Richard Coleman has been a renowned data analyst and statistician who has pioneered advanced metrics since his 2005 NHL debut. After working at Harvard University Medical School in Boston, MA, he established his own company - Coleman Analytics - and then went to Stanford University Medical School in Stanford, CA, where he sharpened his data analysis and interpretation abilities. Coleman Analytics focuses on creating higher-level analytics to track team and player performance using intricate formulas such as Corsi, Fenwick, Expected Goals and PDO, which are more exact than traditional methods. Corsi examines a player's shot attempts instead of just goals scored when the puck enters the net, while Expected Goals analyse a team's attempts more efficiently. Similarly to Corsi, Fenwick excludes blocked shots from consideration.
At the same time, PDO furthers into how "lucky" or "unfortunate" teams are by calculating their shooting percentage plus save percentage when on the ice. Working side by side with Mike Smith, Coleman also developed software programming which facilitated deeper data collection for NHL hockey matches by assessing each game layer-by-layer for simpler tracking of players. These successes have solidified Coleman as an industry leader in hockey analytics and a pioneer in sports statistics analysis overall. He has clinched five Stanley Cups with various teams, including the Blackhawks, since this award was founded in 1892 by Canada's Governor General Lord Stanley of Preston — North America's oldest professional sports trophy. Coleman also has two books published, making him one of great influence.
Richard Coleman Hockey Analytics discusses Character of NHL players
Hockey Analtyics are concerned with the objective measures of players performance. Another important aspect of becoming an NHL player is character, which is harder to measure. Below is a partial subjective list created by the Richard Coleman Chicago Blackhawks of some important character attributes that can be observed from watching a player.
LINE CHANGES: alert, responsible…
Player A has extended shifts on a regular basis and changes on the back check.
Player B has short shifts and seems to change after any Defensive Zone play
Player C raises his stick and casually comes to the bench for a line change
Player D sprints to the bench on line changes
Player E comes off the bench on a line change fixing his equipment 6. Player F comes off the bench in full stride.
A player who plays with tenacity. Fights through checks and wins battles.
Moving your feet at all times, being active, involved around the puck.
Creating energy and momentum with constant fore check.
A defenseman shows determination/persistence when he works to maintain defensive side position on his check in the low defensive zone and eventually wins the low battle to prevent a defensive breakdown.
A player hustles back hard to break up a scoring chance and then makes a full effort to either get back up ice and into the play or to the bench with hustle and effort.
A player who takes lazy stick penalties on the back check or fore check shows a lack of effort.
Player A seldom goes 1st to the puck when pressured.
Player B will go 1st and take a hit to make a play.
Player C makes big hits but seldom goes 1st to the puck.
Player D retrieves pucks with no check- offs and no urgency.
SACRIFICES BODY: blocks shots, takes hit to make play, goes into the hard areas .
Undersized player takes abuse in the corners and in front of the net but continues to go back to the net front and other hard areas determined to score a goal.
What a players’ first reaction after they turn over the puck, instantly back on the puck or do they look for someone else to get it back for them. For a defender when they are in the process of getting beat how do they react? Let the guy go or slash, whack, hold, dive do whatever it takes to not get beat even though it isn’t pretty!
. A goaltender shows second and third effort to make the save after the initial scoring chance.
. Player sprints to beat out an icing.
1. Player A blocks shots 5 on 5 and on PK.
2. Player B never blocks a shot 5 on 5 or PK.
3. Player C battles to the net in the OZ consistently.
4. Player D plays outside the dots in the OZ.
5. Player E is slow to backcheck and will wait outside the DZ.
6. Player F will BC to the goal line and support the puck low in DZ.
About ten percent of each game, an NHL team will be down one man on the penalty kill. How important is penalty killing about rank in the standing? There is a .50 correlation between this hockey analytic “goals allowed per 60 minutes of 1 man disadvantage” and rank in the standings, so there is a moderate relation been these two hockey analytics. (1.0 would be a perfect, strong relationship, and 0 would be no relationship). The NHL norm so far this season is to allow 7.46 goals if a club is down one man for 60 minutes. Boston ranks best, allowing just 4.6 goals per 60 minutes shorthanded, and also ranks as the number one club in the NHL standings; the worst NHL penalty-killing team is the Vancouver Canucks allowing 11.6 goals per 60-minute shorthanded; Vancouver ranks 27th in the standings. However, San Jose is the 3rd best penalty-killing team at 5.9 goals allowed but ranks 20th overall, while the Buffalo Sabers rank 30th in penalty-killing but are the 16th-best NHL team. So, penalty killing is an important hockey analytic, but there is no one-to-one relationship with rank in the standings.
If we look at goalies, the best save percentage when shorthanded is by Filip Gustavsson at .916. He is followed by Cam Talbot .901, James Reimer .907, and Ilya Sorokin .904. If we look at save percentage on shots on the net from the house when one man is down, the leader is Reimer at .893, followed by Sorokin at .883, Matt Murray at .878, and Tristan Jarry at .867. For the Chicago Blackhawks, shorthanded save percentages are Petr Mrazek at .838 and Arvid Soderbloom at .813 compared to the NHL norm of .866. To evaluate the best individual forward and defensemen penalty killers, some of the hockey analytics that need to be investigated include loose puck recoveries, clear rate, limiting entries and setups, blocks, face-off wins, percent time versus first power play units, opponent possession time and scoring chances. A good first hockey analytic is goals against when an individual player is on the ice. In determining a player’s percentile rank, it is necessary to mathematically correct a player’s rate for the impact of his team’s penalty killing. For example, Colin Blackwell of the Chicago Blackhawk’s rate of goals allowed per 60 minutes shorthanded is 3.87 on a club whose rate is worse than the NHL norm at 8.8 (which ranks 25th). To perform so well on a poor pk club, he gets corrected to a better rate of 2.74, placing him in the 100th percentile among NHL regular forward penalty killers. (His penalty-killing time on ice is a bit low at 78 minutes, but he is still among the 120 NHL forwards with the most penalty-killing time on ice). On the Blackhawks, before the trade deadline, the best-performing defenseman was Jack McCabe. His corrected rate of 5.55 goals against per 60-minute shorthanded placed him in the 84th percentile among NHL regular D men penalty killers. About the author: Richard M. Coleman was the Chicago Blackhawks hockey analytics leader for 13 seasons.