Alternative · Analytics aggregator
EventWaves vs
SimpleFunctions.
EventWaves surfaces trader-skill rankings and momentum signals to help identify high-edge Polymarket markets — a focused analytics layer for human-driven decision-making. SimpleFunctions ships the agent layer above it: causal-tree thesis decomposition with auto-evaluation cycles, a Portfolio Autopilot with a 1M-context LLM and 7-gate risk cascade, 56 MCP tools that integrate into any AI coding environment, and computed indicators across 48K+ active contracts on both Kalshi and Polymarket.
Verified 2026-04 · public sources only · live SF data from /calibration
Verdict
Pick the one that fits how
you actually work.
Choose SimpleFunctions if
You are building agents, autonomous trading systems, or research workflows that need more than analytics dashboards — calibrated probabilities with public Brier scores, causal-tree thesis modelling with auto-evaluation cycles, regime classification across the full 48K-contract universe on both Kalshi and Polymarket, computed indicators (implied yield, cliff risk index, liquidity availability score), cross-venue arbitrage pairs, and a 56-tool MCP server that integrates into Claude Code or Cursor in one line.
Choose EventWaves if
EventWaves specialises in Polymarket trader-skill ranking and momentum analysis — a purpose-built tool for users who want to identify high-edge markets based on which historically skilled traders are most active. If your workflow centres on Polymarket-specific trader attribution rather than agent integration, multi-venue coverage, or autonomous execution, EventWaves is designed for that use case.
EventWaves focuses on Polymarket trader-skill analytics for human dashboards. SimpleFunctions ships the agent layer above it: theses, indicators, autopilot, MCP, multi-venue. Different products, mostly different audiences.
At a glance
Three things that
actually differ.
Everything EventWaves gives you — Polymarket market analytics, high-edge market identification, and momentum signals — SimpleFunctions also gives you, extended across both Kalshi and Polymarket via the same upstream feeds.
On top of that, SF ships a causal-tree thesis system, Portfolio Autopilot (1M-context LLM, 7-gate risk cascade), and 56 MCP tools that no current prediction market analytics product exposes.
SF publishes live Brier scores at /api/calibration — Kalshi 0.20, Polymarket 0.12 on T-24h price, past 90 days — letting you audit its accuracy the same way you would evaluate any probabilistic forecaster.
Side by side
10 dimensions · verified 2026-04SimpleFunctionsKalshi + Polymarket normalised, 48K+ active contracts indexed and queryable.
EventWavesPolymarket-focused analytics; Kalshi coverage is not documented in public sources.
SimpleFunctionsGET /api/public/market/{ticker}?depth=true returns the bid/ask ladder, spread, and slippage estimate.
EventWavesNot documented as a public feature.
SimpleFunctionsMomentum captured via computed indicators (CRI, LAS, regime label) pre-computed across 48K contracts; no per-trader attribution layer.
EventWavesTrader skill ranking and momentum tracking are the core differentiators — identifies which traders historically outperform and where they are active.
SimpleFunctionsImplied yield (IY), cliff risk index (CRI), liquidity availability score (LAS), event overround (EE), τ-days, regime label — pre-computed at /screen across the full contract universe.
EventWavesAnalytics oriented toward trader-skill and market momentum; specific derived indicators are not documented in public sources.
SimpleFunctionsLive Brier scores at /api/calibration, broken down by venue, category, and price bucket — Kalshi 0.20, Polymarket 0.12 on T-24h price, trailing 90 days.
EventWavesNot published in public documentation.
SimpleFunctionsPOST /api/thesis/create decomposes any plain-language claim into a causal tree, propagates probabilities, scans both venues for tradeable edges, and runs a continuous evaluation heartbeat.
EventWavesNot in scope.
SimpleFunctionsPortfolio Autopilot — 1M-context LLM, 13 data sources, 7-gate risk cascade (kill switch, position limits, drawdown gate, regime check) before every execution.
EventWavesNot in scope.
SimpleFunctions56 tools via claude mcp add simplefunctions --url https://simplefunctions.dev/api/mcp/mcp; works with Claude Code, Cursor, and any MCP-compatible client.
EventWavesNo MCP server published.
SimpleFunctionsPublic REST at /api/public/*, 60+ CLI commands (npm i -g @spfunctions/cli), no authentication required for read operations.
EventWavesNo public REST API documented in public sources; product appears to be a web dashboard.
SimpleFunctionsPublic REST + MCP + CLI reads require no auth. Pay-per-token only on thesis/intent execution, with 15M tokens included before charges apply.
EventWavesPricing not documented in public sources.
Methodology
Verified 2026-04 from public sources only — EventWaves's documentation, public website, and publicly observable behaviour. We never claim non-public information about EventWaves's internals. SimpleFunctions claims on this page are computed live from /api/calibration, /api/public/cross-venue/pairs, and /api/public/markets — you can re-verify them yourself with curl.
Use cases
Same data, different
best fit per scenario.
Scenario 01
Building an AI agent that monitors prediction markets and executes trades autonomously.
SimpleFunctions · best fit
SimpleFunctions is designed for this use case. Portfolio Autopilot ingests 13 data sources through a 1M-context LLM, runs a 7-gate risk cascade, and executes without human intervention. The 56-tool MCP server gives any AI coding environment structured access to the full pipeline.
EventWaves
EventWaves is a human-facing analytics dashboard focused on identifying high-edge markets; it does not offer an autonomous execution layer or a machine-readable API for agent integration.
Scenario 02
Identifying Polymarket markets where historically skilled traders are currently most active.
SimpleFunctions
SimpleFunctions computes momentum-adjacent indicators (CRI, LAS, regime label) across the full contract universe but does not expose per-trader attribution or trader-skill ranking.
EventWaves · best fit
This is EventWaves's primary use case. Trader skill ranking and momentum tracking are its core differentiators — it is purpose-built to surface exactly this signal on Polymarket.
Scenario 03
Decomposing a complex geopolitical thesis into testable sub-claims mapped to live contracts on both Kalshi and Polymarket.
SimpleFunctions · best fit
POST /api/thesis/create handles this end-to-end: causal-tree decomposition, probability propagation, venue scanning, and a continuous evaluation heartbeat that re-scores each node as news arrives and prices shift.
EventWaves
EventWaves is oriented toward market selection via trader signals, not thesis modelling or causal decomposition. This use case is outside its documented scope.
Scenario 04
Auditing a forecasting system's accuracy by venue and price bucket before deploying capital.
SimpleFunctions · best fit
GET /api/calibration returns SF's own Brier scores segmented by venue (Kalshi, Polymarket), category, and price bucket over the trailing 90 days, giving a direct accuracy baseline to compare against.
EventWaves
EventWaves does not publish equivalent calibration data in its public documentation; this audit workflow is not part of its stated feature set.
Live data
The SimpleFunctions claims on this page are not marketing copy. Brier scores, market counts, and cross-venue pair counts are computed live from /calibration, /screen, and /api/public/cross-venue/pairs. All public, all free, all CC-BY-4.0.
FAQ
What does EventWaves do?+
EventWaves is a Polymarket analytics tool that surfaces high-edge markets by ranking traders on historical skill and tracking momentum signals. It is designed to help human users identify which markets are worth trading based on who is actively participating and how those participants have performed historically. It does not appear to expose a public REST API, and its documentation does not describe Kalshi coverage.
How does SimpleFunctions compare to EventWaves on Polymarket coverage?+
Both products cover Polymarket, but with different orientations. EventWaves focuses on trader-skill ranking and momentum as the primary signal for human decision-making. SimpleFunctions normalises prices across Kalshi and Polymarket combined — 48K+ active contracts — computes derived indicators (implied yield, cliff risk index, liquidity availability score) across the full universe, and publishes live Brier scores at /api/calibration so you can audit its accuracy directly. The two approaches address different workflows.
What is the SimpleFunctions causal thesis system and how does it work?+
POST /api/thesis/create accepts a plain-language sentence and decomposes it into a causal tree of testable sub-claims. The system propagates probabilities across the tree, scans Kalshi and Polymarket for contracts that map to each node, and runs an ongoing evaluation heartbeat — news scan, price refresh, milestone check, LLM evaluation, confidence update — on a continuous cycle. You can inject external signals via /api/thesis/{id}/signal. Public theses are forkable. No other prediction market data product currently exposes this capability.
What is Portfolio Autopilot?+
Portfolio Autopilot is SF's autonomous trading agent. It ingests 13 data sources through a 1M-context LLM and runs a 7-gate risk cascade — including a kill switch, position limits, drawdown gate, and regime check — before placing any trade. It is built for users who want a fully autonomous system rather than a signal dashboard they act on manually. EventWaves does not offer an equivalent autonomous execution layer.
What is the SimpleFunctions MCP server?+
SimpleFunctions ships a 56-tool MCP server. Running claude mcp add simplefunctions --url https://simplefunctions.dev/api/mcp/mcp connects it to Claude Code, Cursor, or any MCP-compatible client. From there, AI agents get structured access to prediction market prices, computed indicators, thesis trees, trade ideas, cross-venue arbitrage pairs, and calibration data — without manually wiring REST calls. EventWaves does not publish an MCP server.
How does SF's live calibration data work?+
GET /api/calibration returns SF's own Brier scores broken down by venue (Kalshi, Polymarket), category, and price bucket, computed over the trailing 90 days. Current figures: Kalshi 0.20, Polymarket 0.12 on T-24h price. This lets you treat SF's probability estimates the same way you would evaluate any probabilistic forecaster — by checking historical accuracy before acting on its outputs. EventWaves does not publish equivalent calibration data in its public documentation.
Does SimpleFunctions cover Kalshi in addition to Polymarket?+
Yes. SimpleFunctions indexes and normalises prices across both Kalshi and Polymarket — 48K+ active contracts — and exposes cross-venue arbitrage pairs at /api/public/cross-venue/pairs?preset=arb. EventWaves focuses on Polymarket; its public documentation does not describe Kalshi coverage.
Can I use SimpleFunctions without creating an account?+
All read endpoints — /api/public/markets, /api/public/cross-venue/pairs, /api/public/ideas, /api/calibration, and orderbook depth — require no authentication. The CLI (npm i -g @spfunctions/cli, 60+ commands) and the MCP server both work without API keys for read operations. Authentication is only required for thesis creation and intent execution.
Start for free.
Public endpoints are free for normal usage and rate-limited for reliability. Authenticated endpoints are free up to 15M tokens, then pay per token. No credit card to start.