Round 13 · 2015

Marina Bay Street Circuit

Marina Bay, Singapore · September 20, 2015 · Circuit History · Wikipedia

Kings of this circuit
The race, in perspective

Race debrief

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

R132015
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20 stored results 20/20 Elo snapshots 20/20 numbered grid slots 20/20 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 592 earlier finishes across 35 races, 2005–2015. No results from this race enter its expectation.

Top 3

Beat the estimate
  1. Carlos Sainz Toro Rosso · Elo #17 · Q14

    Expected P12.1 Finished P9

    +3.1places
  2. Sergio Pérez Force India · Elo #9 · Q13

    Expected P9.5 Finished P7

    +2.5places
  3. Daniel Ricciardo Red Bull · Elo #8 · Q2

    Expected P4.5 Finished P2

    +2.5places

Flop 3

Below the estimate
  1. Daniil Kvyat Red Bull · Elo #7 · Q4

    Expected P5.0 Finished P6

    −1.0places
  2. Max Verstappen Toro Rosso · Elo #11 · Q8

    Expected P7.9 Finished P8

    −0.1places

14/20 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 → P20vs expectedReading
S. VettelFerrari #22489 P1 P2.4P1–P6 P1 +1.4places In range
D. RicciardoRed Bull #82230 P2 P4.5P1–P9 P2 +2.5places In range
K. RäikkönenFerrari #62262 P3 P4.3P1–P8 P3 +1.3places In range
N. RosbergMercedes #32470 P6 P4.8P1–P9 P4 +0.8places In range
V. BottasWilliams #52340 P7 P5.8P2–P10 P5 +0.8places In range
D. KvyatRed Bull #72260 P4 P5.0P1–P9 P6 −1.0places In range
S. PérezForce India #92211 P13 P9.5P5–P14 P7 +2.5places In range
M. VerstappenToro Rosso #112118 P8 P7.9P4–P12 P8 −0.1places In range
C. SainzToro Rosso #172030 P14 P12.1P8–P16 P9 +3.1places In range
F. NasrSauber #142078 P16 P12.1P8–P16 P10 +2.1places In range
M. EricssonSauber #132100 P17 P12.3P8–P16 P11 +1.3places In range
P. MaldonadoLotus F1 #191932 P18 P14.4P10–P18 P12 +2.4places In range
R. GrosjeanLotus F1 #102122 P10 P8.5P4–P13 DNFTyre Not assessedDNF: Tyre
A. RossiManor Marussia #182000 P20 P15.0P11–P19 P14 +1.0places In range
W. StevensManor Marussia #201930 P19 P15.1P11–P19 P15 +0.1places In range
J. ButtonMcLaren #162038 P15 P12.3P8–P16 DNFGearbox Not assessedDNF: Gearbox
F. AlonsoMcLaren #152043 P12 P10.7P7–P15 DNFGearbox Not assessedDNF: Gearbox
L. HamiltonMercedes #12650 P5 P3.8P1–P8 DNFThrottle Not assessedDNF: Throttle
F. MassaWilliams #42367 P9 P6.4P2–P10 DNFGearbox Not assessedDNF: Gearbox
N. HülkenbergForce India #122112 P11 P9.4P5–P13 DNFCollision Not assessedDNF: Collision
How useful is the model? See the historical check

Average absolute error on 592 classified finishes in 35 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
2.42places
Qualifying only
2.63places
Elo only
2.93places

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 grid-to-finish gain

Pérez+6 places

The bigger picture

Championship after this round

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

  1. 1 Hamilton 252pts 0
  2. 2 Rosberg 211pts 0
  3. 3 Vettel 203pts 0
  4. 4 Räikkönen 107pts +1
  5. 5 Bottas 101pts +1

Movement since round 12. 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.

Mercedes

RosbergP4+5.0 Elo
HamiltonDNF−107.4 Elo

Non-finish recorded; no finishing gap comparison.

Q3 · Hamilton 0.115s faster

Williams

BottasP5+13.8 Elo
MassaDNF−87.1 Elo

Non-finish recorded; no finishing gap comparison.

Q3 · Bottas 0.401s faster

Sauber

NasrP10+19.7 Elo
EricssonP11+9.2 Elo

1 place apart at the finish.

Q1 · Nasr 0.123s faster

Lotus F1

MaldonadoP12+26.8 Elo
GrosjeanDNF−8.1 Elo

Non-finish recorded; no finishing gap comparison.

Q1 · Grosjean 0.463s faster

McLaren

ButtonDNF−15.9 Elo
AlonsoDNF−23.5 Elo

Non-finish recorded; no finishing gap comparison.

Q2 · Alonso 0.691s 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 →
20
Result Entries
Avg Elo
Highest Elo (Hamilton)
6
Non-finishes

Race

Qualifying

# Driver Grid +/- Points Season Pts Season # Elo Change Elo
P1 🇩🇪 S.Vettel 1 +25 203 P3 +23.8 2,513
P2 🇦🇺 D.Ricciardo 2 +18 73 P7 +51.0 2,281
P3 🇫🇮 K.Räikkönen 3 +15 107 P4 +39.1 2,301
P4 🇩🇪 N.Rosberg 6 +2 +12 211 P2 +5.0 2,475
P5 🇫🇮 V.Bottas 7 +2 +10 101 P5 +13.8 2,354
P6 🇷🇺 D.Kvyat 4 -2 +8 66 P8 +18.6 2,279
P7 🇲🇽 S.Pérez 13 +6 +6 39 P9 +19.3 2,230
P8 🇳🇱 M.Verstappen 8 +4 30 P11 +27.2 2,145
P9 🇪🇸 C.Sainz 14 +5 +2 11 P16 +34.0 2,064
P10 🇧🇷 F.Nasr 16 +6 +1 17 P13 +19.7 2,097
P11 🇸🇪 M.Ericsson 17 +6 0 9 P17 +9.2 2,109
P12 🇻🇪 P.Maldonado 18 +6 0 12 P14 +26.8 1,958
DNF 🇫🇷 R.Grosjean 10 0 38 P10 -8.1 2,113
P14 🇺🇸 A.Rossi 20 +6 0 0 P21 +3.6 2,004
P15 🇬🇧 W.Stevens 19 +4 0 0 P20 +6.1 1,936
DNF 🇬🇧 J.Button 15 0 6 P18 -15.9 2,022
DNF 🇪🇸 F.Alonso 12 0 11 P15 -23.5 2,019
DNF 🇬🇧 L.Hamilton 5 0 252 P1 -107.4 2,542
DNF 🇧🇷 F.Massa 9 0 97 P6 -87.1 2,280
DNF 🇩🇪 N.Hülkenberg 11 0 30 P12 -55.3 2,057
# Driver Q1 Q2 Q3 Gap Elo
1 🇩🇪 S.Vettel 1:46.017 1:44.743 1:43.885 1:43.885 2,156
2 🇦🇺 D.Ricciardo 1:46.166 1:45.291 1:44.428 +0.543 2,055
3 🇫🇮 K.Räikkönen 1:46.467 1:45.140 1:44.667 +0.782 2,029
4 🇷🇺 D.Kvyat 1:45.340 1:44.979 1:44.745 +0.86 2,171
5 🇬🇧 L.Hamilton 1:45.765 1:45.650 1:45.300 +1.415 2,437
6 🇩🇪 N.Rosberg 1:46.201 1:45.653 1:45.415 +1.53 2,617
7 🇫🇮 V.Bottas 1:46.231 1:45.887 1:45.676 +1.791 1,862
8 🇳🇱 M.Verstappen 1:46.483 1:45.635 1:45.798 +1.913 2,335
9 🇧🇷 F.Massa 1:46.879 1:45.701 1:46.077 +2.192 2,196
10 🇫🇷 R.Grosjean 1:46.860 1:45.805 1:46.413 +2.528 1,931
11 🇩🇪 N.Hülkenberg 1:46.669 1:46.305 +2.42 2,099
12 🇪🇸 F.Alonso 1:46.600 1:46.328 +2.443 2,002
13 🇲🇽 S.Pérez 1:46.576 1:46.385 +2.5 1,955
14 🇪🇸 C.Sainz 1:46.465 1:46.894 +3.009 2,061
15 🇬🇧 J.Button 1:45.891 1:47.019 +3.134 2,016
16 🇧🇷 F.Nasr 1:46.965 +3.08 2,014
17 🇸🇪 M.Ericsson 1:47.088 +3.203 2,009
18 🇻🇪 P.Maldonado 1:47.323 +3.438 2,068
19 🇬🇧 W.Stevens 1:51.021 +7.136 1,892
20 🇺🇸 A.Rossi 1:51.523 +7.638 1,976
Data: Jolpica (Ergast) API

Elo Changes