In many educational settings, students may have an incentive to take courses where high grades are easier to achieve, potentially corroding student learning, evaluation of student achievement, and the fairness and efficiency of post-graduation labor outcomes. A grading system that takes into account heterogeneity of teacher standards and student ability could mitigate these problems. Using unique data from a major Canadian research university, we calculate student grade point averages (GPAs) net of course difficulty and find evidence that raw GPAs systematically distort student achievement across majors. We then link undergraduate performance and law school data. We find that adjusted GPAs better predict Law School Admissions Test scores, while the raw GPAs better predict admission to law school and grades in law school. These results suggest nuanced relationship between grades, incentives and subsequent academic outcomes. We conclude by discussing implications of our results for university leaders.