Analytics, Basic Stats, and Recent Historic Context: The ABC’s of Penn State Basketball? – NCAA Tournament Round of 64

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Introduction

Like many of you, I have been a huge Penn State basketball fan for my entire life the entire month of March.

A deep, somewhat unexpected run in the Big Ten Tournament that saw wins over Illinois, Northwestern, and Indiana (and an almost-win vs. Purdue in the title gam), propelled the Nittany Lions to their first NCAA Tournament appearance since 2011. In fact, this is only the third time this century that Penn State received an invitation to college basketball’s Big Dance.

This 2022-23 transfer-heavy version of Penn State hoops plays a very fun brand of ball – from its  deep 3’s and air traffic controller-like stress, no matter if Micah Shrewsberry’s crew is winning or losing. It’s been a heckuva magic carpet ride thus far…and it’s not over.

In the Round of 64, Penn State faces the Aggies of Texas A&M – a consensus underseeded group that finished 2^nd in the SEC in both the regular season and conference tournament. It will be no small feat for our Nittany Lions to get past TAMU but we’re all going to be there watching when the game tips off at 10:00 EST (after a nap from 6-8 PM, of course.). Until then, why don’t we recycle some of the same analytics principles we dish out during football season and apply them to basketball, for the first time in the history of this blog, in order to break down this match-up and see how Penn State and TAMU stack up.

Normally, with all of these stats, we’d have broad context across the entire NCAA sample set for multiple years. Today though, we’re going mano a mano to compare these two teams as directly as we can.

Scoring

We’ll start our analysis by examining game-level scoring offense and defense. In the graph below, we display team scoring by game in the top panel (left is Penn State, right is TAMU) color-coded to differentiate Home vs. Away/Neutral. TAMU averages 73.6 PPG and PSU 72.2. Of note here is that Penn State has a fairly obvious bias of scoring more at home than on the road; the Nittany Lions score 76 points at home and 69 on the road. That may be a big concern with the game being held in Des Moines, Iowa and not State College. Texas A&M scores 73 points at home and 74 on the road – so setting doesn’t seem to matter for Buzz Williams’ boys. Overall though, the distributions are pretty similar and I would venture that these datasets are not meaningfully different.

The bottom of the graph charts out the scoring allowed – or scoring defense – for each team. Once again, no huge difference between the two teams in this metric. For the H/A splits defensively, though, the Lions fare about the same whether they’re in the BJC or beyond. At home, they allow 66.5 points and away they allow 70.4. Conversely, Texas A&M allows a full 10 points more on the road than they do at home (60.5 versus 70.6). Both teams have one high outlier of more than 100 points allowed.

Basketball analytics is often done in terms of possession efficiency (points per possession) where possesions are calculated by: field-goal attempts – offensive rebounds + turnovers + (0.44 * free throw attempts). A team in a college game will have about 70 possessions per game (which coincidentally is the average number of plays for a team in a college football game; interesting symmetry fact).

For our match-up, it’s more or less the same story as points per game – the two teams are equal in terms of points per possession at 1.10. Penn State does have a worse H/A split thought with 1.14 (home) and 1.06 (away). Texas A&M has nearly equal possession efficiency at home and away.

In points/possession allowed (bottom of graph) we see that while TAMU is better overall allowing 0.97 points per possession to Penn State’s 1.04, they average 0.9 at home and 1.03 away. Penn State is worse at 1.08 away but being on the road should help lessen the overall disparity a bit.

Three Point Shooting

Penn State lives and dies by the three point shot. Of course, that is a somewhat hyperbolic statement to make after the Big Ten Tournament when the Lions shot below 40% from long range in every game, well shy of the pre-March percentage in games they won. Regardless, three point shooting is a metric where there’s clear advantage for the Nittany Lions who are making deep shots at a rate of 39% versus 32% for the Aggies. Both teams are allowing a similar rate of 3’s made (32.3% for A&M and 33.6% for Penn State). As far as splits goes, Penn State shoots nearly 38% on the road and just better than 40% at home – so no huge swing when the setting changes. This is a relatively low differential. And when you add in A&M’s defense’s grander H/A splits (allowing 30% at home and 34.2% on the road), this is an area where shooters like Jalen Pickett, Andrew Funk, Seth Lundy, Myles Dread, etc., can fuel what would be a mild first-round upset.

Furthermore, the next chart measures each team’s 3-point attempt rate – in other words, the percentage of possessions in which each team attempts a 3. Penn State shoot a 3 on 41% of their total possessions compared to just 28% for A&M. That equates to roughly 10 more 3-pointers per game for the Lions.

To contextualize how important this long-range discrepancy can be for the Nittany Lions, let’s assume in a standard game both Penn State and A&M have 66 possessions. In that scenario, Penn State is going to take 27 3-pointers on those 66 possessions.  If the Lions shoot their road/neutral site average of 38% from beyond the arc, they will score 31.4 points on 3’s. A&M, on the other hand, will take 18 3-pointers and shoot 31% at a neutral site, good for 17 points on average – obviously you can’t make a fraction of a 3, but you get the idea. The Nittany Lions will need those 14 bonus bombs-away points to come to fruition.

Rebounding

My biggest fear for this game is that Penn State gets destroyed on the boards. And if shots aren’t falling, it could get ugly. This metric marks a clear disadvantage for Penn State going into the game. Below is the Rebound Differential for each team. Penn State averages  a -2.5 rebound differential per game versus competition whereas A&M averages +6.1 rebounds per game. The Lions will have to box-out, find opportunistic offensive rebounds, use their limited length, and get some rim luck to hang with the Aggies. Can it happen? Sure. Actually, Penn State performed better than average in rebound differential in the Big Ten Tournament …well, until the Purdue game when they got Edey’d.

We’re here Nittany Lion fans. We are finally in the NCAA tournament for the first time in over a decade. Now, as we wait until Thursday we can crunch numbers and find points of hope and points of concern. But, it’s March and it shouldn’t shock anyone if this team makes a run and goes deep into March (or dare I say April). Because, as the team said on Saturday, “Why not us?”