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Lineups in Review: Rutgers & Nebraska

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Reader Questions and Quick Lineup Takes from Last Week

NCAA Basketball: Nebraska at Iowa Reese Strickland-USA TODAY Sports

How about that? Iowa got some wins against a couple cellar-dwellers. They all count the same in the win column so I’m pleased to see them on the right side of .500 for now. Let’s see if they can take a team (or two) by surprise this week.

From you!

Comments/questions were edited for clarity

Paul requested: Could you provide a description of the statistics used?

This was a mistake not to provide the equations I used. Here is an overview of the Four Factors from Basketball-Reference which are stats developed by Dean Oliver (not this one):

Shooting

The shooting factor is measured using Effective Field Goal Percentage (eFG%). The formula for both offense and defense is (FG + 0.5 * 3P) / FGA.

Turnovers

The turnover factor is measured using Turnover Percentage (TOV%). The formula for both offense and defense is TOV / (FGA + 0.44 * FTA + TOV).

Rebounding

The rebounding factor is measured using Offensive and Defensive Rebound Percentage (ORB% and DRB%, respectively). The formula for offense is ORB / (ORB + Opp DRB), while the formula for defense is DRB / (Opp ORB + DRB).

Free Throws

The free throw factor is a measure of both how often a team gets to the line and how often they make them. The formula for both offense and defense is FT / FGA.

I also use a Net Points Per Minute which is (Points Scored - Points Allowed) / Minutes played. I could normalize by possession, using the (FGA + .44 * FTA + TOV) formula but have made the choice to do it by minute.

Note: I actually had the incorrect formula for Free Throws and used attempts instead of makes in my previous calculations. It was something I didn’t really touch on in my previous write-up but has been adjusted going forward.

StoopsMyAss asked: Does Jok’s presence affect Iowa’s pace?

My calculations didn’t average out to the numbers Stoops provided or KenPom’s calculations. What I can say, is that directionally, Iowa does play faster offense with Peter on the court. On defense, the same can be said. It was especially the case when he was not healthy. Iowa was the cheese, instead of the grater, for those 3 games.

Iowa Possession Estimation

Jok On: Off Poss/40 Off: Off Poss/40 On: Def Poss/40 Off: Def Poss/40
Jok On: Off Poss/40 Off: Off Poss/40 On: Def Poss/40 Off: Def Poss/40
Healthy 79.8 75.0 77.7 74.8
Not Healthy 84.3 77.3 84.4 75.5
Out 0.0 78.6 0.0 80.9
vs NEB 78.1 73.2 69.5 103.2

DrHenryKillinger & Eyeheartfreedumb collaborated: Is Iowa more hesitant to shoot when Jok plays? Is the defense better without him?

Perhaps the easiest stats to address the first question - hesitancy to shoot - are ones not tracked at the college level. I’d say they are secondary assists - passes which lead to passes which lead to made shots - and potential assists - passes which lead to shots taken (Golden State leads both categories by a wide margin in the NBA this year).

Since we don’t have those, I’ll look at the simpler Assists/Field Goals Made. As of 2/6, KenPom ($) has Iowa at 20 in the nation with an assist rate of 61.6% and 2 in the Big Ten using conference-only games. While these numbers are good, they didn’t account for whether Jok is or isn’t on the floor.

Because of how I have my data stored (probably something to improve in the offseason), it wasn’t as quick as I’d like to figure this out for Jok on/off splits. However, I was able to get the information in the following chart, which shows the field goals taken with Jok on/off and the percentage of which are assisted:

Prior to Sunday’s game, it told me there is a difference in offensive stylings without Peter Jok. I do not think this means this version is better than a Hawkeye outfit with a healthy Peter Jok. When Jok is in, Iowa’s offense will run much more pick and roll with him as the ballhandler than they have without him. Against Purdue, that was done to great effect, in arguably his greatest game as a Hawkeye:

In this respect, he showed great deference as a ball handler against Nebraska. Jok led the team with 5 assists, tied with Ellingson, and didn’t force his shot. My eye tells me the shots he took came in the flow of the offense and out of less isolation like his prior 3 games.

Ideally, I would like to see Iowa continue to leverage Pete into more motion sets like they used in his absence. This would relegate the isolation and pick-and-roll to later in the shot clock. This shift might have Jok expending more energy on offense but a reduction of minutes might be for the best as Brady Ellingson and others are proving their value during this time. Their insertion would not represent the same dropoff as it did earlier in the season.

On the other side of the floor, Iowa regularly allows less points per minute without Jok on the floor which results in a better net margin.

Defense / Net Points Per Minute By Jok Status

Jok Off: PAPM On: PAPM Off: Net PPM On: Net PPM
Jok Off: PAPM On: PAPM Off: Net PPM On: Net PPM
Healthy 1.603 1.977 -0.037 -0.056
Not Healthy 1.732 2.224 0.055 -0.682
Out 1.688 0.000 0.413 0.000
vs NEB 1.433 1.852 0.717 0.132

Clearly, the defense is regularly better, by minute, when he isn’t playing. His offensive presence makes up for it, in my opinion. Personally, I focus on the numbers Iowa put up when he was 100%, which show Iowa is roughly the same team, per minute, with or without him.

@ Rutgers (W, 83-63)

Rutgers Lineups by Net PPM

Lineup Points For Points Against Minutes Net PPM
Lineup Points For Points Against Minutes Net PPM
Bohannon-Ellingson-Wagner-Uhl-Pemsl 9 2 2.48 2.819
Bohannon-Moss-Baer-Wagner-Kriener 7 2 2.00 2.500
Bohannon-Ellingson-Baer-Cook-Pemsl 2 0 1.10 1.818
Bohannon-Moss-Baer-Wagner-Cook 28 13 10.80 1.389
Williams-Ellingson-Dailey-Uhl-Pemsl 14 9 6.38 0.783
Bohannon-Ellingson-Baer-Wagner-Cook 6 4 3.40 0.588
Bohannon-Moss-Wagner-Cook-Kriener 5 5 2.68 0.000
Rose-Ellingson-Williams-Dailey-Pemsl 4 4 1.27 0.000
Williams-Ellingson-Baer-Uhl-Pemsl 6 8 3.05 -0.656
Bohannon-Ellingson-Baer-Uhl-Pemsl 2 5 2.32 -1.295
Williams-Ellingson-Dailey-Uhl-Kriener 0 2 1.50 -1.333
Williams-Ellingson-Dailey-Cook-Pemsl 0 2 0.85 -2.353
Williams-Ellingson-Baer-Wagner-Cook 0 3 1.13 -2.647
Bohannon-Moss-Baer-Cook-Pemsl 0 4 1.03 -3.871
  • Perhaps most importantly, Iowa was able to start really strong in both halves unlike many of their other Big Ten games. Ben touched on the lineup in his Day-Lewisian recap, and it really shows through here: +15 in 10ish minutes is really good.
  • An interesting rotation nuance I’ve been keeping my eye on is the rotation of Cook and Pemsl. Their numbers broke out as such: Cook only, +14; Pemsl only, +7; Both off, +3; Both on, -4. Even though Kriener had a bad game, the team didn’t suffer when he was the lone big man on the floor. I’m not the only one fascinated with the Cook/Pemsl dynamic:

v. Nebraska (W, 81-70)

Nebraska Lineups by Net PPM

Lineup Points For Points Against Minutes Net Points Per Minute
Lineup Points For Points Against Minutes Net Points Per Minute
Bohannon-Jok-Baer-Wagner-Kriener 2 0 0.22 9.231
Bohannon-Ellingson-Moss-Jok-Baer 5 2 0.63 4.737
Williams-Ellingson-Moss-Baer-Pemsl 2 0 0.58 3.429
Williams-Ellingson-Jok-Uhl-Cook 4 0 1.45 2.759
Bohannon-Ellingson-Jok-Baer-Cook 7 3 2.87 1.395
Bohannon-Ellingson-Baer-Uhl-Pemsl 3 2 0.93 1.071
Bohannon-Jok-Baer-Wagner-Cook 4 2 1.92 1.043
Williams-Ellingson-Baer-Uhl-Pemsl 7 4 3.78 0.793
Bohannon-Moss-Baer-Wagner-Kriener 7 5 2.73 0.732
Bohannon-Ellingson-Jok-Baer-Pemsl 12 12 5.70 0.000
Williams-Ellingson-Jok-Uhl-Pemsl 2 2 1.30 0.000
Bohannon-Moss-Jok-Baer-Pemsl 3 4 2.52 -0.397
Bohannon-Ellingson-Jok-Wagner-Uhl 3 4 2.02 -0.496
Bohannon-Ellingson-Baer-Uhl-Kriener 2 3 1.73 -0.577
Bohannon-Moss-Jok-Wagner-Cook 11 16 7.72 -0.648
Bohannon-Ellingson-Jok-Uhl-Pemsl 7 11 3.90 -1.026
  • I didn’t predict the starting lineup correctly this time last week, but I’m not convinced they are putting out the right group to begin each half. With Jok still not 100%, but certainly better than he was 2 weeks ago, I think they need to reinsert Baer for Moss and maintain 2 guys who don’t need the ball to contribute on offense. A nice ripple effect of this was maintaining at least of Jok or Baer on the floor at all times.
  • Fran really forced Tim Miles’ hand in both games. He leaned on Baer and Jok to play up a spot in both games. In both games, Jok logged over 27 minutes at the 3 and Baer logged over 11 as a stretch 4. This was the most each guy has played at that position all conference season. This required a slower guy to shadow Iowa’s guards since Tai Webster was the primary defender on Jok during crunch time of both games. This was exacerbated in perhaps my favorite play of the season.
  • The #Platoon of Cook and Pemsl remained in full effect, as they didn’t log a single second together. (+5 with Cook, +5 with neither, +1 with Pemsl)
  • The possession chart above is out of whack for Iowa’s defense with Jok off the court. That’s because they forced turnovers the same amount of turnovers (7) in 20 less minutes. Press Baer was in full effect.

Do you have any questions you’d like me to explore in a later post? Please let me know in the comments below.