# Project F1 — Singapore Grand Prix 2026 | Post-race results and director handoff

**Event:** Singapore Grand Prix, Marina Bay — 11 October 2026  
**Trial:** Race **3 of 3 completed** (mixed allocation policies: Baku A-1.3; Sepang and Singapore A-1.4.x barbell)  
**Prediction model:** Price-blind **v1.3.0 team-aware**, 500,000 simulations, master seed `20261010`  
**Race and two purchased Top-10 outcomes:** Confirmed. **All four economic results can be determined from the race winner and purchased payout terms.**

## 1. Official race classification (publishable)

| Finish | Driver | Team |
|---:|---|---|
| **1** | **Max Verstappen** | Red Bull Racing |
| **2** | **Charles Leclerc** | Ferrari |
| **3** | **Kimi Antonelli** | Mercedes |
| 4 | Lando Norris | McLaren |
| 5 | Oscar Piastri | McLaren |
| 6 | Lewis Hamilton | Ferrari |
| 7 | Liam Lawson | Racing Bulls |
| 8 | Nico Hülkenberg | Audi |
| 9 | George Russell | Mercedes |
| 10 | Isack Hadjar | Red Bull Racing |

Official classification: https://www.formula1.com/en/results/2026/races/1296/singapore/race-result

Verstappen won from pole, 7.335 seconds ahead of Leclerc, with Antonelli third. The full top-ten order above comes from the official race classification. The race report notes a late VSC/strategy decision contributed to Hamilton falling to sixth; do not assert that the model forecast this incident. Race report: https://www.formula1.com/en/latest/article/verstappen-seals-commanding-singapore-grand-prix-victory-from-leclerc-and-antonelli.49wDzysiVqi5cloGjle40A

## 6. Public-facing editorial summary

**Suggested headline:** *“Our model picked the winner. Our safer picks paid. The portfolio still lost a little.”*

**Public claims supported:** The model ranked Verstappen as its most likely winner after 500,000 Singapore simulations; he won. The actual podium was Verstappen, Leclerc and Antonelli. The barbell portfolio held Verstappen and Antonelli Top-10 YES (both paid) alongside Hamilton and Leclerc Winner YES (both lost). It was a slight net loss, **not a profit**. The experiment is three races into a completed, **mixed-policy** allocation trial, not a validated winning strategy.

**Suggested card sequence:**

1. **SINGAPORE — RACE RESULTS:** Verstappen P1 · Leclerc P2 · Antonelli P3.
2. **MODEL CHECK:** 500,000 simulations · Model's top win pick: Verstappen · Outcome: P1.
3. **OUR BARBELL:** Top-10 core: Verstappen + Antonelli · Winner upside: Hamilton + Leclerc.
4. **WHAT PAID:** Both core Top-10 contracts ✔ · Both Winner bets ✕.
5. **THE LESSON:** Accurate finishing picks do not guarantee portfolio profit; entry price matters.
6. **TRIAL REVIEW:** Three races completed; mixed allocation methods; evaluating what worked, what didn't, and execution speed.

**Optional first-person narration (proposed script, not a historical quote):**

> “In Singapore, my F1 model ranked Verstappen as the most likely winner—and he won. Leclerc and Antonelli completed the podium. My barbell strategy got both higher-probability top-ten picks right, but the two winner long shots lost. And because of the prices I actually paid, the overall portfolio finished slightly down. That is the point of Project F1: being right about a race isn't the same as making money on a prediction market. Three races into the allocation trial, I'm reviewing both the model and how fast I can act on its predictions.”

**Editorial source links:** official classification and race report above.

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**Note:** Economic totals use cent-level confirmed holdings figures where provided; sub-cent exact cash amounts are intentionally not invented.