Technological Edge

Training against serving, which hardware suits which model, where the money actually goes, and why iteration speed explains more than modelling talent does.

Why a stated accuracy figure is rarely comparable, which baselines are actually hard to beat, how benchmarks get gamed, and the four questions worth asking.

Why k-fold cross-validation misleads in sport, what walk-forward testing reveals, and why calibration — not accuracy — decides whether a forecast is worth reading.

Stream platforms, event-driven architecture and in-memory state — how a forecast keeps pace with a live match, and the four ways speed goes wrong.