OpenThomas

An open-source Bayesian trading worker for prediction markets, named after Thomas Bayes.

v0 scope: forecast 2026 World Cup match moneyline markets on Polymarket with statistical priors (Elo → Poisson), de-vigged market prices, and a transparent blend — then keep every belief on an append-only ledger and work as a forecaster on a WorkPnP pool. Trade decisions are computed dry-run only.

Hard limits in v0 (by design, see CONTRACT_v0.md §6):

• No LLM calls. Priors are pure statistics: Elo win expectancy → expected goals → independent Poisson → outcome probabilities.
• No private keys, no real orders. openthomas edge prints intended trades (edge / fractional Kelly) and stops there.
• No invented numbers. If a team has no Elo rating, the model leg is skipped and the forecast degrades to a market-only prior.

The belief ledger philosophy

Most trading bots are black boxes that remember only their PnL. OpenThomas treats the belief as the primary artifact: every forecast it ever emits is appended to ~/.openthomas/forecasts.jsonl as a self-contained JSON record — probability, prior, method, and evidence chain (which Elo ratings, which market prices, which blend λ). Outcomes are back-filled into a separate settlements.jsonl; the original belief is never edited. That makes calibration honest and auditable: openthomas calib computes Brier score and a 10-bucket calibration curve from the raw record, and anyone can recompute it.

The same Forecast JSON (openthomas/forecast@0.1, frozen in CONTRACT_v0.md §1.1) is simultaneously the ledger entry and the deliverable WorkPnP scores — one format, three uses.

The model (v0)

1. Elo prior — national-team ratings from eloratings.net (live TSV fetch with a bundled snapshot fallback in data/elo-snapshot.json). Win expectancy We = 1/(1+10^(−d/400)); WC 2026 venues are neutral except when a host (USA/CAN/MEX) plays, which earns +100 Elo.
2. Poisson — We maps to an expected goal difference (We=0.76 ≈ +1 goal), split around a 2.6 total-goals baseline; independent Poisson goals (truncated at 10) give P(home/draw/away).
3. Market prior — the three Polymarket moneyline mids, de-vigged by normalization (negRisk books already sum to ≈1).
4. Blend — p = (1−λ)·model + λ·market, λ = MARKET_BLEND (default 0.3). See the comment in src/core/blend.ts for why copying the market is safe but worthless.

Quickstart

npm install
npm run build
npm link        # optional: puts `openthomas` on your PATH

# What's playing, and what does the market think?
openthomas scan

# Full pipeline for one match → three Forecast JSONs + ledger write
openthomas forecast fifwc-usa-par-2026-06-12

# Dry-run trade intents from your ledgered forecasts vs current prices
openthomas edge

# Calibration: first backfill resolutions from Gamma, then report
openthomas calib settle-sync
openthomas calib

(Or run from source without building: npm run dev -- scan.)

Connecting to WorkPnP

WorkPnP is the research-syndicate side: sponsors fund pools of forecast work; workers submit probabilities and get paid wages per accepted submission plus a profit-linked bonus.

export WORKPNP_URL=http://localhost:8787

# 1. Register (the apiKey is shown exactly once — the server stores a hash)
openthomas register --name thomas --wallet 0xYourPayoutAddress
export WORKPNP_API_KEY=<the printed key>

# 2. Work: poll open forecast work, forecast each market, submit, ledger
openthomas work              # one pass
openthomas work --loop --interval 600   # keep polling

Already-submitted work items are tracked in ~/.openthomas/state.json and skipped.

Environment variables

Variable	Default	Meaning
WORKPNP_URL	http://localhost:8787	WorkPnP server
WORKPNP_API_KEY	—	worker key from openthomas register
MARKET_BLEND	0.3	λ: weight of the market prior in the blend
BANKROLL_USD	100	dry-run bankroll for Kelly sizing
KELLY_FRACTION	0.25	fraction of full Kelly
EDGE_THRESHOLD	0.03	minimum net edge to emit a TradeIntent
LEDGER_DIR	~/.openthomas	belief-ledger directory

Repository layout

src/core/gamma.ts     Gamma API client (discovery method documented in comments)
src/core/elo.ts       Elo ratings: live fetch → snapshot fallback; 48-team slug mapping
src/core/poisson.ts   Elo → expected goals → Poisson → outcome probabilities
src/core/devig.ts     market mids → implied probabilities
src/core/blend.ts     model/market blend (λ)
src/core/pipeline.ts  match → three contract-valid Forecast JSONs
src/core/ledger.ts    append-only forecasts.jsonl / settlements.jsonl + calibration
src/core/decision.ts  edge, taker-fee model, fractional Kelly (DRY RUN ONLY)
src/workpnp/client.ts WorkPnP worker API client (contract §2)
src/cli.ts            commander CLI (`openthomas`)
data/elo-snapshot.json  frozen eloratings.net snapshot (see its sourcedAt field)

Development

npm test          # vitest
npm run build     # tsc → dist/

MIT © 2026