Prediction market odds are frequently misinterpreted as vote-share forecasts rather than win probabilities. A candidate priced at 70% to win carries a 30% probability of losing, meaning an upset outcome does not inherently invalidate the underlying model. Market data suggests that single election results cannot establish whether prediction market odds were reliable. Evaluating accuracy requires comparing outcomes against probabilistic expectations across multiple events rather than treating each result as binary confirmation or failure.