Decades of criminological research have highlighted the principle that "place matters" when analysing crime dynamics. While acknowledging this, our study emphasises that place matters at specific times of the day and days of the week. This paper explores spatio-temporal patterns of assaults in public spaces in Stockholm, Sweden, using a time-space modeling approach. By segmenting annual crime registry data into time-specific models (e.g., weekday mornings and weekend nights), sixteen models were created covering two years. Using Risk Terrain Modeling, spatio-temporal cells were analysed with Spearman's Rank Correlations and Predictive Accuracy and Efficiency measures to explore and compare time-specific models to a more generalised annual model. Results suggest that time-specific models perform better in smaller geographical areas compared to a yearly model. However, correlations and GIS mapping show that micro-grid crime hotspots fluctuate within larger hotspots and between years. These findings underscore the need for dynamic hotspot monitoring within crime analysis and for law enforcement to adapt resource allocation at both hotspots and within hot times. By shifting from static annual models to more nuanced temporal models, authorities can enhance crime prevention strategies and optimise interventions at high-risk locations during critical temporal windows.