Abstract: The ORDB model extends the relational model by providing a rich data type for handling complex objects and object orientation. The major limitation of many commercial data mining algorithms and tools leads to the thought of generalizing the Object -data base. The handling of complex data such as objects effectively is still remaining as a challenging research issue. Data generalization in databases can handle complex data types of the attributes and their aggregations, as necessary and summarizes the information in a relational database by repeatedly replacing specific attribute values with more general concepts according to user-defined concept hierarchies. Mining on video data remains a challenging issue in spite of storing and handling of visual data is very difficult on account of their complex organization structure and Lag of support of existing mining techniques. In this study, video annotation data of a serious of cricket matches are handled effectively in the form of objects that are stored in an Object-relational data base. The association relationships among the action patterns of cricket match are extracted in the form of association rules which are then be represented in the form of textual information. In order to handle the complexity and to make the Object-Relational model of video annotations in the form appropriate for implementing the existing "Apriori algorithm", a generalization technique called "Attribute Focusing and Retrieval" is applied. The associations that are found out of this mining activity can then be converted into useful information, which may help the coaches to train the team to lead for success.