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Inspection is an effective but also expensive quality assurance activity to find defects early during software development. The defect detection process, team size, and staff hours invested can have a considerable impact on the defect detection effectiveness and cost-benefit of an inspection. In this paper, we use empirical data and a probabilistic model to estimate this impact for nominal (noncommunicating) inspection teams in an experiment context. Further, the analysis investigates how cutting off the inspection after a certain time frame would influence inspection performance. Main findings of the investigation are: 1) Using combinations of different reading techniques in a team is considerably more effective than using the best single technique only (regardless of the observed level of effort). 2) For optimizing the inspection performance, determining the optimal process mix in a team is more important than adding an inspector (above a certain team size) in our model. 3) A high level of defect detection effectiveness is much more costly to achieve than a moderate level since the average cost for the defects found by the inspector last added to a team increases more than linearly with growing effort investment. The work provides an initial baseline of inspection performance with regard to process diversity and effort in inspection teams. We encourage further studies on the topic of time usage with defect detection techniques and its effect on inspection effectiveness in a variety of inspection contexts to support inspection planning with limited resources.