Polymarket 24h Sports Line Curve Trader

Trades structural mispricings in sports over/under markets by reconstructing the implied probability curve across multiple O/U line values for the same game...

Security Scan

The skill's code, declared dependencies, and environment variables align with its stated purpose (reconstructing O/U probability curves and trading via the Simmer API); nothing in the package requests unrelated credentials or performs unexpected actions.

Purpose & Capability

Name/description, SKILL.md, clawhub.json, and trader.py all describe the same activity (finding O/U curve violations and trading). The only required credential (SIMMER_API_KEY) and the simmer-sdk dependency are appropriate for a Simmer/Polymarket trading client.

Instruction Scope

SKILL.md instructs running trader.py, defaults to paper/sim mode, and requires an explicit --live flag for real trades. The runtime instructions and included code focus on market parsing, curve detection, and trade execution; they do not instruct reading unrelated system files or exfiltrating data.

Install Mechanism

There is no custom install spec; dependencies are installed via pip (simmer-sdk on PyPI / GitHub). Pip installation is expected for this functionality but carries the usual third-party package risk — verify the simmer-sdk package and its source if you don't already trust it.

Credentials

The skill requires a single trading API key (SIMMER_API_KEY) and exposes configurable tunables via environment variables (declared in clawhub.json). No unrelated secrets or system config paths are requested.

Persistence & Privilege

always is false and autostart is false; the automaton entrypoint exists but nothing runs automatically without explicit configuration. The skill may be invoked autonomously per platform defaults, which is expected for skills of this type.

Assessment

This package appears coherent for a Polymarket/Simmer trading bot. Before installing, verify the simmer-sdk package source and review its code (pip packages can contain arbitrary code). Treat SIMMER_API_KEY as a high-value credential: restrict its permissions if possible, store it securely, and test thoroughly in paper (sim) mode before using --live. Confirm autostart/cron remain disabled in your runtime if you don't want continuous automation. If you want extra assurance, request a full review of the simmer-sdk and the complete trader.py file (to ensure no hidden behavior in the truncated portion).

24h Sports Line Curve Trader

This is a template. The default signal is implied O/U curve violation detection across sports markets -- remix it with additional sports, line types, or cross-venue feeds. The skill handles all the plumbing (market discovery, curve construction, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Polymarket lists multiple over/under lines for the same sporting event:

• "Team A vs Team B O/U 5.5" = 50%
• "Team A vs Team B O/U 6.5" = 46%
• "Team A vs Team B O/U 7.5" = 29%

Retail trades each market as an isolated bet. But together, these markets form an implied probability curve -- higher totals must always be less likely for the OVER side.

This skill reconstructs that curve and finds where it is mathematically broken.

The Edge: Sports Line Curve Arbitrage

Violation Type 1: Monotonicity Break

The probability of going OVER a lower line must always be greater than or equal to going OVER a higher line:

P(O/U 5.5 OVER) >= P(O/U 6.5 OVER) >= P(O/U 7.5 OVER)

If a higher line is priced above a lower line, the curve is broken -- pure structural arbitrage.

Violation Type 2: Tennis Set vs Match Inconsistency

For tennis, the match total always equals or exceeds the Set 1 total. Therefore:

P(Match O/U X OVER) >= P(Set 1 O/U X OVER)

If a Set 1 O/U market is priced higher than the equivalent Match O/U market, the relationship is violated.

Why This Works

1. Retail trades in silos -- most users view each O/U line independently and do not cross-reference the full line ladder
2. No market maker enforcement -- unlike sportsbooks, there is no central entity maintaining curve consistency across lines
3. Mathematical, not opinion -- the violations are provable inconsistencies in the implied distribution
4. Applies across sports -- football, basketball, tennis, esports (kills, maps), baseball, hockey

Signal Logic

1. Discover all sports O/U markets via keyword search (O/U, total goals, total kills, etc.)
2. Parse each question: extract game/match name, O/U line value, scope (set or match)
3. Group into curves by (game, scope)
4. For each curve with 2+ points:
   • Check monotonicity: P(O/U X OVER) must decrease as X increases
   • Check tennis set-vs-match consistency
5. Rank violations by magnitude
6. Trade only violations that also pass threshold gates (YES_THRESHOLD / NO_THRESHOLD)
7. Size by conviction (violation magnitude), not flat amount

Safety & Execution Mode

The skill defaults to paper trading (venue="sim"). Real trades only with --live flag.

Scenario	Mode	Financial risk
python trader.py	Paper (sim)	None
Cron / automaton	Paper (sim)	None
python trader.py --live	Live (polymarket)	Real USDC

autostart: false and cron: null mean nothing runs automatically until configured in Simmer UI.

Required Credentials

Variable	Required	Notes
SIMMER_API_KEY	Yes	Trading authority. Treat as a high-value credential.

Tunables (Risk Parameters)

All declared as tunables in clawhub.json and adjustable from the Simmer UI.

Variable	Default	Purpose
SIMMER_MAX_POSITION	40	Max USDC per trade at full conviction
SIMMER_MIN_TRADE	5	Floor for any trade
SIMMER_MIN_VOLUME	5000	Min market volume filter (USD)
SIMMER_MAX_SPREAD	0.08	Max bid-ask spread
SIMMER_MIN_DAYS	0	Min days until resolution (0 = allow same-day)
SIMMER_MAX_POSITIONS	8	Max concurrent open positions
SIMMER_YES_THRESHOLD	0.38	Buy YES only if market probability <= this
SIMMER_NO_THRESHOLD	0.62	Sell NO only if market probability >= this
SIMMER_MIN_VIOLATION	0.03	Min curve violation magnitude to trigger a trade

Edge Thesis

Traditional sportsbooks have professional line-setters who enforce consistency across O/U lines for the same game. Polymarket has no such mechanism -- each O/U market is priced by its own order book with its own liquidity pool. This creates systematic micro-inconsistencies in the implied distribution, especially when:

• New O/U lines are added at previously unlisted values
• Large directional flow pushes one line without propagating to neighbors
• Market makers leave gaps during low-liquidity hours
• Tennis set-level markets diverge from match-level markets

This skill treats the O/U line ladder as a probability curve and trades the repair.

Dependency

simmer-sdk by Simmer Markets (SpartanLabsXyz)

• PyPI: https://pypi.org/project/simmer-sdk/
• GitHub: https://github.com/SpartanLabsXyz/simmer-sdk