Round 8 · 2023 · 18 Jun

Circuit Gilles Villeneuve

Montreal, Canada

Results & qualifying →

Race debrief

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Elo × qualifying → race result

Did they beat the expectation?

Experimental · v1
Model & data

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

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 620 earlier finishes across 37 races, 2013–2023. No results from this race enter its expectation.

20 stored results 20/20 Elo snapshots 20/20 numbered grid slots 0/20 qualifying results

Missing Elo or qualifying stays visible in the full grid. A grid position is not used as a qualifying result.

0/20 entrants have an estimate. Missing Elo or qualifying; see the full grid below.

Top 3

Beat the estimate

No comparable estimates available for this race yet.

Flop 3

Below the estimate

No comparable estimates available for this race yet.

0/20 entrants assessed. DNFs excluded. How we rank

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
M. VerstappenRed Bull #12650 — —No error range P1 — Not assessedQualifying unavailable
F. AlonsoAston Martin #52348 — —No error range P2 — Not assessedQualifying unavailable
L. HamiltonMercedes #32441 — —No error range P3 — Not assessedQualifying unavailable
C. LeclercFerrari #72298 — —No error range P4 — Not assessedQualifying unavailable
C. SainzFerrari #62341 — —No error range P5 — Not assessedQualifying unavailable
S. PérezRed Bull #22447 — —No error range P6 — Not assessedQualifying unavailable
A. AlbonWilliams #171998 — —No error range P7 — Not assessedQualifying unavailable
E. OconAlpine F1 Team #82221 — —No error range P8 — Not assessedQualifying unavailable
L. StrollAston Martin #102144 — —No error range P9 — Not assessedQualifying unavailable
V. BottasAlfa Romeo #162022 — —No error range P10 — Not assessedQualifying unavailable
O. PiastriMcLaren #152030 — —No error range P11 — Not assessedQualifying unavailable
P. GaslyAlpine F1 Team #92162 — —No error range P12 — Not assessedQualifying unavailable
L. NorrisMcLaren #112125 — —No error range P13 — Not assessedQualifying unavailable
Y. TsunodaAlphaTauri #122073 — —No error range P14 — Not assessedQualifying unavailable
N. HülkenbergHaas F1 Team #142037 — —No error range P15 — Not assessedQualifying unavailable
G. ZhouAlfa Romeo #132044 — —No error range P16 — Not assessedQualifying unavailable
K. MagnussenHaas F1 Team #191977 — —No error range P17 — Not assessedQualifying unavailable
N. de VriesAlphaTauri #181989 — —No error range P18 — Not assessedQualifying unavailable
G. RussellMercedes #42380 — —No error range DNFBrakes — Not assessedQualifying unavailable
L. SargeantWilliams #201911 — —No error range DNFEngine — Not assessedQualifying unavailable
How useful is the model? See the historical check

Average absolute error on 620 classified finishes in 37 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
2.10places
Qualifying only
2.31places
Elo only
2.54places

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 gain

Albon+44.3 Elo

Largest Elo loss

Russell−77.1 Elo

Largest grid-to-finish gain

Stroll+7 places

The bigger picture

Championship after this round

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

  1. 1 Verstappen 195pts 0
  2. 2 Pérez 126pts 0
  3. 3 Alonso 117pts 0
  4. 4 Hamilton 102pts 0
  5. 5 Sainz 68pts +1

Movement since round 7. 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.

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 →