Austrian Grand Prix 2026

GAS managed their MEDIUM tyres worse than the FP2 model predicted — by 141%

• ›FP2 model predicted 0.1207s/lap degradation on MEDIUM
• ›Actual race stint slope: 0.2913s/lap (Δ +0.1706s/lap)
• ›Over 12 laps, that compounds to ≈2.0s of less efficient pace vs the model's expectation

FP2 long-run data is the basis of the tyre degradation model. A 141% efficiency gap suggests either a meaningful setup change between Friday and Sunday, different thermal management in race conditions, or fuel load assumptions in FP that weren't representative of race pace.

If GAS's pace deficit in this stint was intentional, it will show up in their rolling form trend. If it was situational (traffic, thermal window, safety car), the model will not be recalibrated.

GAS managed their MEDIUM tyres worse than the FP2 model predicted — by 134%

• ›FP2 model predicted 0.1207s/lap degradation on MEDIUM
• ›Actual race stint slope: 0.2825s/lap (Δ +0.1618s/lap)
• ›Over 12 laps, that compounds to ≈1.9s of less efficient pace vs the model's expectation

FP2 long-run data is the basis of the tyre degradation model. A 134% efficiency gap suggests either a meaningful setup change between Friday and Sunday, different thermal management in race conditions, or fuel load assumptions in FP that weren't representative of race pace.

If GAS's pace deficit in this stint was intentional, it will show up in their rolling form trend. If it was situational (traffic, thermal window, safety car), the model will not be recalibrated.

FP2 long-run called 24% of race pace ranks correctly; RUS was the exception

• ›4 of 17 drivers finished within 3 positions of their FP2 long-run rank
• ›RUS: FP2 ranked P15, race result P1 (-14 positions)
• ›Best prediction match: VER — FP2 P2, actual P2

FP2 long-run data is the strongest single predictor of race pace (academic correlation ρ ≈ 0.67 vs race, strongest of any practice session). At 24% of the field within 3 positions, the model's practice-session intelligence is working as designed.

RUS's divergence from their FP2 signal is worth investigating: a meaningful gap between Friday pace and Sunday result suggests either a setup change between FP and race, a significant fuel load difference in long runs, or conditions that changed between sessions.

ANT improved consistently as the session progressed, benefiting from an evolving track surface — their best effort came as conditions peaked.

VER improved consistently as the session progressed, benefiting from an evolving track surface — their best effort came as conditions peaked.