Most DNFs Per Track

Circuit-specific mechanical attrition reveals which venues place the greatest stress on Formula 1 machinery. High-speed layouts demand sustained aerodynamic load and maximum powertrain output, testing cooling system capacity and component durability over race distance. Street circuits with barrier proximity and minimal run-off punish positioning errors and contact incidents with immediate retirement. Tracks with severe elevation changes, high-frequency direction switches, or extended full-throttle sections expose weaknesses in suspension geometry, brake thermal management, and power unit reliability.

Retirement rates aggregate DNFs, DNS (did not start), and DSQ (disqualifications) to quantify how many cars fail to reach the chequered flag. Elevated attrition suggests a venue either mechanically challenges the cars through physical demands or generates incidents through layout characteristics that increase contact probability. Understanding which circuits produce higher failure rates provides insight into engineering priorities, where teams accept calculated risk, and which venues demand conservative setup approaches to ensure race completion.

Top circuit

Melbourne

5.5 · avg dnf + dns + dsq

All-circuit average

2.7

Avg DNF + DNS + DSQ

Races analyzed

80

across 24 circuits

Average retirements per race by circuit

Avg DNF + DNS + DSQ
  1. 1 Melbourne 5.5
  2. 2 Interlagos 4.7
  3. 3 Shanghai 4.7
  4. 4 Lusail 4.0
  5. 5 Mexico City 4.0
  6. 6 Montréal 4.0
  7. 7 Monaco 3.8
  8. 8 Silverstone 3.2
  9. 9 Las Vegas 2.7
  10. 10 Suzuka 2.5
  11. 11 Baku 2.3
  12. 12 Barcelona 2.2
  13. 13 Miami 2.2
  14. 14 Spielberg 2.2
  15. 15 Jeddah 2.0
  16. 16 Marina Bay 2.0
  17. 17 Zandvoort 2.0
  18. 18 Austin 1.7
  19. 19 Budapest 1.7
  20. 20 Monza 1.7
  21. 21 Sakhir 1.7
  22. 22 Yas Island 1.7
  23. 23 Imola 1.5
  24. 24 Spa-Francorchamps 1.5

Grands Prix from 2023 to 2026, sprints excluded. The “R” count shows how many races at that circuit are in the sample. Seasons prior to 2023 are not included in this dataset.