Richard Coleman


CEO of Hockey analytics-NHL


Richard M. Coleman is a revolutionary statistician in the world of hockey analytics. Originally hailing from Stamford, Connecticut, he moved to San Francisco in 1979 and quickly established himself as a leader in the field. Through his collaborations with former Chicago Blackhawks General Manager Mike Smith, he brought new data and insights into play that revolutionized how teams recruit and build their rosters. Coleman's experience before hockey analytics extended far beyond the rink. He obtained degrees from Harvard University Medical School in Boston and Stanford University Medical School in California. Richard of Coleman Consulting Group authored two books on the subject and continues to provide valuable consultation for NHL teams and other sports organizations. 

His advanced metrics have allowed teams to make better use of available data. An example of this is his work with Corsi - which seeks to measure attempts made at the goal rather than successful shots past the goalkeeper - making evaluating potential players easier than ever before. Precision methods can now break down hockey games into manageable layers of information, providing accurate data tracking that has benefited many NHL teams thanks to Coleman Analytics. Coleman is an important figure whose commitment to advancing hockey analytics has paid great dividends for many NHL organizations worldwide. His enthusiasm for the sport is evident in all he does. At the same time, his cutting-edge software programming continually provides insight that can be utilized on-site or remotely - a testament to his strong dedication no matter what challenge arises.

Richard Coleman Chicago Blackhawks analyst describes 10 game segment report 

Published on : 03/28/2023

NHL RANKS: CHI ranked 25th of 32 NHL teams. Among 16 Western conference teams CHI ranked 8th in evs net goals but 13th in net goals versus top at -1.15/60 min. Chances for versus top ranked 13th and chances allowed 11th. The CHI power play ranked 11th at 7.0 goals/60 min pp1 compared to the 7.7 norm for this 10-game segment. The penalty kill, however, ranked last (16th) allowing 14.3 goals/60 min pk1. CHI also ranked last both on shot attempts and shots allowed while on the penalty kill. EVS goaltending was strong ranking 4th  among the West.  Overall, CHI was ahead 19% of the time and behind 30%.

As Per Richard Coleman Chicago, FWDS: Among centers Dach was the best on net chances equivalent to out chancing opponents 20-15 in a 60-minute evs game. Toews was 19-20 and allowed the highest rate of chances against.  Hagel and Strome were the best wingers on net chances while Johnson and Carpenter were the worst on this index. Forwards struggled on limiting chances against versus top opponents. The norm is 16.2 chances allowed per 60 min evs versus top. Kane was 32.6, Kubalik 31.8 and Borgstrom 39.0. Versus 1st and 2nd lines Dach in a 60-minute evs game was 19-18 on chances , Toews 16-20 and Kane 17-24. Kane has 30% of his toi versus 1st lines and was out chanced the equivalent of 12-29.  He was positive versus 2nd , 3rd and 4th lines on net chances. Kurashev and Hagel were best on net chances versus 1st and 2nd lines; Carpenter, Borgstrom and Kharia were worst. 

Chi forwards scored 13 evs goals; 10 games from the red zone (77%), which is close to the norm. The average NHL forward has 3.8 red zone shots per 60 min evs.  Strom (7.1) and Debrincat (4.8) were the leaders. Kane was just at 2.7 and Toews 3.0. Looking at synergies, Kane and Debrincat were antagonist, i.e., they made each other worse on net shots.  Dach made Debrincat much better on this index.  Seven different forward lines with at least 23 evs minutes together were used.  The best line was Dach-Strome-Debrincat; Dach-Kurashev-Kubalik was 2nd best. The line with the most evs toi together (51 minutes) Toews-Hagel-Kane, was the 2nd worst line on net goals, net chances and limiting chances against.  

On 50-50 battles Slavin had the best win rate and a high number of battles. Toews had the 2nd best win rate but 2nd lowest rate of battles among all CHI forwards.  Two forwards were very poor on this index; Kane won just 35% of battles and had the 3rd lowest rate of battles while Kubalik had just a 40%-win rate and the lowest  battle rate. 

SUGGESTIONS: Would go with Dach-Debrincat-Strome as first line and match them versus opponents first line. Would try to keep Kane away for opponent top line and match him versus 3rd and 4th lines whenever possible and/or flex him to CHI 3rd and 4th lines. Would break up Toews-Hagel-Kane line and not match Toews versus opponent top line.  Slavin outperforming Carpenter and Johnson and would consider using him as 4th liner. Kubalik toi should be mitigated by his 50-50 battle efforts. 

Richard Coleman NHL hockey analytics Chicago Blackhawks Discusses Power Play

Published On: 03-09-2023

About ten percent of each team game will be up one man on the power play. How important is the power play about rank in the standing? There is a .50 correlation between this hockey analysis, "goals per 60 minutes of 1 man advantage," and rank in the standings, so these two statistics show a moderate relation. (1.0 would be a perfect, strong relationship, and 0 would be no relationship). The league norm so far this season is 7.46 goals scored if a club is up one man for 60 minutes. The Edmonton Oilers are best, averaging 12.7 goals per 60 minutes of one-person advantage but rank just as the 13th-best club in the standings. Ottawa has the fourth-best power play averaging 9.0 goals scored per 60 minutes of one-person advantages but is only the 19th-best performing club. The Vegas Golden Knight power play is just 21st best at 6.7 goals scored per 60 minutes of one-person advantage, yet it is the 5th best-ranked team in the standings thus far. So, the power play is an important statistic, but there is no one-to-one relationship with rank in the standings.


To evaluate the best individual forward and defensemen power play contributors, some of the data that needs to be investigated include successful entries, successful setups, scoring chances, net-front presence, face-off wins, winning battles, point and goal scoring, and so forth. A good first data point is "team goals" when an individual player is on the ice. Some players can have an important, positive contribution to a club's overall power play success even though they are not racking up individual points.


In determining a player's contribution (percentile rank) to his team's power play, it is necessary to mathematically correct a player's rate for the impact of his team. For example, the Chicago Blackhawks' rate of goals per 60 minutes of power play is just 5.4, ranking 30th or second worse. With Max Domi on the ice, however (before the trade deadline), the team's rate was 7 .0. His corrected rate was 8.30, equivalent to the 66th percentile league-wide among regular forwards on the power play. Thus, we expect Domi to be a slightly above-average contributor to his new team, the Dallas Stars power play. In contrast with Caleb Jones on the power play, the Hawks only scored 3.07 goals per 60 minutes of one-person advantages. Even correcting his performance for being in a poor power-play club, his contribution comes out at the 22nd percentile among league defensemen. Caleb Jones, thus, is unlikely to be a positive contributor to any club's power play. Tyson Barrie, Morgan Reilly, and Miro Heiskanen are the top power-play defensemen in team contribution this season.

 

About the author: Richard M. Coleman was the Chicago Blackhawks hockey analytics leader for 13 seasons.