Experiments carried out within evaluation initiatives for information retrieval have been building a substantial resource for further detailed research. In this study, we present a comprehensive analysis of the data of the Cross Language Evaluation Forum (CLEF) from the years 2000 to 2004. Features of the topics are related to the detailed results of more than 100 runs. The analysis considers the performance of the systems for each individual topic. Named entities in topics revealed to be a major influencing factor on retrieval performance. They lead to a significant
improvement of the retrieval quality in general and also for most systems and tasks. This knowledge, gained by data mining on the evaluation results, can be exploited for the improvement of retrieval systems as well as for the design of topics for future CLEF campaigns.