How Much of the Day-Ahead Value Does a Forecast Capture? A 43- Market Benchmark with a Weather-Orthogonality Test

Renewable penetration makes short-term electricity prices increasingly weather-driven, and a growing literature studies how traders convert forecasts into profit — almost entirely on the continuous intraday market and almost entirely in single markets. We complement that work at the foundation of the value stack: the day-ahead auction. We define a resolution-disciplined, ceiling-relative forecast-capture metric — the ratio of a forecast-driven, price-taking battery's day-ahead arbitrage P&L to the perfect- foresight ceiling — and measure it across 43 markets spanning Europe, GB, the Nordics and the US, with hourly and native 15-minute markets each handled on their own resolution. Measured with a standard, reproducible reference forecaster — internally constructed from open methods on public data — a price-taking battery captures a money-weighted 92% of the ceiling on average, with a wide spread we decompose into market archetypes (saturated, forecast-powered, flat-hydro). We then test whether raw archived numerical weather adds capture beyond the transmission operator's own published day-ahead RES forecast, and find a structured, not blanket residual signal: weather is orthogonally informative — adding +0.6 to +2.4 percentage points — only in wind-dominated zones with capture headroom (Latvia, Great Britain, Estonia, Lithuania, southern Sweden), while it is neutral- to-harmful in solar-heavy, high-capture markets where the operator's RES forecast already prices it. A near-saturated wind market (Poland, +0.16pp) isolates headroom, not RES type, as the primary driver. We cross-validate against independent third-party benchmarks on the day-ahead slice (Electricity Maps and Chronos-2 for Germany/Austria; Suena for Poland). Day-ahead is the layer every battery trades first — the measurable foundation beneath the intraday value ladder, and the plain complement to the intraday weather "arms race." In short: across 43 markets we measure how much day-ahead trading value a standard price forecast captures, and we identify the markets where adding weather forecasts still improves on the grid operator's own wind and solar forecasts.