Welcome to the first KenPom update of the 2020-21 Rutgers men’s basketball season! For those new to the site or these articles, this is something I write up every 4-5 games during the season, to offer a big-picture view of Rutgers basketball built primarily off of advanced analytics (particularly the KenPom efficiency metric, which you can access here and read more about how it works here).
Advanced analytics, of course, are designed to supplement, not replace, the eye test. I continue to trust the eyes and experiences of people who professionally coach basketball and evaluate basketball talent, but it’s also important (and for nerdy people like me, interesting) to take a look at the numbers behind the performances and see what trends emerge.
It’s been a while since I’ve posted one of these, so here are a few reminders about the numbers I’ll refer to throughout the article:
- Overall team rankings (KenPom ranks every team in D-1 from 1 to 357): at the time of this writing, Rutgers is ranked 26th in the nation by the KenPom metric, which is three spots away from an all-time high (RU was briefly ranked as high as 24 back in January).
- Offensive and defensive efficiency ratings: These numbers are indexed to every 100 possessions, where a rating greater than 100 is good for offensive efficiency and a number below 100 is good for defensive efficiency. For example, right now Rutgers is 57th in offensive efficiency with a rating of 106.9 (6.9% better than the average D-1 team, which is nice) and 13th in defensive efficiency with a rating of 88.1 (11.9% better than the average D-1 team, which is even better).
- Individual players have offensive efficiency ratings, too, which we’ll get to in just a minute.
Without further ado, let’s get to it.
Piscataway is Lob City
What’s craziest to me about the numbers I just presented in the bullet points above is, if you watch this team play, with the exception of a few minutes in each of their first four games I’m not even sure they’re playing to their full potential yet.
Using the eye test, you’re likely to see moments like in the first half of the Syracuse game, when Rutgers pierced Syracuse’s zone defense with three passes within five feet of the basket to set up an open layup and you’d be right to think to yourself, “Wow, this looks like a top-20 offensive team in the nation.” But then you’d see the first part of the second half of that very same game, and you’d be right to think more critically. But then you’d see Rutgers finish that game on an incredible offensive run and whipsaw right back around. Being a Rutgers fan is a weird experience, sometimes.
Anyway, looking at the numbers for individual players, you’d be correct to say Rutgers looks like a more finely-tuned offensive machine in the early going of this season, even compared to the end of last season. For instance:
- Ron Harper, Jr. had an offensive efficiency rating of 111 last season (which itself is really good and team-leading). This year he has been at 142 (42% better than the average D-1 player!!).
- Jacob Young has improved from 85 (below average efficiency last season) to 107.
- Montez Mathis has improved from 94 (again, below average) to 106.
Taking into account the Geo Baker and Caleb McConnell injuries which have largely left Rutgers with a six-man rotation (more on this below), and what you have are Rutgers’ arguably three most important players right now each showing a significant increase in their offensive productivity.
When you look deeper at some of these numbers, it’s even more stunning. Ron Harper, Jr. will likely not play all season with an offensive rating of 142 – it’s a small sample size against largely inferior competition, so numbers like that are bound to come down to earth. For reference, last year Luka Garza finished the year at 117. Two years ago, Zion Williamson led the nation at 129.2 (LOL). But let’s say, for the sake of argument, Harper Jr. finishes the year at 120ish in offensive efficiency. Does the NBA come calling? Just a thought.
Freshmen Will Be Freshmen
With the exception of Cliff Omoruyi, and exceptions should rightfully be made for top-50 recruits, Rutgers is limiting the exposure and minutes given to its freshmen players. This is for a good reason, as the eye test and advanced analytics align to tell us the youngsters are experiencing some growing pains in the early going.
Whether to give the majority of minutes moving forward to Cliff Omoruyi vs. Myles Johnson (as of this writing, it’s been roughly a 50/50 split) is an interesting debate. Myles has been better at shot blocking and offensive rebounding, while Cliff has been better at defensive rebounding and has been the more efficient scorer. I’m not sure there’s an easy answer, but if Cliff can stay out of foul trouble, I am of the opinion he should start and he should play a majority of available minutes at the 5. Am I a little scared of him going against some of the 20- and 21-year old centers in the conference, from a pure physicality perspective? Yes, I am. But I still think the above, unless and until he shows some obvious reason that he shouldn’t. (Nothing against Myles Johnson, whom I think is awesome – I’m thinking about this purely from a “floor” and “ceiling” perspective, but Rutgers knows Myles’ ceiling and maybe needs to see Cliff’s ceiling).
When I evaluate freshmen from an advanced analytics perspective, I look at the improvement from December through March. In essence, I grade them on a curve (and I think I’m going to do even more of this in 2020-21, when practice time is limited by the pandemic). So I’m not even going to post specific offensive efficiency numbers for the other freshmen right now. Instead I’m going to say, stay tuned and enjoy watching them grow, because I think they each have talent.
A Six-Man Rotation
Expect Steve Pikiell to keep giving each of the four freshmen at least a few minutes in every game, because with Geo Baker and Caleb McConnell both out (McConnell for the foreseeable future with a redshirt season), right now Pikiell’s Inner Circle of Trust likely consists of six players. Do you remember when Pikiell used to run a 10-man rotation and seemingly sub players like a hockey line at every opportunity? Pepperidge Farm remembers.
Check out how minutes have been distributed so far this season:
- Jacob Young: 85% of available minutes
- Ron Harper, Jr: 81%
- Montez Mathis: 81%
- Paul Mulcahy: 81%
- Cliff Omoruyi 51% / Myles Johnson 49% (putting these on the same row because, that brief Twin Towers experiment during the ‘Cuse game aside, I think it’s interesting the numbers add up to 100%)
Until Geo Baker gets back, Rutgers is in a rotation with the above six players playing the vast majority of the available minutes, with other players (Doucoure, Reiber, Mag, Palmquist) playing on an as-needed basis. When Geo Baker gets back, it’ll be interesting to see how things shift. Last year, Geo came back on the bench for several games, essentially working himself back into shape as the conference slate proceeded. It took him about a month of regular action to get back to being himself again, also.
With this knowledge, it may be the case (read: Pikiell may now have the luxury) to bring Geo back even slower this season. I honestly kinda hope he does, because Geo’s too important to rush back. It’d be a bummer if they did that and he re-injured himself. Of course, on the other side of the coin, Rutgers now has very little margin of error in the event a player gets into foul trouble, or worse, experiences an injury. Let’s hope Geo comes back reasonably soon, and all of this is a non-issue.
The Look Ahead
Here are the games as currently scheduled (eek) for the remainder of the calendar year 2020, along with Rutgers’ expected win probability in each game:
- at Maryland: 46%
- vs. a ridiculously good Illinois: 53%
- at Ohio State: 35%
- vs. Purdue 59%
It’s statistically possible Rutgers wins each of the next four games (there’s roughly a 5% chance if you’re into combinatorial mathematics). But that being said, there are very few games in the Big Ten conference that aren’t in that 30-60% win probability range for this Rutgers team. It’s all about which Rutgers team shows up, how prepared they are, and just the random fluky stuff that seems to happen in every college basketball season.
As an overall note about the above percentages, I’m a little concerned about the projections because I think KenPom still treats home games as if they’re happening in front of a crowd. We all know there’s a RAC effect – KenPom’s statistical model treats it as being worth almost 4 points per game – but it’s not the same with empty stands. But, we’ll see how it goes as it unfolds.