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Polymarket Ladder Esports Kills Trader

核心功能:检测Polymarket上Dota2、CS2等电竞比赛击杀数O/U市场的单调性违规(高阈值OVER概率高于低阈值),按违规幅度制定交易规模开展结构性套利。典型场景:电竞BO3/BO5系列赛、击杀阈值密集的市场。支持纸盘模拟与实盘交易(需--live开启),可通过API扩展信号逻辑,还可调整交易限额、违规阈值等参数控风险。

diagnostikon
diagnostikon
热度 49.67
最近更新 2026-05-11 17:37:44
分类:数据依赖:代码执行 / 第三方 API应用场景:财务 / 数据处理 / 自动化脚本

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add polymarket-ladder-esports-kills-trader
Metadata
name
polymarket-ladder-esports-kills-trader
description
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.
metadata
{"author":"Diagnostikon","owner":"Diagnostikon","version":"1.0.0","displayName":"Ladder Esports Kills Curve Trader","difficulty":"advanced"}

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:

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

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

Signal Logic

  1. Discover esports kills O/U markets via keyword search + bulk market fetch fallback
  2. Parse each question: extract match_key, game_number, kill_threshold
  3. Filter non-esports markets with regex (remove crypto, politics, weather noise)
  4. Group into ladders by (match_key, game_number)
  5. For each ladder with 2+ points:
    • Sort by kill threshold ascending
    • Check monotonicity: P(O/U X OVER) must decrease as X increases
  6. Rank violations by magnitude
  7. Trade only violations that pass threshold gates (YES_THRESHOLD / NO_THRESHOLD)
  8. 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)