
A Snapshot of How Rithmm Identifies NBA Player Props
A Snapshot of How Rithmm Identifies NBA Player Props
Table of Contents
How Rithmm Surfaces Player Props Over Time
One of the easiest ways to understand how Rithmm works is to look at what actually shows up inside the product over time.
Rithmm doesn’t recommend every player, every game, or every prop. It surfaces specific player props when its models identify value relative to the market. When there’s no edge, nothing appears.
A clear example of this behavior shows up in NBA player prop unders this season.
When the Model Flags an Under
Below is a snapshot of how certain players have performed specifically in games where Rithmm surfaced an under recommendation. These are not all unders across the market. They are only situations where the model identified value and surfaced the play.
Here’s what that slice of performance looks like:
Giannis Antetokounmpo — Under: 40–21 record, 65.57% win rate, 21.16% ROI
Anthony Davis — Under: 32–15 record, 68.09% win rate, 26.81% ROI
Domantas Sabonis — Under: 18–7 record, 72% win rate, 35.76% ROI
Devin Booker — Under: 17–7 record, 70.83% win rate, 29.22% ROI
Joel Embiid — Under: 15–6 record, 71.43% win rate, 31.58% ROI
There are also smaller samples where the same pattern appears when the model surfaces an under:
D’Angelo Russell — Under: 10–0 record, 100% win rate, 88.58% ROI
Trae Young — Under: 8–0 record, 91.08% win rate, 90.08% ROI
Larry Nance — Under: 7–0 record, 100% win rate, 103% ROI
What This Snapshot Shows
This snapshot isn’t meant to suggest that unders are always the answer or that every player appears regularly. It simply shows what happens when Rithmm’s models decide a player prop is worth surfacing.
Over the course of the season, those moments can be tracked, reviewed, and evaluated in real time. That’s the experience users see inside Rithmm: selective recommendations, familiar players appearing in specific spots, and performance that can be measured over time.
You can see this same behavior inside Rithmm. Player props surface when the model identifies value, and you can track how those recommendations perform over time. Rithmm is available on the App Store, Google Play, and on the web, with a free trial to explore NBA player props.


