Esports & Gaming · Quantitative#256

Series-Length Distribution Model

Markets on whether a series goes the distance — 2-0 versus 2-1, or a deciding fifth map — depend on how evenly matched the teams are and on how much per-map results correlate within a series. Momentum is real in esports: the team that wins map one wins map two more often than independence would predict. You fit that correlation from historical series and price the length markets, which are usually quoted as if each map were an independent coin flip.

What you need to run it

  • Historical series database with per-map results to estimate within-series correlation
  • Per-matchup map win probabilities feeding a series simulator
  • Separate parameters by format and title, since momentum differs between games

Where this applies

Markets on Polymarket where series-length distribution model is the natural play:

  • Will this Bo3 go to a deciding third map?
  • Will the grand final go all five maps?
  • Will the series end 2-0?

Capabilities this demands

Model / quantData ingestionDomain knowledge

At a glance

CategoryQuantitative
MarketEsports & Gaming
Requirements3
CapabilitiesModel / quant, Data ingestion, Domain knowledge
VenuePolymarket (CLOB, Polygon)

Build it

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This is documentation, not advice. Poly Research & Robotics publishes how these strategies work because the method should be checkable — not as a recommendation to trade them. See the full strategy database (297 strategies) or the data resources directory.
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