Polymorphic Case study
← All case studies

03 / GAMES / ILLUSTRATIVE

The loop that keeps a player economy alive.

A mathematical model of a decentralised game economy—sources, sinks, prices, and the players between them—that found the feedback loop deciding whether the world stays rich in choices or collapses into a single strategy.

The plateTriangle: every state of the economy, as the shares of three strategies. Contours: the potential of the game the economy plays; its basins are the economies that last. Shards: populations of players flowing downhill. As the sink drifts toward a fold the model tunes it; an untuned run collapses into one corner.

ClientINDEPENDENT GAME STUDIO
CapabilityECONOMY MODELLING
Duration14 WEEKS
StatusILLUSTRATIVE CASE

01 / the question
What keeps an economy worth playing?

Every action moved the economy.

In a decentralised economy there is no central bank. Every craft, trade, and reward is a player decision that creates or destroys value, and each of those decisions changes what the next player finds worth doing. Balancing by spreadsheet had produced the usual cycle: a dominant strategy, a patch, and a new dominant strategy.

The studio needed to understand the system before tuning it: which feedback loops kept many ways of playing viable, and which quietly collapsed them into one.

Fig. 01

Strategy share in the closed beta

One strategy took 61% of play; the other five shared what was left.

One strategy dominant

02 / the build
Model → simulate → measure → tune

Write the economy down as a dynamical system.

We modelled resources, sinks, prices, and rewards as one coupled system, with player populations whose choices respond to what each mechanic pays. The model ran as millions of simulated player-days, calibrated against telemetry from the closed beta.

We measured richness directly—how many distinct strategies remain worth playing—and traced it to the loop driving it: player actions set resource abundance, abundance sets prices and rewards, and rewards decide which mechanics players choose next.

  1. Stage 0101

    Model

    Sources, sinks, prices, and rewards as one coupled system, with player behaviour that responds to payoff.

  2. Stage 0202

    Simulate

    Millions of player-days across populations, including bots, hoarders, and new arrivals.

  3. Stage 0303

    Measure

    Richness: how many strategies stay worth playing, and which loop is moving it.

  4. Stage 0404

    Tune

    Parameter bands that keep the economy in its rich regime, with early signs when it drifts.

03 / the result
More ways to play

Balance by mechanism, not by patch.

Before launch, the design team could see which parameter changes would collapse the economy into a single strategy and which would keep it open. Tuning moved from reactive patches to a monitored band, with an early signal whenever live play drifted towards its edge.

3.2×

viable strategies at launch, vs the closed beta

−70%

emergency balance patches in the first season

40M

simulated player-days