How much is a missed 3 point shot worth?
Should you be shooting more threes? The generic stats package you are probably using just shows the “3 point percentage” – i.e. how many makes and misses occurred when a three-pointer was taken. But that doesn’t capture the whole story.
Many missed three point shots typically lead to long offensive rebounds due to hitting the rim harder – making it harder to box out. From there, many second chance scoring opportunities arise, including kickouts and putbacks. So a missed shot has some hidden value in it.
To illustrate how three-point shots differ, we used Hoopsalytics to chart the location of 1468 rebounds during our last season, and here’s where two-point shots were rebounded from:
Here’s where three-points shots went::
These three-point offensive rebounds can be converted into scores at a relatively high rate. Here’s why:
- The defense will be out of position.
- Passes out from rebounders to shooters often result in uncontested “step-in” threes, which are more accurate than other types of three point shots.
- Offensive rebound putbacks are also a high percentage shot.
We can approximate the point-value of a missed three by using a team’s offensive rebounding percentage, and their PPP (Points per Possession). For USF, their season PPP was 1.08, and their three-point offensive rebounding percentage (tracked by Hoopsalytics) was 29%. Just given those numbers, you’d expect the value of a missed three to be 0.31 PPP (1.08 * .29).
However, the real value of a missed three for USF was actually 0.34 PPP. For their opponents, it was 0.27.
This calculation is more accurate because we use actual play-by-play data. The table below shows Hoopsalytics data for the net points scored per possession when the possession contained at least one attempted three pointer, or a missed three pointer or an attempted two pointer. For comparison, we also show the aggregate points per possession (which can include possessions ending in a turnover – worth zero points) for these various levels.
Here’s the data:
| Team | 3 point shots Attempted PPP |
3 point shots Missed PPP |
2 point shots Attempted PPP |
All Possessions PPP |
|---|---|---|---|---|
| USF Men (NCAA D1 – 34 games) | 1.29 | 0.34 | 1.32 | 1.08 |
| USF Men Opponents (NCAA D1 – 34 games) | 1.02 | 0.27 | 1.19 | 0.95 |
| High School Girls Varsity (1 team, 23 games) | 0.89 | 0.25 | 0.82 | 0.62 |
| High School Girls Varsity (multiple teams, 23 games) | 0.90 | 0.32 | 0.92 | 0.63 |
| High School Freshmen Boys (8 games) | 0.82 | 0.35 | 0.84 | 0.64 |
Schemes like the Grinnell System take advantage of these analytics by minimizing turnovers via getting up a quick shot, shooting a lot of threes, and by emphasizing “everybody crash the offensive boards”. Your mileage may vary depending upon your team’s shooting and offensive rebounding.
How Do I Get This Data for My Team?
First, you need to score a game using Hoopsalytics. If you’re not yet subscribed, you can sign up for a free one game trial. And we’ll help you get up and running and answer any questions as you get started.
Once you’re done scoring, have a look at your Offensive Stats box score, and click on the details icon next to 3 Pt A:
Then click on Scoring Efficiency. You will see the expected value for a possession or a sequence with the selected shot type.
Hoopsalytics shows you the overall expected value, as well as the expected value for various players and/or shot types. Here’s how it looks for my 2021-2 high school team:
All box score data in Hoopsalytics is linked to video of those events, so you can click on any number or cell and see exactly what happened. Sometimes the “eye test” can be a helpful addition to just the numbers.
When viewing these reports, you can choose between sequences and possessions. A possession spans the time when one team exclusively controls the ball. There can be multiple sequences in a possession (i.e. if a possession contains a stoppage of play, or a reset.) Sequences are probably a better indicator of value, but you can see both measurements and decide for yourself.
Was this interesting or helpful to you? Let us know if you like this sort of analysis by commenting, or if you have any questions or observations.