A Statistical Case for Not Ranking the Utah Utes After Four Football Games in 2015

A dry title, to be sure, lol.

I was not born there, but I am a Utahn, having lived the majority of my life there. I was raised as a Cougar in Happy Valley, schooled as a Cougar, served two years spreading the Cougar faith, lost my Cougar faith and faith in any supernatural animals, married while living in Salt Lake City, tried some more school as a Ute, had my first born at St. Mark's hospital, moved to Oregon for winter time air that doesn't make you sick and keeps you sick. I like Salt Lake City, the only city along the Wasatch front I'd even remotely consider living in again, though I'd probably have to live somewhere above the inversion. I'd live in Red Butte garden if they let me, I love that place.

All of that doesn't add up to one byte of date to influence my lines one way or the other. I work purely with numbers, and the formulas are blind to history or expectations. OSU and MSU started the season in my top 4. OSU is barely hanging onto my top 25, while MSU is now out. That might lead you to believe that Utah would be in my top 25, having defeated two teams who have been in the top 25 at some point this season, and are 4-0 overall.

I concede that Utah is probably better than I rank them, but I maintain that only time and more box scores will tell if that is true or not. QB Travis Wilson's injury and time missed to me means that the Utes, when he is healthy as he currently is, are a little bit better than their season statistics would indicate. Not a lot, but at least a little. He has a much higher yards per carry average than backup Thompson, and a higher QB rating. Fortunately for the Utes the only full game that Wilson missed was against their weakest opponent to date, Fresno State.

I also concede that I am not a schooled statistician or mathematician. I am a commonsensian handicapper who figured out pretty early the best way to utilize a limited set of box score stats to make future projections. I arrived at the same starting point for handicapping as the famed Dr. Bob and any other number of computer based handicapping groups that ultimately shape the market lines each week. From that base each of us chosen how to reformulate the data into successful projections. The basis of my spread and total projections comes down to the run/pass matchups for each game, and then grading the results of each game versus the opponent's usual averages. There are then, naturally, four main match up units.

Let me start with Utah's one unit which I do rank in my top 25 -- their run offense. They ran for 189 yards against Michigan at 3.5 yards per carry, 1.2 ypc better than Michigan has allowed on average this year. It was still 1.2 yards less per carry than Utah averages this year, which is the same success level that UNLV and BYU had against Michigan's defense. Michigan's run defense was at it's best versus Oregon State, who they held to 2.4 less ypc than they usually average. After the Michigan game Utah had two fairly average days running the ball against Utah State and Fresno, which coincides with Thompson filling in for Wilson at QB. With Wilson back, the Utes had their best game on the ground of the year against Oregon. Oregon's run defense had been looking particularly suspect after allowing Michigan State to run on them, the only time this season MSU has had a really good day running the ball. Oregon's defense stepped up last week, though, for the first time this year, really limiting Colorado's success on the ground.

Utah's passing game is decent, but also took a hit when Wilson missed time. Thompson doesn't get the ball downfield as well as Wilson. Like I said above, I think Utah is better than I rank them because of Wilson being healthy now, but probably not quite enough to crack my top 25. It would be close. If Wilson were not to have missed any time and if he'd played a little better than average during that time there's a good chance Utah would have made my rankings.

I handicapped the NFL for many years before I switched over to college football a few years ago. I'm always tinkering with my spreadsheet trying to find ways to correctly interpret the statistical results of each game in a predictive manner. Before one season I added an offensive and defensive number to be input for each game for each team that indicated the health of those units coming into each game played. I believe I broke it down by starting quarterback as well. Nobody's going to argue the huge difference that typically exists between the starting QB and his backup in the NFL. Based on those "health" numbers for each game, a team would have it's performances shifted up or down to some degree, to reflect whether they were playing against a much weaker backup QB or not, for example. I have not, as yet, added this to my NCAA spreadsheet. It is something I would like to do when I have time to do so. I'm sure Utah would be closer to being in my top 25 if I had this implemented.

Let me also do a quick look at the Utah defense. I rank them 46th vs the run and 82nd vs the pass based on this year's stats alone. Against the run they started off strong versus Michigan, still did very well against Utah State, but have since turned in below average performances versus Fresno and Oregon, given those schools averages this year. Against the pass it took until their last game against Oregon to finally hold a team under its' usual ypp average. That means three below average games versus FBS opponents and then one stellar game against Oregon.

So those are the numbers and stats I'm looking at. To make statements beyond the numbers, I think they are fortunate they played Michigan in week #1, at home. First year coaches usually start off struggling, even if they are Jim Harbaugh, lol. The final stats of that game were pretty close, and Michigan was only trailing by 7 with possession of the ball in the 4th quarter until the pick 6 thrown by Ruddock made a comeback highly unlikely. Michigan's pass defense, in particular, has been much stronger since the Utah game.

Total yards are typically not a very useful handicapping tool, but they do tell a little bit of the tale. Michigan outgained Utah by 18, Utah State outgained Utah by 46, Utah outgained Fresno by just 15, and Utah outgained Oregon by 130. If you look at the NCAA average of yards gained versus points scored, you can see that Utah has exceeded that average every single game this year. The good teams will beat that average, typically, because of special teams, better execution of the offense and defense in the red zone. This number is easily skewed, especially in the short term, by special teams scores, of which Utah has had more than one this year.

Utah has done unbelievably, and almost certainly unsustainably, better than average in this yards to points business. They are #1 in the FBS scoring 10.2 points more per game than the average team does with the yards they've gained. Last year for the entire season Louisiana Tech led this category with a 10.8 point differential. Georgia was in 2nd with 9.0, and Ohio State 3rd with 7.4. No one else was 7 or above. Luck coupled with efficiency is a difficult thing to sustain. Last year Utah finished with a +4.8 differential. That is pretty good. Is it reasonable to expect after four games that Utah is going to be more than twice as efficient and lucky at turning yards into points than they were for all of last year?

Defensively they have the 15th best differential, allowing -5.1 points less than the average team would normally score for the yards gained. Last year Utah had a defensive differential of -0.8. Mississippi State, coincidentally, leads that category defensively so far this year, and they were supposed to be the worst defense in the SEC West according to some. Thanks, Bulldogs, for costing me a play on the Over more than once this year. And your -3.8 offensive differential hasn't been helping, either.

Dave Bartoo's Top 25 is an analytics poll, not a resume or anecdotal evidence poll. I guess analytics is a pretty broad term and technically can include metrics as simple as just looking at the final scores of games. Successful football handicapping against the spread and total may include some shading of statistics based on the final score, but is much more likely to involve betting against inefficient lines that were created anticipating a certain amount of equal betting based on previous final scores.

Dave's poll is supposed to reflect where you think each team would finish in the rankings if they were somehow all able to round robin play each other, with your projections based on the analysis of the statistics available year to date. I personally do not think making top 25 projections based almost entirely on efficiency ratings largely determined by luck over a small sample size of games is a viable method.

In spite of my long term success at setting sharper-than-opening lines, I'm not going to say that how I've chosen to turn my usual handicapping numbers into a top 25 poll is the best possible way. I am going to say that my numbers, who don't care if you're Ohio State or Texas State, are not putting Utah into the top 25 yet after the four games they've played so far, and I'm comfortable with that when looking at the numbers. If they end up beating Cal this week in a statistically strong fashion, though, they just might steal the spot Cal has at 21st while sending the Bears back into the ranks of the unranked.