Determining Player Impact – Accounting for “Coat Tailing”

See howe excluding a player affects the other player's stats

Not all basketball players are created equal. At every level, you will have dominant players who bring up the rest of the team, and weaker players who are not quite on the level of everyone else. When these players are in the game, the other individual player’s team-oriented stats produced will be affected positively or negatively, affecting the plus/minus, points scored, points allowed, or other team total stats. So how do you ensure your player analyses take this coat tailing into effect?

Hoopsalytics box score stats have an “exclude player” option. When you select a player to exclude, every other player’s stats are updated to show their numbers when the excluded player is NOT in the game. The Net PPP (Points per possession) and the game-adjusted plus/minus in particular are recalculated, so you can see the effect each player has on the entire team’s performance excluding these overly strong or weak players.

For one of our demo teams, the screenshot image above shows Dylan as an excluded player, and how the stats are recalculated. This particular team had relatively even talent, so excluding the one player with the best adjusted plus/minus had no effect on the rest of the rankings.

Note that you can exclude multiple players to continue to re-rank players as needed.

Now you have another tool to help ensure the numbers for each player match your perception of their abilities. So the next time you view a game scored with Hoopsalytics, try the exclude option. You might be surprised at the results!

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Category: Analytics