Experimental AI-assisted analytics, predictions and ratings are estimates, not official results.

Insights

Derived from 11,160 matches across 247 processed 2026 events · TBA data · APEX APEX · updated 2026-07-20 23:49 UTC

FRCinsights uses AI-assisted experimental analytics. Predictions, rankings, ratings, and insights are not guaranteed to be accurate and should not be treated as official results or professional advice. Data may be incomplete, delayed, miscategorized, or incorrect. FRCinsights is a new project under active development, and accuracy will improve over time.

Top APEX teams

Highest overall estimated contribution.

  1. 11690Orbit442.4apex
  2. 2254The Cheesy Poofs437.9apex
  3. 31114Simbotics423.1apex
  4. 44414HighTide418.9apex
  5. 51323MadTown Robotics409.1apex
  6. 61678Citrus Circuits409.1apex
  7. 72056OP Robotics404.1apex
  8. 827Team RUSH396.1apex
  9. 96329The Bucks' Wrath391.8apex
  10. 107769The CREW385.4apex

Fastest improving

Largest positive momentum vs season baseline.

  1. 12367Lancer Robotics541.5mom
  2. 22262Robo-Panthers463.5mom
  3. 35454Obsidian437.5mom
  4. 44509Mechanical Bulls435.5mom
  5. 57907Spartan Robotics434mom
  6. 610043Conscius Robotics428mom
  7. 74065Nerds of Prey427mom
  8. 82383Ninjineers426.5mom
  9. 95538Vikingbots415.5mom
  10. 105010Tiger Dynasty409mom

Most consistent

Lowest match-to-match variance among rated teams.

  1. 1818The Steel Armadillos72cons
  2. 22231OnyxTronix70cons
  3. 31073The Force Team69cons
  4. 42137The Oxford RoboCats66cons
  5. 510002BotBuilders66cons
  6. 66152Robo-Falcons64cons
  7. 71498The Polar Pilots64cons
  8. 81038Lakota Robotics64cons
  9. 95193Pantheon63cons
  10. 102181GEARS61cons

Strongest events

Events with the highest top-end APEX field.

  1. 1Galileo Division265.9
  2. 2Curie Division265
  3. 3Hopper Division260.4
  4. 4Daly Division255.1
  5. 5Newton Division247.6
  6. 6FIRST California Northern State Championship247.6
  7. 7Archimedes Division244.9
  8. 8Milstein Division239.1

Data-quality warnings

68 rated teams currently fall below the reliable-sample threshold.

Model limitations

What these insights cannot yet tell you.

  • Contributions are statistical estimates, not measured robot capabilities.
  • Early-season teams may have too few matches for a stable rating.
  • Defense and specific game tasks are inferred indirectly from scores.
  • Upsets reflect rating gaps, not narrative or mechanical context.