Kalshi F1 Teammate Anti Trader

Trades F1 Drivers Championship markets on Kalshi using teammate anti-correlation. Teammates share the same car so their probabilities are structurally linked -- when one rises, the other should fall. Requires SIMMER_API_KEY and simmer-sdk.

diagnostikon@diagnostikon

Install

openclaw skills install @diagnostikon/kalshi-f1-teammate-anti-trader

Kalshi F1 Teammate Anti-Correlation Trader

This is a template. The default signal uses static dominance ratios -- remix it with live head-to-head qualifying/race data for dynamic dominance estimation. The skill handles all the plumbing (market discovery, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

F1 teammates share the same car, meaning their championship probabilities are structurally anti-correlated. If Verstappen's probability rises, Lawson's should fall (they share Red Bull's probability budget). Markets are slow to adjust both sides of teammate pairs simultaneously, creating exploitable relative mispricings.

Key advantages:

Structural constraint -- teammate probabilities must sum to roughly the team's total share
Dominance ratios are stable -- intra-team hierarchy rarely changes mid-season
Markets adjust asymmetrically -- one driver's price moves but teammate's lags
Pairs trading -- natural hedge structure reduces directional risk

Signal Logic

Teammate Anti-Correlation Model

Define teammate pairs (same constructor)
Set dominance ratios (who captures what % of team total)
For each pair, sum their market prices = team_total
Compute fair split: fair_A = team_total * dominance, fair_B = team_total * (1-dominance)
Trade when |fair - market| >= entry_edge for either driver

Teammate Pairs (2025)

Pair	Constructor	Dominance	Team Total
Verstappen / Lawson	Red Bull	85%/15%	~36%
Leclerc / Hamilton	Ferrari	50%/50%	~20%
Russell / Antonelli	Mercedes	70%/30%	~8%
Piastri / Norris	McLaren	40%/60%	~36%

Conviction-Based Sizing

conviction = min(|edge| / entry_edge, 2.0) / 2.0
size = max($1.00, conviction * MAX_POSITION_USD)
Larger edge = larger position, capped at MAX_POSITION_USD

Risk Parameters

Parameter	Default	Notes
Entry edge	8%	Min fair-vs-market divergence to trade
Exit threshold	45%	Sell when position price reaches this
Max position size	$5.00 USDC	Per market
Max trades per run	4	Rate limiting
Max slippage	15%	Skip if slippage exceeds
Min liquidity	$0	Disabled by default

Installation & Setup

bash

clawhub install kalshi-f1-teammate-anti-trader

Requires: SIMMER_API_KEY and SOLANA_PRIVATE_KEY environment variables.

Cron Schedule

Cron is set to null -- the skill does not run on a schedule until you configure it in the Simmer UI.

Safety & Execution Mode

The skill defaults to dry-run mode. Real trades only execute when --live is passed explicitly.

Scenario	Mode	Financial risk
`python trader.py`	Dry run	None
Cron / automaton	Dry run	None
`python trader.py --live`	Live (Kalshi via DFlow)	Real USDC

Required Credentials

Variable	Required	Notes
`SIMMER_API_KEY`	Yes	Trading authority. Treat as a high-value credential.
`SOLANA_PRIVATE_KEY`	Yes	Base58-encoded Solana private key for live trading.

Tunables (Risk Parameters)

Variable	Default	Purpose
`SIMMER_F1_TEAM_ENTRY_EDGE`	`0.08`	Min divergence to trigger trade
`SIMMER_F1_TEAM_EXIT_THRESHOLD`	`0.45`	Sell position when price reaches this level
`SIMMER_F1_TEAM_MAX_POSITION_USD`	`5.00`	Max USDC per trade
`SIMMER_F1_TEAM_MAX_TRADES_PER_RUN`	`4`	Max trades per execution cycle
`SIMMER_F1_TEAM_SLIPPAGE_MAX`	`0.15`	Max slippage before skipping trade
`SIMMER_F1_TEAM_MIN_LIQUIDITY`	`0`	Min market liquidity USD (0 = disabled)

Dependency

simmer-sdk is published on PyPI by Simmer Markets.

PyPI: https://pypi.org/project/simmer-sdk/
GitHub: https://github.com/SpartanLabsXyz/simmer-sdk
Publisher: hello@simmer.markets