If you’re like me, you love getting into all the newfangled analytics to find out if your favorite sports team is out there really sportsing well or sportsing poorly. After a loss, what’s better than telling the other fan base that despite the real outcome of the game, you’re sports team sportsed better but was really unlucky?

I cribbed all this data from Bill Connelly’s excellent work for the mothership. I don’t know about you, and while completely respect Bill’s wizardry in putting this stuff together, which is a major accomplishment, but my eyes glaze over looking at tables like this. Tables make it really hard (for my human brain) to compare data points across multiple rows and multiple columns. As a result, I began dabbling with a simple visualization of S&P+ data to make it easier to see how teams in the Big Ten are performing.

Once my very simple visualization was ready, I set out to pack as much data into as possible to make it hard to read.

Gentlemen, behold.**

DarkKnight5

The Basics

The horizontal axis represents a team’s defensive potency.

The vertical axis represents a team’s offensive potency.

It follows that teams in the upper left are good, and teams in the lower right are bad. The quadrants on the chart are split by the average rating in each category across all of FBS.

The red point in the top left represents a hypothetical best team, which is a combination of the best offensive rating and defensive rating on the chart. This week, the combination is Clemson’s offense and Alabama’s defense.

Each team in the Big Ten is plotted on the chart using their real ratings, and labeled for your pleasure.

The vector arrows represent how far each team is from the hypothetical best team, using the Pythagorean equation: a^2 = b^2 + c^2. The magnitude of that vector is included in the team’s label. The smaller the magnitude of your team’s vector, the closer they are to being the best. The larger the magnitude your team’s vector, the closer they are to being the absolute worst, looking at you Rutgers and Purdue.

Next, I drew some curves to make it easier to evaluate the teams against each other, if they’re not in close proximity on the chart.

The Results

A few things are obvious. S&P+ expects Michigan and Ohio State to be really good. Michigan State and Penn State are both expected to be top-25 performers this year. Then there’s a mass in the middle with Minnesota, Iowa, Wisconsin and Nebraska.

Minnesota and Iowa are well-rounded teams.

Wisconsin is expected to be really good on defense but to have a glaring issue with offense. Nebraska is expected to be strong on offense but struggle defensively. Their game in October could be really interesting. Or really boring. Or really meteor. Which do you prefer?

The best part of this is that it validates my fear of Illinois in the TDG Staff Predictions. Gopherguy05, GoAUpher, and I all see a trap game on the road against a middling team. They just think it will be Maryland and I think it will be Illinois. Time will tell.

Best Offense: Nebraska

Worst Offense: Northwestern

Best Defense: Michigan

Worst Defense: Rutgers by a hair over Indiana

That pretty well sums-up my analysis. Let me know if I missed anything in the comments.

**Updated to include Non-Conference Opponents