This weekend I attended a virtual hockey analytics conference. The conference, OTTHAC has been in person in Ottawa for the last couple of years which unfortunately I couldn’t attend. But, because of Covid-19, it was moved online so I could attend for the first time. I don’t want to write about this conference specifically because there is a lot of resources online where you can read recaps and watch the presentations. What I want to talk about is more the broad concept of analytics and how it can be used as a tool to help athletes.
The debate of whether analytics have a spot in sports is basically over now since every team that has won major champions in the last couple of years has an analytics department of some form it’s hard to deny its importance. It’s not a matter of if analytics can help your game in whatever sport you compete in but how. Other than eSports the amount of analytics and data points for a sport goes down dramatically the farther away you get from the professional ranks. For example, the NHL now has play-by-play data which tracks a couple of gigabits of data a game but a league like the OHL only records a couple of stats which is a couple of megabits of data a game. So, if you’re in a league lower than that chances are you have even fewer data recorded. However, this doesn’t mean you can’t use analytics to help your game.
One way you can use analytics to help your performance in your game is to apply the findings of the highest league and apply them to your game. This doesn’t necessarily mean spending hours in a spreadsheet looking at data, it could be just reading tweets, blogs, or books of what analysts have found. For example, in basketball analysts of the NBA found that mid-range shots are inefficient and not worth shooting, so you could practice avoiding taking mid-range shots and start practicing threes or shots from the paint. Another example is in baseball as a batter your chances improve greatly when you take the first pitch of every at-bat, so you can start getting in the practice of taking the first pitch. There are plenty of examples of these little tidbits which have been discovered since the analytics revolution.
Another way you can use analytics to help your game is to record your own analytics. If your game is videotaped you can watch the game back a track the analytics yourself. The analytics you track depends on your sport and which ones you think are important. It doesn’t take much research to find out which stats the analytics community use for your particular sport. Doing this helps twofold because tracking stats of a recorded game forces you to watch the game slowly, rewind and notice little details about the game which always helps. Forcing yourself to watch yourself is a big way to improve
Analytics is a big deal in sports and will stay a big deal for the foreseeable future. Being the type of player that the data likes is a huge advantage in recruiting nowadays. Staying up-to-date with the current mindset of your sport is important. The methods I shared are mostly about team sports but there is plenty of resources about analytics in every sport, team, or individual. Learning about your passion shouldn’t be something you ever stop doing.