In FTC (FIRST Tech Challenge) competition, alliance selection is one of the highest-leverage decisions of the event. After qualification rounds, the top-ranked teams pick alliance partners — two additional robots to compete in elimination rounds. You have roughly three minutes to decide.
The naive approach is to sort by raw match score. But raw scores are deeply confounded: a robot that consistently scores 40 points alongside a partner who scores 60 looks identical in the rankings to a robot that scores 40 while carrying a partner who scores 20. These robots are fundamentally different — but the number is the same.
"A robot that carries a weak partner to 40 points is worth more than a robot that coasts to 40 behind a strong one. Raw scores can't tell you which you're looking at."
OPR (Offensive Power Rating) is the standard metric that separates team contribution from partner contribution using the full qualification dataset. The calculation is a system of linear equations — one per match — where each team's individual contribution is the unknown. Solved via Gaussian elimination.
But OPR has its own weakness: small sample sizes. With only 6–10 matches per team in a typical regional event, OPR estimates are noisy. A team that played strong opponents who scored 30 looks worse than a team that carried weak partners to the same number. The variance swamps the signal. ScoutSelect fixes both problems.
Six distinct systems working in concert. Each one exists because a specific failure mode in conventional scouting demanded a specific fix.
Live mock simulation — same algorithms, fake teams. Regenerates every 12 seconds. This is what runs on the competition floor.
| Rank | Team | OPR | Role | Auto | Teleop | EG |
|---|
ScoutSelect wasn't built as a demo. It was deployed at actual FTC competitions during the 2025–26 season.
During the 3-minute alliance selection window at California Invitational 2025, ScoutSelect was running live on the competition floor. The platform identified pick order in real time and flagged two teams whose raw scores substantially understated their actual per-robot contribution — teams that a simple sort-by-score approach would have missed entirely.
Those picks became part of the Champion Alliance run that made Team IK19859 the first Chinese team to reach Champion Alliance at that event. The platform didn't just theoretically work — it influenced decisions in an actual elimination bracket.
"The math has to be right and it has to be fast. You can't explain Bayesian shrinkage to a teammate during a 3-minute clock. It just has to produce the right answer."
The platform is live at scoutselect.org and available for any FTC team to use. Developed in full by George Hu under Team IK19859.
Three things this platform demonstrates — for any interviewer asking whether this is rigorous engineering or weekend scripting.
Robotics · Research · Rowing · Debate · All work.
Control systems lead. World Championship qualifier. The full robotics story.
Adaptive layer routing for energy-efficient local LLM inference.