Scrabble Cheating Detector
Analyze a suspicious Scrabble move and get a Suspicious Move Score based on how unusual and solver-like the play was. Set up the position before your opponent's move, mark the tiles they placed, and compare the play to strong solver output and to typical human choices.
- Board
- Mark move
- Score
How do you want to enter the board?
Upload a screenshot to fill the board automatically, or enter it by hand. Either way you'll review the board before anything is analyzed.
How the analysis works
- Reconstruct the board as it was before your opponent's move.
- Have a game solver evaluate the strong, legal plays from that position.
- Compare the observed move against patterns from human gameplay.
- Account for the tiles on the opponent's rack that you can't see.
- Combine these into a single Suspicious Move Score.
Understanding the Suspicious Move Score
The Suspicious Move Score (SMS) runs from 0 to 100 and summarizes how unusually solver-like a move is compared with human play. Low scores mean the move looks ordinary; high scores mean it closely matches what a solver would choose and is rarely picked by human players.
Scrabble has deep, well-studied strategy around rack leaves and board control. The score considers whether an opponent's choices track solver preferences — including subtle defensive or setup plays that most human players overlook.
A high score on a single move is not proof of cheating — luck and skill both produce strong plays. Repeated high scores across many moves are much more meaningful than any one result.
Frequently asked questions
Can a Suspicious Move Score be used as proof of cheating?
No. It is an analytical signal, not a verdict. Treat a high score as a reason to look closer, ideally across multiple games, rather than as evidence about any single move or player.
Why are repeated solver-like moves more suspicious than one?
Any one strong move can come from skill or luck. But finding the solver's preferred play again and again — including obscure words and non-obvious defensive moves — becomes statistically unlikely for unaided human play as the sample grows.
Does a high rating make a low score more likely?
Stronger players naturally produce more solver-like moves, so context matters. When a rating is available it can be factored in, so an expert's strong play is judged against expert expectations rather than beginner expectations.