Major League Baseball tracks every pitch of every game and provides the public with access to a significant amount of data for each pitch. This level of data availability is not seen in many other sports and offers substantial opportunities to provide analysis on the sport. Major League Baseball does not provide the raw data but provides refined data. While the algorithms for transforming the raw data are robust, the algorithms are not perfect. This study investigates the specific case of knuckleball pitches and shows that the equations of motion and reported spin rates do not align. This study uses the modified shooting method combined with the Levenberg–Marquardt algorithm to determine the trajectories of the pitches based on the provided data and known equations of motion. This study investigates three scenarios: 1) the reported data are correct; 2) the pitches are correctly identified, but the spin rates are incorrect; and 3) the spin rates are correct, but the pitches are incorrectly identified as knuckleballs. We show that the reported data are inconsistent with the equations of motion and that, based on statistical analysis, the pitch identification is likely incorrect.