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

Insights

Derived from 10,087 matches across 189 processed 2026 events · TBA data · APEX APEX · updated 2026-06-30 22:44 UTC

predictFRC 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. predictFRC is a new project under active development, and accuracy will improve over time.

Top APEX teams

Highest overall estimated contribution.

  1. 11690Orbit452.5apex
  2. 24414HighTide371.6apex
  3. 31678Citrus Circuits363apex
  4. 49483Overcharge348apex
  5. 5254The Cheesy Poofs341.3apex
  6. 61323MadTown Robotics325.9apex
  7. 727Team RUSH319.7apex
  8. 87769The CREW313.7apex
  9. 92056OP Robotics313.1apex
  10. 102481Roboteers304apex

Fastest improving

Largest positive momentum vs season baseline.

  1. 111387G.L.E.A.M. - Grass Lake Engineering and Mechanics384.5mom
  2. 22877LigerBots334.5mom
  3. 32491NoMythic327.5mom
  4. 46940Violet Z320.5mom
  5. 59738Ionic Bond309mom
  6. 63959Mech Tech307.5mom
  7. 75104BreakerBots293.5mom
  8. 88145Tech Warriors293mom
  9. 9503Frog Force292.5mom
  10. 102708Lake Effect Robotics291mom

Most consistent

Lowest match-to-match variance among rated teams.

  1. 110452RoboLions63cons
  2. 2308Monsters62cons
  3. 310234TEDRA62cons
  4. 44085Technical Difficulties61cons
  5. 52227Tigers61cons
  6. 610935Krono60cons
  7. 710553Orange Overdrive60cons
  8. 81884Griffins60cons
  9. 911118The Baybies58cons
  10. 102068Metal Jackets58cons

Strongest events

Events with the highest top-end APEX field.

  1. 1Curie Division276.7
  2. 2Hopper Division274.5
  3. 3Galileo Division273.4
  4. 4Newton Division266.3
  5. 5Daly Division259.9
  6. 6Archimedes Division246.7
  7. 7Johnson Division246.2
  8. 8Milstein Division242.7

Data-quality warnings

0 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.