Coaching Stats & Player Impact on Plays and Sets Sticky

As a coach, I’m always trying to determine which plays and sets are working, and how to place my players in sets and actions that are best suited for their skills. Many coaches rely on the “eye test”, or assumptions about a player’s ability, but having analytics to back up or challenge your perceptions of a player can help you make the best possible decisions.

To that end, we’ve added a player on/off calculation to the Coaching Stats. So not only can you see how a particular play or set works, but you can see how it works when a specific player is involved, or not involved. For example, is a particular athlete better suited for a Zone or Man-to-Man offense? You can find those answers with the latest Coaching Stats tool.

Here’s a real example from one of my prior year’s teams. Gisela and Tessa were both good three point shooters. We had a specific BLOB inbounds play called “Hawaii”, whereby one of them would be in position to shoot an uncontested long three.

From the Coaching Stats, and BLOB details, this play generated 0.93 points when there was an outcome:

Clicking on Include/Exclude Players, we can see that Gisela’s presence made the play work much better:

Tessa was also a good three point shooter, but when she was involved, the play did much worse::

We can also remove players from the calculation, and see how their absence affected the outcome of various plays. Perhaps one of your players isn’t as good at executing?  For example, when Charlotte was NOT in the game, this play had a slightly better outcome:

Like every other analytic, clicking on the number in the box score will show video clips of those events. I can watch every Hawaii play that Charlotte participated in and see if she was not executing the play properly, or maybe determine another reason.

To back up the data, I used the Shot Chart tool to isolate every shot taken from the BLOB Hawaii 3. You can see Tessa was 0 for 7 and Gisela was 3 for 4. I watched video of these shots as well from the Shot Chart.

And as a standard disclaimer, small sample sizes will have a much greater margin for error. Making one or two lucky three pointer bank shots could greatly affect the points per outcome. So you should always watch the video-links before coming to a conclusion.

This level of analysis is available for all paying customers. If you want to explore the above example yourself, try the full featured team demo for Truckee High.

 

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Category: Analytics | Stats