Improper technique is detrimental to a tennis player's performance and increases the risk of injury. Regular training routines are necessary but take effort and motivation, and on-court training requires resources that pose additional barriers. Virtual reality paves the way for engaging self-training applications that address these barriers, but without a coach, motion errors may go uncorrected. We present a complementary way of practicing aspects of proper tennis forehand technique in virtual reality, utilizing automated motion analysis for immediate post-action multimodal feedback. Our VR tennis training utilizes motor learning principles and motion analysis to reinforce proper movement patterns and provide timely corrections. We overcome the problem of complex motion analysis by breaking the motion into distinct phases and utilizing the concept of coaching rules. After each shot, auditory and visual feedback is given, focusing on one aspect at a time. The exclusive use of the Meta Quest's partial motion capture poses technical challenges, restricting the set of applicable coaching rules and feedback due to the limited number of tracked joints. However, it allows us to present a more accessible and flexible alternative to on-court training and existing self-training setups. We conducted a user study$(\mathrm{N} = 26)$following a within-subjects pretest-posttest design to evaluate short-term effects of our VR tennis training. Results demonstrate significant improvements in motivation, performance metrics, and participants' self-reported confidence in technique from the pre- to posttest, suggesting a potential short-term learning effect. Qualitative insights reveal that participants believe our VR training can complement traditional tennis training to a certain degree.