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Belady's optimal cache replacement policy is an algorithm to work out the theoretical minimum number of cache misses, but the rationale behind it was too simple. In this work, we revisit the essential function of caches to develop an underlying analytical model. We argue that frequency and recency are the only two affordable attributes of cache history that can be leveraged to predict a good replacement. Based on those two properties, we propose a novel replacement policy, the Effectiveness-Based Replacement policy (EBR) and a refinement, Dynamic EBR (D-EBR), which combines measures of recency and frequency to form a rank sequence inside each set and evict blocks with lowest rank. To evaluate our design, we simulated all 30 applications from SPEC CPU2006 for uni-core system and a set of combinations for 4-core systems, for different cache sizes. The results show that EBR achieves an average miss rate reduction of 12.4%. With the help of D-EBR, we can tune the weight ratio between 'frequency' and 'recency' dynamically. D-EBR can nearly double the miss reduction achieved by EBR alone. In terms of hardware overhead, EBR requires half the hardware overhead of real LRU and even compared with Pseudo LRU the overhead is modest.