With the halfway mark of the 2019-2020 NHL season past, I dove into some statics for individual players. Using a couple different stats, a player’s luckiness, chippiness, and quality vs. quantity of shots were evaluated.
Defenseman were separated out from the centers, and wings for a more fair evaluation. Players had to have had at least 20 games played to be included in this analysis. All data is as of 1/12/2020.
The first set of graphics looks at how lucky players have been in regards to goals. This is done by taking a player’s total expected goal value and total goals scored and comparing both these to the average (represented by the lines in the graphics). If a player is below the average in expected goals, but above in goals they are considered lucky. Players who are above the average in expected goals, but below in goals are considered unlucky. Players who are above both averages are good, and those below are bad.
It’s no surprise the superstars of the league are some of the best players by this measure: David Pastrnak, Auston Matthews, Alex Ovechkin, and Leon Draisaitl. Some of the best defenseman are Roman Josi, Zach Werenski, and Dougie Hamilton. These players are constantly getting scoring chances and are taking advantage of it.
Some of the unlucky players are Wayne Simmonds of the NJ Devils and Austin Wagner of the LA Kings. Notably, both these players are on teams who are not having the best seasons. It’s hard to say of the lack of goal scoring is due to less support from a better team, or if it is really more of an individual issue.
Lucky players include Andre Burakovsky, Brett Connolly, and Carson Soucy. What’s different here are the make up of the teams. Andre plays for the Colorado Avalanche who are currently in third place in the Central. Brett is on the Florida Panthers who are in fourth place in the Atlantic, and Carson is on the Minnesota Wild who are tied for last place with the Chicago Blackhawks in the Central.
The second set of graphics looks at how chippy players are on the ice. This is done by comparing the penalty minutes (PMI) drawn of a player to the number of PMI they’ve served.
Players who are above average in both categories are chippy. Players below average in PMI taken, but above average in PMI drawn are disciplined. Players above average in PMI taken, but below in PMI drawn are undisciplined.
This really was a fun graphic to look at and create. Clearly Nicolas Deslauriers, Brendan Lemieux, and Dennis Gilbert stick out. These are players who have been known to take on a fight and definitely live up to the classification of chippy.
Evander Kane, Ryan Strome, Tomas Tatar, and Hampus Lindholm have all been penalized more than double the amount of minutes they have drawn. What’s curious is most of the teams on the outer edge of the undisciplined category are not doing well in the standings. It’s hard to say if their lack of success is because they are more undisciplined than average, or if they are more undisciplined because they are not doing as well.
The final set of graphics looks at if players have more quality or quantity of shots. Players with above average expected goal value and shot attempts are good. Players with above average expected goals, but below average shot attempts pick quality over quantity. Players with below average expected goals, but above average shot attempts pick quantity over quality. Players above average in both categories are good.
On the other hand, Evgeny Kuznetsov and Cale Makar were a bit surprising to see them in the quality over quantity section. These are two staples to their respective teams, but clearly they have less shot attempts than others in their same positions.
Duncan Keith, Mike Hoffman, and Elias Lindholm were noticeable players in the quantity over quality section. I’ll admit, of these three I definitely have seen Duncan Keith the most and he seems to be firing the puck any chance he gets.
These types of comparisons are very fun and interesting to me. By taking some very basic statistics we can categorize players into different play styles. I certainly expect I’ll be doing this type of analysis in the future, but with different sports and also on the team level.
Data and inspiration: moneypuck.com