Wisconsin Basketball vs. Iowa: Analytics Game Prediction

If you missed my latest Wisconsin Basketball Predictions, find them here:

Northwestern | Penn State | Indiana | Minnesota | Michigan St. | Nebraska | Purdue | Michigan | Rutgers | Ohio State

We’ve officially stopped the bleeding. Things looked really good for Wisconsin Basketball in the 1st Half and a good chunk of the 2nd Half. When Ohio State went 1-3-1 in the 2nd Half, that was actually a fantastic move by Chris Holtman. It slowed down the tempo of the game dramatically, and we got very lethargic in attacking the paint, which, in effect, also took us off the FT Line. They also kept chipping away at our lead with some really hot shooting in the 2nd half based on one big hole in our defense.

Our P&R defense wasn’t very good, which I’ll again point to footwork. On screens, we slide or run right into the defender’s chest; we need to utilize better footwork to get AROUND the screener. Getting caught in those screens has allowed the PG to penetrate and put our Drop Coverage defender in a huge bind. Ideally, Crowl/Winter fall right back under the hoop so they can defend the Roll-Man, but with the PG unguarded, they’ve stepped up on occasion, which led to a lot of the Dunks we saw by Ohio State. They corrected in the 2nd Half, always dropping Deep, but that then allowed Thornton to get a lot of easy looks in the Paint.

This will continue to be the biggest thing to correct heading into March. But if we can, the rest of our defense looks VERY GOOD!

With that, let’s dive into the Prediction Model for Saturday’s matchup vs. Iowa!!!

Wisconsin Basketball Prediction Model

Feb 13, 2024; Madison, Wisconsin, USA; Wisconsin Badgers forward Nolan Winter (31), forward Carter Gilmore (14) and head coach Greg Gard celebrate a three point basket during the second half against the Ohio State Buckeyes at the Kohl Center. Mandatory Credit: Kayla Wolf-USA TODAY Sports

First, let’s start off with what comprises my Prediction Model (See Below):

Pace:

Gard Your Fickell’s Model | 70 Projected Possesions

KenPom Model | 69 Projected Possesions

Torvik T-Rank | ???

Haslam Metrics | 67.2 Projected Possions = (Projected Points / “Should” OEFF)

Height:

Wisconsin Basketball has the slightest of Height advantages over Iowa, with an Average Height of 78.39 vs. 78.23 (inches). This “Factor” influences my DREB% Model but is only a part of the equation. Combining the overall Height advantage along with the other Metrics listed in the Model (3PAR, FTAR, 2P%, 3P%, and OPP OREB%), I can then project out each team’s DREB%.

DREB%:

Based on all the combined metrics in the DREB% Model, Wisconsin Basketball is projected to win the DREB% advantage vs. Iowa, with an expectation of UW grabbing 77.78% of their Defensive Rebound opportunities in Saturday’s Matchup vs. an expectation that Iowa grabs only 72.87% of their Defensive Rebound opportunities.

DREB% is a huge component in Stop Factor, which is essentially my own Defensive Efficiency Metric. I’m still working on adjusting my DREB% model to account for past performance and see if a team can have outsized influence over the model metrics. Still debating over the HOW to do this:

• Do I look at overall performance vs. the Model and regress over that?
• Or regress over each factor and adjust each factor in the model?

This will probably take a few weeks to test out! But for now, we’ll stick with the current model.

Stop_Factor:

Wisconsin basketball gets a slim advantage in Stop Factor, coming in at a projected 1.58 Stop Factor to Iowa’s 1.50.

For those unfamiliar with Stop Factor, it’s looking at a Team’s ability to be efficient on Defense.

That can come in various ways:

• Low eFG% given up to your opponent
• Forcing a lot of turnovers
• Collecting a high % of Defensive Rebounds available.

Score Prediction & Model Table:

Final Thoughts on Wisconsin Badgers vs. Iowa

We need to continue stacking wins, and I think there are two things that we can easily control that will help us do that.

The first is Attacking the Rim. I thought we attacked the rim very well on Tuesday until the last 6 minutes when Ohio State switched to that 1-3-1 Zone, which seemed to “force” us into many 3P jumpers.

The second thing is using better footwork to get around screens. I thought our footwork around screens was brutal all game. What we saw was a poor adherence to Drop Coverage principles in the 1st Half, leading to a lot of Dunks. In the 2nd Half, adhering to those principles correctly led to many easy looks for Thronton. But both were built off of defenders getting caught up in screens much more than they should have.

I don’t think Tony Perkins is the type of PG that scares me because I don’t believe he’s dynamic enough or versatile enough as a PG to take advantage of those miscues in the way Thronton/Smith/Love/Cleary/McDaniel could, which may be our saving grace on Saturday.

Attack the Rim | Fight Around/Over/Through Screens | Win Basketball Games

The new Wisconsin Basketball Formula.

On Wisconsin!

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