Two computer models project narrow winning margins in Friday night's playoff game between the Alabama Crimson Tide and the Oklahoma Sooners. Alabama opened as a 1.5-point favorite. On Wednesday, the Crimson Tide was a 1.5-point underdog.
That three-point swing is a chasm compared to the projected score provided by Brian Fremeau's algorithm. Fremeau's model has the Sooners beating the Crimson Tide by a score of 21.4 - 21.3, with a 50.5% probability of Oklahoma winning. Compared to Brian Fremeau, the projected score from Jeff Sagarin's model is an Oklahoma veritable blowout: 24.08 - 22.06.
Fremeau, Sagarin, and others provide meaningful calculations from which to rank teams and predict outcomes. For Friday's game, their calculations are little more than a way of showing that absolutely no one knows which team will win.
The Sooners talk about being confident, but neither team will have a confidence advantage or disadvantage. Both teams will be prepared for a hard slog of a game. One that may be quite low-scoring, with neither team reaching 20 points.
Can the Alabama Crimson Tide win by a whisker?
Upcoming games such as this are often explained as having 'razor-thin margins.' Google's AI offers other similar descriptions: winning "by a whisker, by the skin of one's teeth, by a nose, and by a hair."
From a literal rather than a lyrical perspective, games between two such evenly matched teams like the Alabama vs. Oklahoma contest are often decided by a lucky play or two. They are also sometimes decided by a call or two, which the losing team believes unfairly causes them to lose the game.
Both of the above are most painful ways to lose a game. Going back more than a century, college football coaches have explained to their players that games are won or lost on just a few plays. And that no one can predict the plays in which the pivotal plays will happen. Friday night's game is similar because anyone who claims to know which team will win is confused or lying.