one goal late in a game, scoring a goal would be hugely valuable because it would mean likely gaining at least one point in the standings as opposed to zero. Conversely, giving up a goal is not as important because that doesn’t change the amount of points they would gain from the game. The best example of this idea in practice is teams pulling the goalie. Coaches understand this intuitively but Micah’s work attempts to quantify this idea. By measuring the amount of pressure in each moment, he then shows how much pressure players face during their ice time relative to what would be faced by a “typical” player. From this, one can see which players received the highest pressure ice time and which players received the lowest. A player who receives the highest pressure ice time would seem to be a player in whom the coach has a great amount of trust. Conversely, players who receive low pressure minutes likely have not earned the same level of trust.
Now that Micah has done all of the hard work, fans can start to compare his results to other data available and see what can be learned. Micah is quick to acknowledge that his model does not have a way of measuring which players perform best under high or low pressure and thus is not a measure of “clutch” performance and also is not a tool for indicating which players deserve to see higher pressure situations. So while that level of analysis is not yet available, one can compare Micah’s results to players’ performance. My expectation would be that the players who receive the highest pressure minutes would generally be the ones who also perform the best. The following dashboard shows Micah’s graph of pressure for the Lightning and a simple table of Emmanuel Perry’s xG data that can be found on corsica.hockey. The xG data is on-ice so it measures how many goals the Lightning would expect to score and allow per 60 minutes with each player on the ice. On Micah’s graph, the x-axis shows how much important scoring a goal would be and the y-axis shows how important giving up a goal would be.
The first name that jumps off the screen in this comparison is the one that frequently does in any analysis of Lightning player results. Ryan Callahan is deployed in the highest pressure situations both offensively and defensively. However, his xG numbers are second worst on the team among the players included in Micah’s study. Callahan clearly has the trust of head coach Jon Cooper but based on his performance last season, one wonders how much that trust is justified. An example of a player whose deployment and results are almost perfectly aligned is Brian Boyle. The Lightning don’t score very much when he’s on the ice but they also don’t give up many goals. And on the pressure chart, he is being deployed in situations where preventing a goal is more important than scoring a goal. JT Brown and Cedric Paquette also fit this description. At the opposite end of the spectrum, Nikita Kucherov is a go-to when the team needs a goal. He receives the highest pressure offensive deployment but slightly less so defensively. The last player that must be noted is Nikita Nesterov. Even without Micah’s data, fans know that Nesterov lost the trust of coach Jon Cooper as the season went on and eventually lost all of his playing time. The pressure chart confirms what fans observed during the season as despite being a defender, Nesterov’s deployment was comprised of by far the least amount of defensive pressure of any player on the Lightning.
Micah’s work is exciting and gives new insight into how coaches deploy players. Quantifying coaching impacts is one of the major areas of work that remains to be explored in hockey analytics. Comparing the amount of pressure players face in their deployment to their performance is an interesting start but it doesn’t account for how players perform under specific types of pressure. So much work remains to be done and as a fan, I look forward to seeing where Micah’s work leads next.
