Why prediction market analytics work better in log-odds: bounded prices, unequal cent moves, and how Logit Terminal measures probability movement.

What calibration means for prediction markets, why sample size matters, and how Logit Terminal handles low-sample buckets and pinned prices.

How volatility works in probability markets, why event phase matters, and what Vol vs Peers means on Logit Terminal.

How volume-at-price profiles approximate where prediction market contracts changed hands, and what distance from crowd basis means.

How Logit Terminal measures whether unusual probability moves historically gave back part of the move, and why terminal moves are excluded.

Prediction market prices as implied probabilities: bid, ask, spread, volume, open interest, and event lifecycle explained.

The difference between volume and open interest, why liquidity matters, and how Logit Terminal uses both in confidence labels.