2026 QEIv15™ Championship
QEIv15™ Championship 2026
Drivers Ranking
A physics-based performance ranking derived from race-state dynamics across the 2026 season. The QEIv15™ framework measures field control, stability, peak capability, and competitive conversion to identify the real performance hierarchy of the grid.
Built on QEIv15™ by Neoamorfic™. This championship view is part of the broader Neoamorfic™ intelligence ecosystem.
Season ranking
Top 10 drivers in the QEIv15™ Championship 2026.
Season-wide structural ranking
Drivers ordered by underlying competitive architecture across completed rounds.
| Physics rank | Driver | Team | QEIv15™ score |
|---|---|---|---|
| 1 | RUS | Mercedes | 86.48 |
| 2 | ANT | Mercedes | 83.67 |
| 3 | HAM | Ferrari | 79.55 |
| 4 | LEC | Ferrari | 76.48 |
| 5 | NOR | McLaren | 71.58 |
| 6 | BEA | Haas F1 Team | 66.56 |
| 7 | BOR | Audi | 65.62 |
| 8 | GAS | Alpine | 62.14 |
| 9 | HAD | Red Bull Racing | 54.72 |
| 10 | LIN | Racing Bulls | 53.37 |
Showing top 10.
Race-level snapshots
Example event-level rankings feeding the championship structure.
Australia 2026
Race-level physics ranking for Australia.
| Physics rank | Driver | Team | QEIv15™ score |
|---|---|---|---|
| 1 | RUS | Mercedes | 88.56 |
| 2 | ANT | Mercedes | 82.39 |
| 3 | HAM | Ferrari | 80.89 |
| 4 | VER | Red Bull Racing | 75.70 |
| 5 | LEC | Ferrari | 75.50 |
| 6 | NOR | McLaren | 71.58 |
| 7 | BEA | Haas F1 Team | 70.24 |
| 8 | LIN | Racing Bulls | 66.89 |
| 9 | BOR | Audi | 65.62 |
| 10 | OCO | Haas F1 Team | 59.09 |
Showing top 10.
China 2026
Race-level physics ranking for China.
| Physics rank | Driver | Team | QEIv15™ score |
|---|---|---|---|
| 1 | ANT | Mercedes | 84.94 |
| 2 | RUS | Mercedes | 84.40 |
| 3 | HAM | Ferrari | 78.21 |
| 4 | LEC | Ferrari | 77.45 |
| 5 | GAS | Alpine | 65.47 |
| 6 | BEA | Haas F1 Team | 62.87 |
| 7 | HAD | Red Bull Racing | 54.72 |
| 8 | LIN | Racing Bulls | 39.84 |
| 9 | LAW | Racing Bulls | 39.72 |
| 10 | BOT | Cadillac | 34.91 |
Showing top 10.
Why this matters
Championship intelligence should show more than points accumulation.
Structural reality
The championship reveals underlying competitive order, not only visible table position.
Pressure conversion
It helps identify which drivers convert control and stability into actual race outcomes.
Decision support
It supports executive review, performance assessment, and future live intelligence systems.
Additional modules
Further championship layers will be added as the season expands.
Constructor structure
Team-level structural ranking derived from race-state performance architecture.
Coming soon
Driver trajectory
Season-shape evolution for each driver across stability, control, and conversion.
Coming soon
Competitive divergence
Measurement of where visible championship order diverges from structural race reality.
Coming soon