We study the operational implementation of multiproduct dynamic pricing by a Major League Baseball franchise for single game tickets. We develop and apply a comprehensive customer choice model to help design dynamic pricing policies for the franchise. Our model encompasses all relevant aspects of customer demand generation process, including ticket quantity and stadium seat section choice. Furthermore, our demand model incorporates external factors that drive customer valuation of sports tickets such as the home team's on-field performance and observed overall attendance level at the time of purchase. Our counterfactual results show potential revenue improvement of up to 15% through the effective use of dynamic pricing. We also find that a properly calibrated fixed pricing policy based on a detailed customer demand model can achieve similar levels of revenue improvement as the optimal dynamic pricing policy.