Project showcase
AI Poker Tells Detection
An AI system that watches poker players the way a great live pro does — blink rate, gaze, posture, stillness, smile symmetry — and flags the moments they are likely bluffing or likely holding it. Built by Luke Geel and featured on ESPN's 2026 World Series of Poker Main Event broadcast, in a five-minute NBC News interview segment, and in WIRED.
See It In Action
These clips show the system's actual output: annotated broadcast footage where the model surfaces a read on a player and the hand reveals whether it was right. No hidden information is used — the model sees only what the camera sees.
What It Does
Every poker player leaks information. Most of it is too subtle, too fast, or too scattered across hours of footage for a human to catch. The AI poker tells detection system scans video of a player across many hands, learns which repeated physical patterns correlate with that player's hand strength, and then flags live moments where those patterns appear.
On ESPN's Main Event coverage the feature was used responsibly: analysis was shown only for players after they had been eliminated, so nothing on the broadcast could influence live play.
Blink rate
Changes in blink frequency under pressure, compared against the player's own baseline.
Eye gaze
Where a player looks — at the board, the chips, the opponent — and how that shifts by hand strength.
Posture & stillness
Shifts in posture and sudden changes in stillness after betting.
Smile symmetry
Asymmetric smiles read differently than genuine ones — one of many micro-expression cues.
How the model combines these signals — the architecture, the training data, and the code — is private. This page is a showcase of what the system produces, not a technical write-up. For the high-level ideas, read Can Poker Tells Be Measured With Computer Vision?
Honest limits: the system needs footage of a player to find their patterns, and some players simply don't have detectable ones. As Luke put it: "If I deployed it on a top professional like Daniel Negreanu, the system would probably find no signals. I assume he's worked hard to eliminate them."
As Featured On
- ESPN — 2026 WSOP Main Event Omaha Productions featured the AI tells detection system on ESPN's World Series of Poker Main Event coverage, using it to break down the behavior of eliminated players.
- NBC News A full five-minute interview segment with Luke Geel on how AI can read poker players and what that means for the game.
- WIRED WIRED's feature on the AI tells detection system at ESPN's World Series of Poker — how an AI tool that reads body language made it onto the Main Event broadcast, and where the technology could go next.
- Sportico World Series of Poker Enlists New AI Tool That Tells When You Bluff
- ZME Science ESPN Is Bringing Back the World Series of Poker, This Time with AI That Spots Players Bluffing
- BroBible ESPN Debuts New AI Technology For World Series Of Poker To Show If Players Are Bluffing
- SoMuchPoker AI Can Detect Poker Bluffs? The Future of Poker Is Here
- PokerStrategy Can AI facial recognition really identify facial tells or are we being bluffed?
- Spade Poker Revolution at WSOP 2026: ESPN Deploys AI to Spot Bluffs
- X & Instagram Clips and threads about the system were widely shared across poker X and Instagram, including Luke's own posts on the project.
Common Questions
What is AI poker tells detection?
A computer vision system that analyzes poker players on video — blink frequency, gaze, posture, stillness, and micro-expressions — and compares those patterns against previous hands to flag likely bluffs and likely strong hands.
Was it really on ESPN?
Yes. Omaha Productions featured the system on ESPN's 2026 WSOP Main Event coverage, applied only to players who had already been eliminated.
Can AI really detect poker bluffs?
Sometimes. It finds player-specific patterns when there is enough footage, and it is honest when there is no signal — some players, especially elite pros, don't have detectable tells.
Can I see the code or use the tool?
The code and methodology are private. For media, licensing, or collaboration inquiries, contact geelluke@gmail.com.