Richard M. Coleman, NHL Expert On Becoming A Sports Statistician and Data Analyst

Richard M. Coleman, an NHL expert, took a unique route to become a sports analyst for the National Hockey League in 2005. He actually bought the idea of using analytics to benefit professional sports teams on the field and in the office of 23 NHL general managers. Five of those initial talks resulted in Coleman signing them on as clients of his company, Coleman Analytics, a joint effort between himself and Mike Smith.

Today, sports analysis has changed with digital technologies like wearable sensors and artificial intelligence, but the work of collecting, evaluating, and interpreting statistical data is still best when assisted by humans – sports statisticians and data analysts. Why? Because while a computer can give you stats on which goalie in a pool of 10 goalies would be the best for your high school or college hockey team, a sports analyst can also factor in some of the unpredictable factors that don’t necessarily show up in numbers.

What is a Sports Statistician?

To become a sports statistician, you need to be comfortable crunching numbers, analyzing data, and, of course, having a love for sports. If you found your college courses in statistics and probability were a breeze, then becoming a sports statistician could be a great career choice.

Today, much of the work in this field is done with computer programs that create mathematical models which are a prediction of a certain outcome. Whether a team wants to optimize their rosters by comparing different players or when they want to get an idea of which player is more likely to score in a penalty situation, the data can be a guide, but data can always be skewed by a small sample size or misinterpreted when extenuating circumstances (either good or bad) exist in real life.

Job Duties of a Sports Analyst

You’ve likely heard the old saying “garbage in – garbage out” when it comes to attempting to excel at anything. The same is true for sports data analysis. The first duty of a sports analyst is to use good data from reliable sources. Next, all that data needs to be entered into a system that will aggregate multiple sources of data – format it, compile it, and process it for further use.

From that data, reports can be written that support or denounce certain choices, decisions, or practices made by players, referees, coaches, and general management. And finally, it’s up to the sports statistician to verify that all information is valid and verifiable before being given to higher-ups or used in official records.

Richard M. Coleman, NHL expert in analytics, believes that his attention to detail and strategic way of solving problems has helped him succeed as a sports data analyst. And he suggests anyone considering this field as a career become familiar with the many software platforms that support the analysis of sports data, including digital tools for graphing, forecasting, and modeling.

Insightful sports analysis can only be done by people who have an appreciation for the nuances of the sport in which they work so that any predictive modeling can be fine-tuned to fit real-world scenarios.