Richard M. Coleman and Hockey – Understanding the Advanced Field of Sports Analytics

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For certain, Baby Boomers can remember collecting sports cards with posed images and recent statistics of their favorite sports figures. Many of those same baseball, basketball, football, and hockey sports cards became collectors’ items, with some fetching over a million dollars in recent trades. While it may be the image of the professional athlete that garners much attention, it is truly the statistics on the back of these cards that prove their worth.

Richard M. Coleman, hockey expert, was one of those young sports fanatics, and he just happened to have a talent for numbers, also. Today, he is a statistician based in Boca Raton, FL, and the co-founder of Coleman Analytics, a joint effort between Coleman and Mike Smith, the former general manager of the Chicago Blackhawks hockey team.

Understanding Sports Analytics

A close analysis of any subject or action will reveal deeper insight and greater discernment when making decisions regarding that subject or action. When it comes to sports, these informed decisions can make all the difference between a losing season and a Stanley Cup.

Sports analysis is the study of professional sports players (physical and mental traits), their athletic performance (on game day and in practice drills), along with the health of the sports organization (because the best players cost the most money). All of these factors can be represented by numbers, except the psychological state of the player. Yet, it is a player’s outstanding statistics that almost always point to a player with the right priorities, enormous drive, a keen knowledge of the game, and more.

In 2005, Richard M. Coleman, hockey analytics expert, introduced some of the most advanced metric counters in the history of professional hockey. These complex calculations include Corsi, which represents the number of times players attempt to make a goal rather than a simple count of goals when the puck enters the net. He also created the Fenwick metric, which excludes blocked shots and counts only shots that go into the net or are blocked from entering the net.

But, these numbers may not reflect whether the player is simply lucky or extremely talented. Therefore, he developed an analytical statistic called PDO, which gives the other stats real-world relevance and puts the numbers into a stronger focus. PDO calculates the on-ice shooting plus save percentage in a game.

With the PDO stat, coaches, managers, and trainers can determine how “lucky” or “unlucky” a team may be. Let’s face it, some shots that resemble trick shots are more luck than skill. Many of these types of Hail Marys are ruled out from the player’s true performance statistics.

These are just a few examples of how sports data can support a player or lead a team down a rabbit hole. No matter how much data a team has in their possession, if it is not leveraged correctly, then it becomes useless. There are many teams that rely on the outstanding statistics of their players to translate into dollars and cents for the franchise. And there are many examples in recent sports history where outstanding team performance results in outstanding team profits.

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