Round 14 · 2013

Korean International Circuit

Yeongam County, Korea · October 06, 2013 · Circuit History · Wikipedia

Kings of this circuit
The race, in perspective

Race debrief

What did we expect after qualifying—and who beat it?

R142013
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22 stored results 22/22 Elo snapshots 22/22 numbered grid slots 22/22 qualifying results
Elo × qualifying → race result

Did they beat the expectation?

A strong driver recovering from a poor qualifying position isn't automatically a surprise. This model estimates a finish from both inputs, then compares it with what happened.

Experimental · v1

Expected finish assumes a classified finish. DNFs stay in the full grid but receive no performance verdict. Qualifying is not the starting grid; grid differences are flagged, not silently substituted.

Fit on 556 earlier finishes across 34 races, 2004–2013. No results from this race enter its expectation.

Top 3

Beat the estimate
  1. Kimi Räikkönen Lotus F1 · Elo #4 · Q10

    Expected P6.9 Finished P2

    +4.9places
  2. Nico Hülkenberg Sauber · Elo #9 · Q8

    Expected P7.4 Finished P4

    +3.4places
  3. Romain Grosjean Lotus F1 · Elo #11 · Q4

    Expected P6.2 Finished P3

    +3.2places

Flop 3

Below the estimate
  1. Daniel Ricciardo Toro Rosso · Elo #13 · Q13

    Expected P10.5 Finished P19

    −8.5places
  2. Jean-Éric Vergne Toro Rosso · Elo #18 · Q16

    Expected P13.1 Finished P18

    −4.9places
  3. Felipe Massa Ferrari · Elo #8 · Q7

    Expected P6.7 Finished P9

    −2.3places

19/22 entrants assessed. Up to three per side, ranked by expected minus actual finish. DNFs, missing estimates and gaps rounding to 0.0 are excluded. “Flop” means below the model's estimate—not poor driving. A ranked gap can still be inside the usual error range.

Full grid: pre-race Elo rank, qualifying position, estimated finish, actual result and difference from expectation. Positive differences mean finishing ahead of the estimate.
DriverPre-race EloQualifyingExpectedResultP1 ← position → P22vs expectedReading
S. VettelRed Bull #12543 P1 P2.3P1–P7 P1 +1.3places In range
K. RäikkönenLotus F1 #42361 P10 Grid P9 P6.9P2–P12 P2 +4.9places In range
R. GrosjeanLotus F1 #112143 P4 Grid P3 P6.2P2–P11 P3 +3.2places In range
N. HülkenbergSauber #92190 P8 Grid P7 P7.4P3–P12 P4 +3.4places In range
L. HamiltonMercedes #32413 P2 P3.3P1–P8 P5 −1.7places In range
F. AlonsoFerrari #22506 P6 Grid P5 P4.7P1–P9 P6 −1.3places In range
N. RosbergMercedes #62313 P5 Grid P4 P5.3P1–P10 P7 −1.7places In range
J. ButtonMcLaren #72293 P12 Grid P11 P8.6P4–P13 P8 +0.6places In range
F. MassaFerrari #82293 P7 Grid P6 P6.7P2–P11 P9 −2.3places In range
S. PérezMcLaren #102174 P11 Grid P10 P8.9P4–P14 P10 −1.1places In range
E. GutiérrezSauber #162025 P9 Grid P8 P9.6P5–P14 P11 −1.4places In range
V. BottasWilliams #152030 P17 P12.8P8–P17 P12 +0.8places In range
P. MaldonadoWilliams #142066 P18 P12.9P8–P18 P13 −0.1places In range
C. PicCaterham #211900 P19 P15.2P10–P20 P14 +1.2places In range
G. van der GardeCaterham #191926 P20 P15.1P10–P20 P15 +0.1places In range
J. BianchiMarussia #201908 P21 Grid P22 P15.7P11–P20 P16 −0.3places In range
M. ChiltonMarussia #221898 P22 Grid P21 P16.7P12–P21 P17 −0.3places In range
J. VergneToro Rosso #182013 P16 P13.1P8–P18 P18 −4.9places In range
D. RicciardoToro Rosso #132093 P13 Grid P12 P10.5P6–P15 P19 −8.5places Below range
A. SutilForce India #122125 P14 P10.7P6–P15 DNFCollision Not assessedDNF: Collision
M. WebberRed Bull #52352 P3 Grid P13 P4.2P1–P9 DNFCollision Not assessedDNF: Collision
P. di RestaForce India #172015 P15 P12.4P8–P17 DNFSpun off Not assessedDNF: Spun off
How useful is the model? See the historical check

Average absolute error on 556 classified finishes in 34 earlier races within the last ten years. Each race was held out and predicted using only older races; all three models use the same samples.

Elo + qualifying
2.61places
Qualifying only
2.76places
Elo only
3.11places

The range scales the 80th percentile of earlier held-out absolute errors to this field size, rounding outward. It is an empirical error guide, not a guaranteed 80% chance for a particular driver. We require at least five checked races and 100 checked finishes before showing it.

Inputs are field-normalised Elo rank and qualifying position. The target is position among all race entries, trained only on classified finishers. Estimates are averages, not a unique predicted finishing order. Penalties, the circuit, weather, incidents and strategy aren't model inputs. Historical qualifying coverage is patchy; this is an exploratory backtest on corrected records, not proof of live forecasting accuracy.

The rating ledger

What changed in Elo?

These are actual rating changes. The expectation model above does not change Elo or fantasy scoring.

Largest Elo loss

Webber−92.8 Elo

The bigger picture

Championship after this round

Top five in the stored standings. Points include sprint results where applicable.

  1. 1 Vettel 272pts 0
  2. 2 Alonso 195pts 0
  3. 3 Räikkönen 167pts +1
  4. 4 Hamilton 161pts −1
  5. 5 Webber 130pts 0

Movement since round 13. A dash means the earlier standing is unavailable.

Explore the season →
Across the garage

Teammate results

Two-driver constructor entries from this race. A result comparison, not an adjustment for strategy or reliability.

Red Bull

VettelP1+17.8 Elo
WebberDNF−92.8 Elo

Non-finish recorded; no finishing gap comparison.

Q3 · Vettel 0.262s faster

Ferrari

AlonsoP6−11.8 Elo
MassaP9−4.9 Elo

3 places apart at the finish.

Q3 · Alonso 0.185s faster

McLaren

ButtonP8+1.7 Elo
PérezP10+7.2 Elo

2 places apart at the finish.

Q2 · Pérez 0.003s faster

Force India

SutilDNF−50.9 Elo
di RestaDNF−46.6 Elo

Non-finish recorded; no finishing gap comparison.

Q2 · Sutil 0.287s faster

What this analysis can—and cannot—tell you

This debrief is calculated from stored results and rating snapshots. The experimental expectation model learns from earlier races only, using Elo rank and qualifying together; it never feeds back into Elo. It is not a separately reviewed race report.

Elo uses the result order, including retirements. It does not isolate driver skill from the car, reliability, penalties or strategy. Elo seed comparisons use pre-race ratings, never today's ratings. Equal ratings share the midpoint of their rank range (for example, tied first and second become seed 1.5).

Grid gains use numbered starting slots and classified finishes only. Zero or missing grid values are excluded; a position gained is not necessarily an overtake. Qualifying gaps use the latest segment both teammates have a valid time for, never Q1 against Q3.

Lap-by-lap pace, tyre stints, pit-stop execution and safety-car effects are not available in this report. Missing data is omitted, not inferred.

Read the Elo methodology →
22
Result Entries
Avg Elo
Highest Elo (Vettel)
3
Non-finishes

Race

Qualifying

# Driver Grid +/- Points Season Pts Season # Elo Change Elo
P1 🇩🇪 S.Vettel 1 +25 272 P1 +17.8 2,561
P2 🇫🇮 K.Räikkönen 9 +7 +18 167 P3 +31.7 2,393
P3 🇫🇷 R.Grosjean 3 +15 72 P8 +58.5 2,202
P4 🇩🇪 N.Hülkenberg 7 +3 +12 31 P11 +44.2 2,235
P5 🇬🇧 L.Hamilton 2 -3 +10 161 P4 +5.1 2,418
P6 🇪🇸 F.Alonso 5 -1 +8 195 P2 -11.8 2,494
P7 🇩🇪 N.Rosberg 4 -3 +6 122 P6 +5.4 2,318
P8 🇬🇧 J.Button 11 +3 +4 58 P9 +1.7 2,295
P9 🇧🇷 F.Massa 6 -3 +2 89 P7 -4.9 2,288
P10 🇲🇽 S.Pérez 10 +1 23 P13 +7.2 2,181
P11 🇲🇽 E.Gutiérrez 8 -3 0 0 P17 +24.7 2,050
P12 🇫🇮 V.Bottas 17 +5 0 0 P18 +17.3 2,047
P13 🇻🇪 P.Maldonado 18 +5 0 1 P16 +5.0 2,071
P14 🇫🇷 C.Pic 19 +5 0 0 P20 +22.7 1,923
P15 🇳🇱 G.van der Garde 20 +5 0 0 P21 +12.7 1,939
P16 🇫🇷 J.Bianchi 22 +6 0 0 P19 +8.5 1,916
P17 🇬🇧 M.Chilton 21 +4 0 0 P22 +3.2 1,901
P18 🇫🇷 J.Vergne 16 -2 0 13 P15 -19.8 1,993
P19 🇦🇺 D.Ricciardo 12 -7 0 18 P14 -39.1 2,054
DNF 🇩🇪 A.Sutil 14 0 26 P12 -50.9 2,074
DNF 🇦🇺 M.Webber 13 0 130 P5 -92.8 2,259
DNF 🇬🇧 P.di Resta 15 0 36 P10 -46.6 1,969
# Driver Q1 Q2 Q3 Gap Elo
1 🇩🇪 S.Vettel 1:38.683 1:37.569 1:37.202 1:37.202 2,156
2 🇬🇧 L.Hamilton 1:38.574 1:37.824 1:37.420 +0.218 2,437
3 🇦🇺 M.Webber 1:39.138 1:37.840 1:37.464 +0.262 2,350
4 🇫🇷 R.Grosjean 1:39.065 1:38.076 1:37.531 +0.329 1,931
5 🇩🇪 N.Rosberg 1:38.418 1:38.031 1:37.679 +0.477 2,617
6 🇪🇸 F.Alonso 1:38.520 1:37.978 1:38.038 +0.836 2,002
7 🇧🇷 F.Massa 1:38.884 1:38.295 1:38.223 +1.021 2,196
8 🇩🇪 N.Hülkenberg 1:38.427 1:37.913 1:38.237 +1.035 2,099
9 🇲🇽 E.Gutiérrez 1:38.725 1:38.327 1:38.405 +1.203 2,002
10 🇫🇮 K.Räikkönen 1:38.341 1:38.181 1:38.822 +1.62 2,029
11 🇲🇽 S.Pérez 1:39.049 1:38.362 +1.16 1,955
12 🇬🇧 J.Button 1:38.882 1:38.365 +1.163 2,016
13 🇦🇺 D.Ricciardo 1:38.525 1:38.417 +1.215 2,055
14 🇩🇪 A.Sutil 1:38.988 1:38.431 +1.229 1,925
15 🇬🇧 P.di Resta 1:39.185 1:38.718 +1.516 2,055
16 🇫🇷 J.Vergne 1:39.075 1:38.781 +1.579 2,141
17 🇫🇮 V.Bottas 1:39.470 +2.268 1,862
18 🇻🇪 P.Maldonado 1:39.987 +2.785 2,068
19 🇫🇷 C.Pic 1:40.864 +3.662 1,850
20 🇳🇱 G.van der Garde 1:40.871 +3.669 1,866
21 🇫🇷 J.Bianchi 1:41.169 +3.967 1,926
22 🇬🇧 M.Chilton 1:41.322 +4.12 1,870
Data: Jolpica (Ergast) API

Elo Changes