Five topics. Every tool. Show the work.

How these five were chosen

Five editorially selected cross-platform topics drawn from the first 50 open Polymarket events ordered by 24h volume. Ordered here by that Polymarket rank. This is not a global top-five ranking or a Kalshi volume ranking. Kalshi volume is contract count, not directly comparable to Polymarket dollar volume. Football, crypto, international elections, monetary policy, and US chamber control provide five different modeling problems. Esports and duplicate crypto horizons were not selected. The midterms example was deliberately included for its joint-outcome lesson despite a lower activity rank.

Polymarket event activity is measured in reported dollar volume; Kalshi activity is reported contract count. We do not add those figures or call the result a global ranking.

The assessment pipeline

1. Capture specific contracts, rules, timestamps, source identifiers, and both order books.
2. Check whether the questions and settlement exceptions actually match. Jev supplies a separate typed review, not authority over the rulebook.
3. Compute spreads, executable-depth examples, payoff, cost hurdles, EV sensitivity, theoretical Kelly where applicable, and dependence bounds.
4. Run the existing Research, AI Analyzer, Drift, and relevant EODHD/Jev integrations. Record success, quality flags, and access limits.
5. Exclude low-data forecasts, unsourced scores, and unrelated financial proxies from the event probability. Keep the crowd midpoint as a labeled benchmark, not an independent prediction.
6. Present a paper scenario and a journal exercise. Revisit after official resolution before calculating accuracy.