The Spread, Week 10: Exceeding Expectations

I want you to think about the Penn State game for a minute. Hooray, you’re probably thinking, I was just about to do that anyway! Don’t get too excited, because I also want you to think about the Buffalo game. Can’t I just think about the Penn State game twice? No. No you can not.

It’s not exactly a bold statement to say that one is a fine example of Ohio State exceeding expectations this season, while the other is an unfortunate example of the Buckeyes’ failing to meet expectations. We all know that by watching the games and having our own expectations, as fans, for the team’s performance.

We also know that Texas far exceeded expectations by blasting TCU last weekend, because we consume enough sports media to understand where other teams in other conferences stand and what the primary storylines surrounding them are. (In this case, it’s pretty much impossible to turn on ESPN or a sports talk radio and not encounter questions about Mack Brown’s long-term viability as the Longhorns’ head coach.)

And that’s all fine and dandy, but wouldn’t it be nice if we could quantify a team’s expectations (or rather, our expectations for them) and then measure those against actual performance? So instead of just knowing that Ohio State and Texas both did better than we thought they would, we would know how much better and which of those teams did more better. (That’s right, all my English teachers ever, I just used “more better” in a sentence and there’s nothing grammatically wrong with it!)

As you’ve no doubt guessed by now, we can and it’s all thanks to the sketchy subhumans who bet on college athletics and the even sketchier and subber-human beings who provide them the tools to do so. Specifically, I’m talking about The Line and The Over/Under Number, and they are important to us because of what they represent: perception, in numerical form.

The purpose of these two numbers, for bookmakers, is to inspire equal betting on both sides. While I don’t claim to understand the inner workings of it, suffice it to say that it is better for bookies if the money on both sides of each of these numbers is even. That’s why the numbers sometimes change: heavier betting on one side will “push” the number until things even up. Because of this, the numbers are not a prediction of what the outcome of the game will be, per se, but they do represent what the general gambling public collectively believes will happen.

Because of this, it is fair to use these numbers as the expectation for a team’s performance (two teams, really). To do this, we have to combine them to produce a “final score” prediction, which is math so simple, I figured it out. Basically we need a prediction such that the winning team’s score – the line = the losing team’s score and both add up to the over/under number. I’m going to leave it at that, because we ain’t blog to play SCHOOL.

Keep in mind that different sources will have slightly different numbers for each game. This shouldn’t impact results too much. I use this site when possible and Google for any numbers its missing.

So, the “Vegas Expected Score” for the Buffalo game was about 45-11, Ohio State. For the record, our own Jeremiah guessed 52-6 and Buffalo blogger BrandedBull picked 41-17. Together, those two picks come out to about 47-12, which is remarkably in line with the Vegas score.

As you know, things didn’t quite turn out so well and we all felt a little disappointed (although some more severely than others) after the game. While Ohio State’s offense did produce nearly 90% of the projected points, the defense gave up nearly twice as many as expected. These two numbers are combined to get a final “Performance” score, expressed as a percentage. (The final scores for both teams in a single game will total 200%.) It turns out that Buffalo was indeed our worst performance against expectations of the whole season, at a sad 3.34%.

By contrast, the VES for the Penn State game was 36-21. Here at MotSaG, YNBA picked 52-24 and Tony reined himself in to 41-20. We didn’t talk to a Penn State blogger (that is so us), but I did find this, where the three pickers who chose OSU to win went with 34-24, 37-24 and 31-27. Average pick: 39-24, again eerily close to the Vegas prediction.

Once again, things didn’t go how we thought they would, but this time it was in Ohio State’s favor. The Buckeyes posted a stunning 208.33% (yes, that means PSU got a negative score) for this game, third best in the nation last week behind Houston’s upset rout of Rutgers and Michigan State’s manhandling of Illinois. Texas came in 5th with 196%.

What good does any of this do us? Well, it gives us some insight into the intangible areas of overrated-ness and bias. If a team had an exceptionally high score week to week, we might start to wonder if they’re being overlooked or not taken seriously by the media/general public. A team that consistently posts low scores would suggest just the opposite: that they are looked at favorably despite not living up to the hype on the field.

In case you’re interested, Ohio State’s season average so far is 105%, and 122% if you take out the Buffalo outlier. (Note: there were no available numbers for the FAMU game, and I probably would’ve thrown it out anyway.) For the most part, we are playing as expected overall, but are probably a little bit underrated. Michigan’s season average is 89.71%, so they are probably a little bit overrated. Their worst performance was -41.05% against Akron, which is nearly five times worse than Penn State’s loss to us. I’m glad I could make you smile.


  1. […] prediction model based on the Performance Against Expectation measure I introduced yesterday in The Spread. Note that “best” and “worst” are from the perspective of the favored […]

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