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Abstract Somatic copy-number alterations (SCNAs) are pervasive across cancers, arising through diverse mutational mechanisms and subsequently shaped by selection according to fitness advantages [1–4]. These alterations can drive tumourigenesis via gene-dosage changes in oncogenes and tumour suppressors [5, 6]. However, observed SCNA profiles do not uniquely define the genomic events that led to them, which is a major obstacle to understanding the selective forces shaping cancer genomes. Here we present SPICE, Selection Patterns In somatic Copy-number Events, an event-level framework that infers discrete copy-number events from allele-specific profiles and models focal selection from first principles, incorporating uniform breakpoint formation and locus-specific selective pressures. Applied to 5,966 samples from the TCGA dataset, SPICE quantifies the full spectrum of SCNA events, recapitulates known mutational processes, and tracks systematic shifts in event types before and after whole-genome duplication (WGD). Next, SPICE employs a generative selection model to identify the location of oncogenes and tumour-suppressors. Unlike previous approaches that detected peaks in aggregated copy-number signals, our model operates directly on inferred events and treats genome-wide breakpoint formation as a neutral reference against which locus-specific selection is detected. This analysis reveals 460 loci under selection which are highly enriched for known oncogenes and tumour suppressors, recapitulating most previously reported sites and uncovering many novel regions, and simultaneously showing that most internal copy-number events are not subject to focal selection. These results establish a unified framework that deconvolves copy-number profiles into their underlying evolutionary events and greatly expand the catalogue of loci implicated in cancer development. Graphical abstract