Why KELLY can be stronger here
KELLY is designed to win by being scoreable: every forecast should connect to source evidence, causal assumptions, falsifiers, settlement, calibration, replay, and memory lineage.
why it mattersA forecast platform is only as good as its ability to be wrong in public, adjust from reality, and improve the next forecast without hiding the chain.
sector edgeShows implied probability, line dispersion, closing-line movement, and calibration.
best claim boundaryKELLY should be called better only where its scorecards, calibration, replay receipts, and source coverage outperform alternatives. This page is built to make that measurable.
Where the proof lives
proofSource plan: the approved feed rows on this page
proofForecast method: the doctrine timeline on this page
proofAuthority evidence: Authority Index and replay receipts
proofScore evidence: settlement and calibration records
proofSystem evidence: Brain Fleet, generality evidence, and advanced proof labs
Professional layout pattern
The lab layout follows successful product patterns: fast first read, watchable objects, citations beside claims, source freshness, score history, and direct proof links.
patternOdds-board pattern: implied probability, market disagreement, closing line, and result all stay attached.
patternCalibration-practice pattern: compare user probability, KELLY probability, and outcome score.
patternCitation-forward answer pattern: put sources and proof next to claims.
patternForecasting track-record pattern: keep probability, resolution rule, score, and history together.
patternWatchlist pattern: let users inspect a saved set without writing ground truth.
patternAlert/status pattern: show what changed, what is stale, and what KELLY is watching.
Research references
TradingViewCharts, alerts, screeners, replay, multi-chart layouts, and fast command/search patterns make market work feel immediate. MetaculusForecast questions need clear resolution rules, track records, scoring, calibration, and aggregation history. Windy / Windy.appWeather users need maps, layers, local points, alerts, history, model comparison, and fast location context. PerplexityAnswer users expect citations beside claims, follow-up context, and checkable source trails.
KELLY's specialized forecast method
Odds conversion, market dispersion, KELLY probability lane, upset/falsifier checks, settlement, Brier-style calibration.
1Approved source intake only
2Tag source, freshness, domain, and authority
3The Book of Why: ask what caused the change, what would have happened otherwise, and what evidence can falsify the causal story
4Thinking in Systems: map feedback loops, delays, stocks, flows, constraints, and downstream effects
5Thinking, Fast and Slow: separate fast pattern recognition from slower deliberate verification
6Superforecasting: start with base rates, update incrementally, keep probabilities explicit, and score the forecast later
7Thinking in Bets: treat every forecast as a wager against reality with a clear settlement rule
8Build causal pressure nodes and forecast cones
9Separate KELLY forecast from user forecast
10Track falsifiers, uncertainty, and competing explanations
11Close against reality
12Score calibration and error direction
13Apply continuous micro-adjustments after settlement to improve future accuracy
14Create replayable memory evidence when eligible
What this lab is for
Showing probability calibration, market disagreement, and outcome settlement.
safe claimShows implied probability, line dispersion, closing-line movement, and calibration.
boundaryNo betting advice, no arbitrage guarantee, no profitable betting system.
Live proof status
proof score42 / early
visible cells0
readiness score0%
sources wired2/3
public writesblocked
Proof links
Every odds view should show implied probability, KELLY probability, market disagreement, outcome, and score.
Approved source plan
| source | status | cost | role |
|---|
No simulated source
synthetic-none |
wired |
none |
The engine can run manual ticks without any external API key. |
TheOddsAPI
the-odds-api |
available |
free_key_limited |
Optional sports odds calibration feed. Poll slowly to preserve free quota. |
OpenAI
openai |
wired |
paid_optional |
Only for narrative phrasing. The proof engine does not require an LLM. |
User questions this lab can inspect
| question lane | plain question | node |
|---|
| Win chance |
Is this team likely to win? |
forecast-lane |
| Upset risk |
Is there upset risk? |
forecast-lane |
| Book disagreement |
Are the books disagreeing? |
forecast-lane |
| Market probability |
What probability is the market showing? |
forecast-lane |
| Forecast practice |
How do I score my forecast later? |
forecast-lane |
Default focuses
| focus | meaning | context |
|---|
| NBA games |
basketball_nba |
league |
| MLB games |
baseball_mlb |
league |
| NFL games |
americanfootball_nfl |
league |
| NHL games |
icehockey_nhl |
league |
| EPL matches |
soccer_epl |
league |
Causal pressure map
SPORTS:AVG_FAIR_PROBSPORTS:MARKET_DISPERSIONSPORTS:BOOK_DEPTHSPORTS:UPSET_RISKSPORTS:DECISION
causal linkSPORTS:AVG_FAIR_PROB -> SPORTS:DECISION
causal linkSPORTS:MARKET_DISPERSION -> SPORTS:UPSET_RISK
causal linkSPORTS:UPSET_RISK -> SPORTS:DECISION
causal linkSPORTS:BOOK_DEPTH -> SPORTS:DECISION
Boundary receipt
{
"readOnly": true,
"publicUserWriteAllowed": false,
"noAdviceSubstitute": "No betting advice, no arbitrage guarantee, no profitable betting system.",
"noClaimOfPerfectPrediction": true,
"proofRequiredForEveryForecast": true
}