Anyone who knows me even a little bit probably understands how big of a baseball fan I am. My obsession is so consuming that I am known for my ability to name any World Series winner since 1903.

Going hand in hand with baseball fandom is my love for statistical analysis.

I am an avid fan of “sabermetrics,” advanced measurements that try to remove outside factors, such as quality of one’s teammates or size of one’s ballpark, from the analysis of the individual.

Sabermetrics isn’t just a baseball concept, though. I believe that a liberal application of these methods could improve our own set of data: the all-important CTECs.

I have found that there is often a disconnect between how people seem to feel about a class and what they put on their CTECs. To get less than a 4 overall, a professor has to be either absolutely tyrannical or completely clueless.

CTECs don’t, however, make it easy to discern the small differences between good professors and great ones. I believe that sabermetrics has the ability to separate the “good professor who gets near perfect marks but isn’t anything special” from the “great professor who most people love, but a few people hate.”

One of the main facets of sabermetrics is the attempt to put performances in their proper context.

For instance, catchers are often poor hitters whereas first basemen are usually powerful sluggers. On paper, a catcher and a first baseman with the same basic stats may seem equal, but sabermetric measures would judge the catcher as more valuable due to the scarcity of hitting at his position.

To bring this back around to CTECs, I have found that a great professor teaching a boring subject, such as research methods or calculus, tends to receive lower CTECs than a less dynamic professor teaching a subject like writing or film that is inherently more interesting to some students. I think CTECs should add a measure for effect sizes, the amount of standard deviations between a professor’s rating and the average rating for that course. Such a metric would more accurately show which professors are truly excelling in a difficult subject and which ones are simply coasting through already-interesting material.

Is there a system that can differentiate between the two? Looking at sabermetrics may provide the answer.

Sabermetrics attempt to remove outside factors from the analysis of baseball players; every one of these measures is based on the ability of each player, without any interference from his teammates’ performances.

This may seem like an obvious concept, but it is actually a common error.

In the case of CTECs, each student’s input is weighed equally. Why? I know I definitely care more about what a fellow senior psychology major thought about a course than what an undecided freshman has to say. After all, that senior’s experience is probably a lot closer to mine, and his or her thoughts on that class will probably be similar to mine as well.

Thus, I propose weighted ratings: Students with similar demographics, such as major and academic year, would have their ratings weighted much heavier than students with whom they have nothing in common.

CTECs are a great resource and have helped me dodge poor professors in the past. However, I think that they fall a bit short when it comes to identifying the professors with whom I will truly form a great relationship.

With these and other sabermetric measures, I can find classes geared right towards my interests and maximize my Northwestern experience.

Sam Gutelle is a Weinberg senior. He can be reached at [email protected].