What is this?
Unmatched Fighter Chooser is a free, fan-made web tool that helps players of the Unmatched board game pick well-matched fighters for their next game. Instead of spending time debating who to play, let the tool do the work based on what you own, how you like to play, and how balanced you want the fight to be.
This is not an official Restoration Games product , it’s built by fans, for fans.
What it does
- Pick your collection — select only the sets you own so suggestions stay practical.
- Choose playstyles and ranges — prefer aggressive rushdown, ranged control, or something in between.
- Get matchup suggestions — optimised for your chosen mode (discovery, balanced, or best-fit).
- Lock a fighter — already know who you want to play? Lock them in and generate tailored opponents.
How suggestions are scored
Every possible matchup receives two scores that are blended together:
- Fit — how well each fighter matches your requested playstyles and range preferences. A higher fit means the fighters feel like the kind of game you described.
- Fairness — how close the matchup is to 50/50 based on community win-rate data. A higher fairness score means neither player has a large statistical advantage.
Different suggestion modes shift the emphasis: Discovery prioritises fit so you try new things; Balanced prioritises fairness for competitive play.
FAQ
Is this an official Restoration Games tool?
No. This is an independent fan project and has no affiliation with Restoration Games. Unmatched is a trademark of Restoration Games.
Where does the win-rate data come from?
Win-rate estimates are compiled from community match data and public discussions. They are approximations , results will vary with player skill and strategy.
Can I share matchups with friends?
Yes! Just share the URL to this site. Select the same fighters and settings and you’ll get the same suggestions. No account required.
How do I report a bug or suggest a feature?
Open an issue on the GitHub repository. All feedback is welcome.
Who built this?
Built by Mohammad Machaka. The source code is open on GitHub.