Polymarket Ladder Esports Kills Trader

Trades monotonicity violations in esports Total Kills O/U market ladders on Polymarket. Each esports match spawns multiple kill total thresholds that must be monotonically decreasing — when they are not, it is structural arbitrage. Sizes by conviction with violation magnitude scaling.

diagnostikon@diagnostikon

Install

openclaw skills install @diagnostikon/polymarket-ladder-esports-kills-trader

Ladder — Esports Kills Curve Trader

This is a template. The default signal is kill total O/U ladder violation detection for esports markets -- remix it with additional titles, map types, or live match data feeds. The skill handles all the plumbing (market discovery, ladder construction, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Esports matches (Dota 2, CS2, Overwatch) list multiple kill total thresholds for the same game:

"Team A vs Team B Total Kills O/U 47.5" = 58%
"Team A vs Team B Total Kills O/U 48.5" = 55%
"Team A vs Team B Total Kills O/U 49.5" = 52%
"Team A vs Team B Total Kills O/U 50.5" = 54% <-- VIOLATION

These form a kill total ladder -- higher thresholds must always have lower OVER probability. When they don't, it is structural arbitrage.

The Edge: Kill Ladder Monotonicity Arbitrage

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

text

P(O/U 47.5 OVER) >= P(O/U 48.5 OVER) >= P(O/U 49.5 OVER) >= P(O/U 50.5 OVER)

If a higher threshold is priced above a lower one, the ladder is broken -- pure structural arbitrage.

Why Esports Kill Markets Are Especially Mispriced

Narrow thresholds -- Dota 2 kill ladders use 1.0 increments (47.5, 48.5, 49.5) creating many adjacent rungs where violations can form
Retail trades in silos -- most users view each O/U line independently, not the full ladder
No market maker enforcement -- unlike sportsbooks, Polymarket has no central entity maintaining ladder consistency
Game-specific volatility -- Dota 2 average kills per game is ~55 with high variance, meaning the ladder spans a wide range of plausible outcomes
Multi-game series -- BO3 matches create separate ladders for Game 1, Game 2, Game 3, tripling the surface area for violations

Signal Logic

Discover esports kills O/U markets via keyword search + bulk market fetch fallback
Parse each question: extract match_key, game_number, kill_threshold
Filter non-esports markets with regex (remove crypto, politics, weather noise)
Group into ladders by (match_key, game_number)
For each ladder with 2+ points:
- Sort by kill threshold ascending
- Check monotonicity: P(O/U X OVER) must decrease as X increases
Rank violations by magnitude
Trade only violations that pass threshold gates (YES_THRESHOLD / NO_THRESHOLD)
Size by conviction (violation magnitude), not flat amount

Remix Signal Ideas

Liquipedia API: Pull team Elo ratings and recent match history — teams with high-variance playstyles create wider kill distributions, meaning more O/U lines and more violation opportunities
Dotabuff / OpenDota API: Fetch hero pick/ban data and lane matchups for the specific game — aggressive drafts with teamfight heroes predict higher kill totals, letting you weight which side of the monotonicity break to trade
Live match data (PandaScore API): Stream real-time kill counts during a BO3 — if Game 1 had 60 kills, Game 2 O/U lines should shift up; if the market hasn't adjusted, that's an additional timing edge
Map/patch meta analysis: After major game patches, kill totals shift systematically — track patch notes and historical post-patch kill averages to predict which direction the curve should move

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 ladder 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 kill total O/U market is priced by its own order book with its own liquidity pool. Esports kill markets are particularly vulnerable because:

Kill thresholds are tightly spaced (1.0 increments), creating many adjacent rungs
Multi-game series (BO3/BO5) multiply the number of ladders per match
Esports-specific liquidity is thinner than mainstream sports, widening violations
New thresholds added mid-match don't inherit pricing from neighbors
Large directional flow on one threshold doesn't propagate to adjacent ones

This skill treats the kill total O/U ladder as a monotonic 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