Through analyzing full text search results from web archives, the authors developed a method called the Random Searcher Model (RSM) to efficiently generate profiles of web archive collections with low overhead. The profiles accurately predict an archive's likelihood of containing a URI's mementos while minimizing search costs. Different RSM modes allow customization based on collection characteristics. The authors recommend profile policies and RSM modes to balance accuracy, recall, and costs depending on available archive metadata. Future work includes combining profile attributes and evaluating profiles for applications beyond memento routing.