2025 United States Grand Prix

Sprint Race
October 18, 2025

Changelog

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Version 1.0.2 Minor Update

October 23, 2025

Frontend

  • [Improved] Misc styling changes.
  • [Improved] About page explaining how calculations are made.

Algorithm

  • No changes.

Version 1.0.1 Minor Update

October 06, 2025

Frontend

  • [Added] Country flags for drivers & constructors.
  • [Added] About button in menu.
  • [Added] Changelog button in menu.
  • [Added] Displaying total calculations on homepage footer, and per-race calculations count on race results pages.
  • [Improved] Event search menu design.
  • [Improved] Hamburger menu design.
  • [Fixed] Removed empty sprint qualifying & sprint shootout from search results.

Algorithm

  • [Added] Historical weighting to team performance for stability.
  • [Added] Raw vs. modified ELO logging for auditing.
  • [Fixed] Enforced zero-cap on DNF ELO changes to prevent positive gains.

Version 1.0.0 Initial Release

October 02, 2025

  • Initial release with driver rankings and race results.
๐Ÿ“ˆ
DRIVER OF THE DAY
Liam LAWSON
Liam LAWSON
Position: 9
+17.8
๐Ÿ“‰
BIGGEST DROP
Lando NORRIS
Lando NORRIS
Position: DNF
-10.4
Pos Driver Team Rating Change New Rating Modifiers
1
Max VERSTAPPEN ๐Ÿ‡ณ๐Ÿ‡ฑ Max VERSTAPPEN
๐Ÿ‡ฆ๐Ÿ‡น Red Bull Racing +6.4 2117
Perf Weight +13%Reliability +3%Team Exp +40%Podium Bonus
2
George RUSSELL ๐Ÿ‡ฌ๐Ÿ‡ง George RUSSELL
๐Ÿ‡ฉ๐Ÿ‡ช Mercedes +9.6 2026
Perf Weight +13%Reliability +3%Team Exp +40%Podium Bonus
3
Carlos SAINZ ๐Ÿ‡ช๐Ÿ‡ธ Carlos SAINZ
๐Ÿ‡ฌ๐Ÿ‡ง Williams +12.6 1920
Perf Weight +13%Reliability +3%Team Exp +25%Podium Bonus
4
Lewis HAMILTON ๐Ÿ‡ฌ๐Ÿ‡ง Lewis HAMILTON
๐Ÿ‡ฎ๐Ÿ‡น Ferrari +9.2 1921
Perf Weight +13%Reliability +3%Team Exp +9%Points Finish
5
Charles LECLERC ๐Ÿ‡ฒ๐Ÿ‡จ Charles LECLERC
๐Ÿ‡ฎ๐Ÿ‡น Ferrari +3.0 2042
Perf Weight +13%Reliability +3%Team Exp -9%Points Finish
6
Alexander ALBON ๐Ÿ‡น๐Ÿ‡ญ Alexander ALBON
๐Ÿ‡ฌ๐Ÿ‡ง Williams +10.5 1738
Perf Weight +13%Reliability +3%Team Exp -25%Points Finish
7
Yuki TSUNODA ๐Ÿ‡ฏ๐Ÿ‡ต Yuki TSUNODA
๐Ÿ‡ฆ๐Ÿ‡น Red Bull Racing +10.3 1573
Perf Weight +13%Reliability +3%Team Exp -40%Points Finish
8
Kimi ANTONELLI ๐Ÿ‡ฎ๐Ÿ‡น Kimi ANTONELLI
๐Ÿ‡ฉ๐Ÿ‡ช Mercedes +5.8 1639
Perf Weight +13%Reliability +3%Team Exp -40%Points Finish
9
Liam LAWSON ๐Ÿ‡ณ๐Ÿ‡ฟ Liam LAWSON
๐Ÿ‡ฎ๐Ÿ‡น Racing Bulls +17.8 1645
Perf Weight +13%Reliability +3%Team Exp +31%Points Finish
10
Pierre GASLY ๐Ÿ‡ซ๐Ÿ‡ท Pierre GASLY
๐Ÿ‡ซ๐Ÿ‡ท Alpine +6.6 1663
Perf Weight +13%Reliability +3%Team Exp +40%Points Finish
11
Gabriel BORTOLETO ๐Ÿ‡ง๐Ÿ‡ท Gabriel BORTOLETO
๐Ÿ‡จ๐Ÿ‡ญ Kick Sauber +5.9 1572
Perf Weight +13%Reliability +3%Team Exp +25%Finish Bonus
12
Isack HADJAR ๐Ÿ‡ซ๐Ÿ‡ท Isack HADJAR
๐Ÿ‡ฎ๐Ÿ‡น Racing Bulls -2.0 1694
Perf Weight +13%Reliability +3%Team Exp -31%Finish Bonus
13
Nico HULKENBERG ๐Ÿ‡ฉ๐Ÿ‡ช Nico HULKENBERG
๐Ÿ‡จ๐Ÿ‡ญ Kick Sauber -2.6 1707
Perf Weight +13%Reliability +3%Team Exp -25%Finish Bonus
14
๐Ÿ‡ฆ๐Ÿ‡ท Franco COLAPINTO
๐Ÿ‡ซ๐Ÿ‡ท Alpine -0.5 1536
Perf Weight +13%Reliability +3%Team Exp -40%Finish Bonus
15
Oliver BEARMAN ๐Ÿ‡ฌ๐Ÿ‡ง Oliver BEARMAN
๐Ÿ‡บ๐Ÿ‡ธ Haas F1 Team -3.3 1593
Perf Weight +13%Reliability +3%Finish Bonus
DNF
Esteban OCON ๐Ÿ‡ซ๐Ÿ‡ท Esteban OCON
๐Ÿ‡บ๐Ÿ‡ธ Haas F1 Team -3.0 1646
Perf Weight +13%Reliability -32%Team Exp -20%DNF Penalty15 laps
DNF
Lance STROLL ๐Ÿ‡จ๐Ÿ‡ฆ Lance STROLL
๐Ÿ‡ฌ๐Ÿ‡ง Aston Martin -4.5 1637
Perf Weight +13%Reliability -24%DNF Penalty15 laps
DNF
Lando NORRIS ๐Ÿ‡ฌ๐Ÿ‡ง Lando NORRIS
๐Ÿ‡ฌ๐Ÿ‡ง McLaren -10.4 2047
Perf Weight +13%Reliability -30%DNF Penalty
DNF
Oscar PIASTRI ๐Ÿ‡ฆ๐Ÿ‡บ Oscar PIASTRI
๐Ÿ‡ฌ๐Ÿ‡ง McLaren -9.8 2005
Perf Weight +13%Reliability -30%DNF Penalty
DNF
Fernando ALONSO ๐Ÿ‡ช๐Ÿ‡ธ Fernando ALONSO
๐Ÿ‡ฌ๐Ÿ‡ง Aston Martin -6.6 1710
Perf Weight +13%Reliability -30%DNF Penalty

Event Search

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About DRS

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Dynamic Rating System (DRS)

DRS is an ELO-inspired rating engine for motorsports racing. It measures how far a driver exceeds or falls short of expectations in every race โ€” not just who wins, but how much better (or worse) they did than their car, form, and rivals suggest they should have.

1. Expected Performance

For every driver in the race, we calculate their expected win probability against every other driver using the classic ELO formula:

Expected = 1 / (1 + 10(OpponentElo - MyElo)/400)

Then average all those expected scores โ†’ this is what the driver โ€œshouldโ€ have achieved based purely on current skill rating.

In Simple Terms: โ€œIf Max has 2000 Elo and Zhou has 1400, Max is expected to beat Zhou ~91% of the time. We do this for every pair in the race and average it. Thatโ€™s the bar the driver has to clear.โ€

2. Actual Performance

Turns finishing position into a 0โ€“1 score:

  • Normalized = (total drivers - position) / (total - 1) โ†’ P1 = 1.0, last = 0.0
  • Score = Normalized^1.2 (slightly rewards higher finishes more)
  • Points bonus: P1โ€“P10 get up to +0.3 extra
  • Teammate beat: +0.10 (backmarker teams get +0.05 extra)
  • Finish multiplier: ร—1.05 for finishing
  • DNF: 0.1 + (laps completed / 60) ร— 0.3 ร— team reliability factor
In Simple Terms: โ€œP1 isnโ€™t just โ€˜1stโ€™, itโ€™s a near-perfect score. Beating your teammate? Extra credit. Crashing out on lap 1? Barely any points. Finishing lap 50 of 60? You get partial credit โ€” not zero.โ€

3. Performance Difference

Diff = Actual Score โ€“ Expected Score

Positive = outperformed expectations. Negative = underperformed.

In Simple Terms: โ€œDid the driver do better than their rating said they would? Thatโ€™s the gap we care about.โ€

4. Dynamic K-Factor (Learning Rate)

Base = 28. Then adjusted:

  • High Elo (>1900) โ†’ ร—0.7 (slow learning)
  • Low Elo (<1400) โ†’ ร—1.4 (fast learning)
  • Podium โ†’ ร—1.4 | P4โ€“P10 โ†’ ร—1.2 | Back of grid โ†’ ร—1.1
  • Smaller field โ†’ lower K | Tighter competition โ†’ higher K

Final K clamped between 15 and 45.

In Simple Terms: โ€œRookies and backmarkers change rating faster. A podium in a chaotic race? Big swing. A veteran cruising to P8? Small tweak.โ€

5. Modifiers

  • Race Weight (1.0โ€“1.5): Bigger fields, closer Elo spread, more top drivers โ†’ more important race โ†’ bigger Elo swings.
  • Reliability Factor: DNF โ†’ ~0.7โ€“0.9 (less penalty if car is unreliable or many laps done). Finish โ†’ ร—1.03.
  • Team Expectation: Did you beat your teamโ€™s average? Sigmoid curve gives 0.6โ€“1.4ร— boost/penalty.
In Simple Terms: โ€œA DNF in a fragile car hurts less. Beating your teammate when both cars are slow? Thatโ€™s huge. Crashing a bulletproof Red Bull? Ouch.โ€

6. Intelligent Capping

  • Standard: ยฑ25 Elo
  • Backmarker upside โ†’ up to +30, downside only -15
  • DNF โ†’ no positive gain
  • Exceptional: (e.g. backmarker in P4) โ†’ up to +40
  • Catastrophic: (e.g. 1950 Elo driver P17) โ†’ down to -30
In Simple Terms: โ€œNo one jumps +100 for one miracle. But a Haas in the points? Thatโ€™s worth celebrating. A Ferrari in the wall? That stings โ€” but not endlessly.โ€

Full Calculation Flow (per driver)

  1. Build team strength (current + 60% historical)
  2. Expected = average win-probability vs all others
  3. Actual = position โ†’ score + bonuses
  4. Diff = Actual โ€“ Expected
  5. Raw Change = K ร— Diff
  6. Apply: Race Weight ร— Reliability ร— Team Expectation
  7. Cap intelligently โ†’ Final Elo change
In Simple Terms: โ€œItโ€™s not just โ€˜you finished P5โ€™. Itโ€™s: โ€˜You were expected to be P12 in that car. You beat your teammate. The car usually breaks. You finished. Hereโ€™s +32 Elo.โ€™โ€

Examples

Exceptional: Backmarker P4

Expected: 0.15 โ†’ Actual: 0.78 โ†’ Diff: +0.63 โ†’ K: 38 โ†’ Raw: +24 โ†’ Exceptional cap โ†’ +38 Elo

Catastrophic: Top driver P17

Expected: 0.82 โ†’ Actual: 0.12 โ†’ Diff: -0.70 โ†’ K: 22 โ†’ Raw: -15 โ†’ Catastrophic โ†’ -28 Elo

DNF with 42/66 laps

Actual: ~0.29 โ†’ Expected: 0.55 โ†’ Diff: -0.26 โ†’ K: 30 โ†’ Reliability: 0.84 โ†’ Final: -6 Elo

The Idea: Reward drivers for punching above their weight. Penalize underperformance โ€” but fairly, with context. The system learns and self-corrects over time.