Batteries are crucial to manage the rising share of intermittent energy sources and variability in demand. ost techno-economic models in the literature oversimplify battery degradation representation. Accounting properly for battery degradation allows for better cost tradeoffs and optimal battery usage, especially in dynamic settings. We propose a highly accurate and scalable formulation for battery degradation that considers the combined impact of cycle depth and state of charge on calendar and cycle aging. We test the consequences of battery degradation in a stylized price arbitrage model on battery operation and solution times. When ignoring battery degradation, ex-post calculations reveal hidden degradation costs that exceed revenues and hence turn seemingly profitable trades into losing trades. Considering battery degradation leads to smaller cycle depths and lower average states of charge. Overall, we show that a much-improved representation of battery degradation is possible at modest computational cost.