Sports Analytics

Analytics is the discovery, interpretation, and communication of meaningful patterns in data. The data in sports analytics are the statistics recorded in games (points, rebounds, aces). It is mainly concerned with quantitative data, meaning numbers. Sports analytics is about using objective numbers to help make decisions. The decisions or applications of sports analytics include: strategy decisions, goal-setting, and player evaluations. Traditionally, the “eye test,” meaning subjective observations have been used to make these decisions. However, the analytics movement has pointed out that the eye test is often inaccurate and inconsistent because of human cognitive biases, therefore they argue that using analytics is a better approach.

Strategic decisions: analytics helps judge the efficiency of certain shots/strategies. For examples, statistics show that lay-ups and three-pointers are the most efficient shots in basketball. Coaches can take these statistics and interpret them to mean mid-range jumpers are bad. However statistics need to be carefully interpreted and applied. Mid-range jumpers may be inefficient, but they are still important. Failing to practice and develop a mid-range jumper allows opponents to better defend your three-pointers and lay-ups. You need to know the meaning, assumptions, and implications behind statistics to properly interpret and apply them to your strategies and playing style.

Player evaluation: How do you define a good player? How do you compare the ability of one player to another? People often look to numbers to evaluate and rank players. This is important for coaches deciding who gets playing time. This is especially important for recruiting and drafting players. Are numbers the best way to evaluate players. Can numbers capture the importance of intangibles such as character, maturity, leadership, passion, and being a good teammate? Player evaluations should use both objective and subjective approaches.

Goal-setting and scouting reports: Analytics can be controversial when it comes to strategic decisions and player evaluations, but for goal-setting and scouting reports, it is pretty simple. Many athletes use analytics to help set goals. If they know their strengths and weaknesses using stats, they know what they need to work on. For example, if you know that you make 75% of your serves on the deuce court, but only 25% on the ad court, you know specifically what you need to work on. This helps you practice more efficiently. Using the stats from scouting reports can be helpful. If you know your opponent's strengths, weaknesses, and tendencies, you will know how to better defend or attack them.

Like most things, there are limits and downsides to analytics. They are just a tool that can help with decisions about strategy, player evaluations, and goal-setting, but they are not the only tool. And like any tool, they can be used wrongly.

Thinking too analytically can be harmful. For one, it can take the fun out of the game. People are attracted to sports because of the emotions that they cause. Thinking too analytically can take the emotion out of the game, and without emotions, you will lose your motivation to play. Sometimes you need to enjoy touchdown celebrations, trick-shots, and trash-talking and stop obsessing over efficiency. You play sports for reasons other than just to win.

Analytics, if used improperly can actually decrease performance. Athletes play their best when they go off their instincts, quiet their mind, and play with “feel.” If given too much numbers and information, players will think too much and perform worse. However, there is a solution to this issue. For example, you shouldn’t tell an athlete ten different statistics and expect them to play better. That is too much info. How are they going to remember all of that and apply it quickly in real time during a game? Instead, athletes should be given stats in bite-size pieces, and then practice applying it to ingrain it into their memories so they can easily apply it in games. For example, if told that your opponent is bad at shooting three pointers, you can prepare for this in practice. That way, during the game, you can use a certain strategy without having to think about it so much.

Sports analytics is going to improve over time. It’s just getting started. Smart people will continue to develop better stats and ways to apply them. As an athlete or a coach, become more comfortable with sports analytics and learn how to incorporate it into your training regimen and game preparation.