Frequent strong El Niño events, including the extremes of 2015/16 and 2023/24, have exerted profound global climatic impacts. Unlike canonical Eastern Pacific (EP) and Central Pacific (CP) types, defined by the location of maximum sea surface temperature (SST) anomalies, these events exhibit a distinct mixed-type pattern characterized by warming in both regions. However, the respective contributions of the EP and CP patterns to the mixed-type events remain poorly understood. Here, using a binary linear regression based on E- and C-indices associated with the EP and CP patterns, we quantify the contribution of the E- and C-components, and show that strong El Niño events are mostly of the mixed-type. Our results indicate that the C-component is the primary source of ENSO variability, while during strong El Niño events, the average contribution of the E-component increases significantly from 6.4% in moderate events to 46.8%, thereby forming the mixed-type El Niño events. Analyses of 45 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) project that, in a warming climate, the frequency of the strong mixed-type events increases by 33.5%. We emphasize that the mixed-type El Niño is the primary contributor to strong El Niño events, with a proportion far exceeding that of either the EP or CP type. Our method offers a framework for understanding ENSO diversity and its response to climate change.