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A Statistical Breakdown of ACC Point Guards (Part II)

Part II of an in-depth statistical look at ACC point guards

NCAA Basketball: Virginia at Pittsburgh Charles LeClaire-USA TODAY Sports

WARNING: THIS INCLUDES A LOT OF STATISTICS AND NUMBERS TO MAKE GENERALIZATIONS ABOUT PLAYERS. IF YOU DON’T LIKE DOING THIS THEN I BELIEVE YOU WILL FIND THE FOLLOWING HIGHLY BORING AND/OR CONFUSING.

Part I - Introduction, Methodology and Raw Number Analysis

Alright then! If you have made it this far then congratulations! First of all, you read through Part I, which included a bunch of words and big charts, but now we get to something different! Well...it’s still more words and big charts, but they are PACE-ADJUSTED CHARTS!!!

If for some reason you are here and did not read Part I, then I suggest you click on the link above because this probably won’t make a whole lot of sense otherwise.

Pace-Adjusted

In Part I I broke down all ACC Point Guards into different categories based on their raw numbers so far this year, and then assigned points to each category to determine a ranking system of sorts. I did the same thing for the Pace-Adjusted charts, but used different criteria that effectively measures the same thing as raw numbers do, but actually adjusts on a per-possession basis.

Note that I do use footnotes in this, so you will see those at the bottom with the definition of each of these in case you are slightly confused.

There are what I figured to be the most important stats: Offensive Rating (ORTG, 1), Defensive Rating (DRTG, 2), Usage Rate (USG Rate, 3), Defensive Rebounding Percentage (DR%, 4), Assist Rate (ARate, 5), Turnover Rate (TORate, 6), Steal Rate (STRate, 7).

These are almost always better barometers of what a player is doing on the court because it breaks down the percentage of statistics they are generating on the team, which is more easily comparable to other individuals on different teams. Since teams often will play much quicker, or much slower than another team, this is a better judge of what an individual brings to the table.

Without further ado, here is the chart for pace-adjusted numbers:

Team Player ORTG DRTG USG Rate DR% Arate TORate STRate
North Carolina Joel Berry 124.4 93.4 22.4 12.3 26.3 21.3 2.5
Duke Grayson Allen 121 92.3 24 13.3 20.7 12.2 1.8
Pittsburgh Jamel Artis 119.4 107.2 27.1 13.4 21 15.5 1.2
Syracuse John Gillon 117.3 98.8 20.4 5.2 34.9 17 4
Notre Dame Matt Farrell 116.6 102.8 22.9 7 28.6 18.6 2.2
Florida State Xavier Rathan-Mayes 115.2 96.2 22 12.5 27.7 18.6 2.1
N.C. State Dennis Smith Jr 114.4 98.7 29.2 10.5 35.6 17.2 3.4
Virginia London Perrantes 112.7 90.4 21.2 10.6 26.5 17.5 1.2
Wake Forest Bryant Crawford 112.1 101.5 25.4 12.7 35.8 19.2 3.2
Virginia Tech Justin Robinson 108.4 100.4 21 9.1 23.7 21.6 1.2
Louisville Quentin Snider 108.3 96.8 21.2 6.2 22.8 11.8 0.9
Clemson Shelton Mitchell 107.3 100 20.8 8.2 23.3 22.1 2.3
Miami Ja'Quan Newton 104.1 93.5 27.9 9.6 26.3 21.9 2.4
Boston College Ky Bowman 103.3 98.4 25.6 14.6 22.7 22.7 2.5
Georgia Tech Justin Moore 82.7 105 20.4 6.1 29 27.7 1

Much like I had to sort the Raw Numbers, I used Offensive Rating to sort this chart. Unlike Points Per Game, this actually provides more context as to how good on offense a player really is, and Joel Berry leads the way for this one.

Joel Berry is having a really good year by almost all standards, but especially by advanced metrics. He is first in offensive rating individually, and second in defensive rating. While he holds a smaller role than a lot of other players do (primarily due to the talent of UNC and how much they spread the ball), he is boosted by an above average assist rate and very high field goal percentage. I do note that he has a higher turnover rate than Bryant Crawford, and a much lower assist rate.

Speaking of Crawford, he performed slightly worse in the advanced stats as he did in the raw numbers (T-2nd in raw numbers, 5th in the pace-adjusted numbers).  Part of this is due to his above average usage (ranked 5th in the conference). He is used on 25.4% of all possessions while on the court, and this likely impacts his offensive rating, but his poor shooting from behind the arc and on layups also negatively impacts him. He does have the highest assist rate in the conference, and after adjusted for pace, lowers his turnovers to 9th in the conference.

Grayson Allen continues to do very well, even in the pace-adjusted category, but shockingly well defensively. This surprised me, but his 1.8 steal rate, and overall team defense boosts that.

Perrantes continues to lag behind what the "eye test" might indicate, but admittedly he has a lower offensive rating than I would expect given his 21% usage rating. Quentin Snider’s turnover rate is amazingly low given Louisville's competition this season (ranked 11th in the nation), but Perrantes’ turnover rate of 17.5% is probably higher than most would think.

Now that we’ve seen the numbers, let’s rank them and see how everybody did:

Team Player ORTG DRTG DR% A-Rate TO-Rate ST-Rate Total
N.C. State Dennis Smith Jr 9 8 8 14 11 14 64
North Carolina Joel Berry 15 13 10 8 6 11 63
Duke Grayson Allen 14 14 13 1 14 6 62
Syracuse John Gillon 12 7 1 13 12 15 60
Wake Forest Bryant Crawford 7 4 12 15 7 13 58
Florida State Xavier Rathan-Mayes 10 11 11 10 8 7 57
Virginia London Perrantes 8 15 9 9 10 4 55
Pittsburgh Jamel Artis 13 1 14 2 13 3 46
Notre Dame Matt Farrell 11 3 4 11 9 8 46
Miami Ja'Quan Newton 3 12 7 7 4 10 43
Boston College Ky Bowman 2 9 15 3 2 12 43
Louisville Quentin Snider 5 10 3 4 15 1 38
Virginia Tech Justin Robinson 6 5 6 6 5 5 33
Clemson Shelton Mitchell 4 6 5 5 3 9 32
Georgia Tech Justin Moore 1 2 2 12 1 2 20

Even after adjusting for pace, Dennis Smith, Jr. claims the title as the best statistical point guard in the ACC. Joel Berry and Grayson Allen gave him a run for it, but his assists and steal rate, along with consistently high offensive and defensive ratings, gave him first place.

A name that seemingly came out of nowhere is the Syracuse transfer from Colorado State John Gillon. His offensive rating of 117.3, along with an impressive assist to turnover rate landed him 4th, right above Bryant Crawford.

For those keeping score at home, Bryant Crawford ranks T-2nd in raw numbers and 5th in pace-adjusted numbers. He was hurt by turnover rate a bit, but his defensive rating is what really plummeted him. Once again, this probably matches up with a lot of what people see when they watch Wake Forest play and see his questionable turnovers and porous defense at times.

The bottom of the ACC held steady again, as Justin Moore for Georgia Tech got last in both raw and pace-adjusted statistics, finishing a whopping 12 points behind Shelton Mitchell of Clemson.

Snider finished in 12th place as well, mostly because he doesn’t grab defensive boards, have good assist numbers, or boast a good offensive rating. He makes Louisville go through, and that is what Rick Pitino needs.

Possible Questions and Concerns

Several things popped up as I was going through this that I knew might be asked, or I identified as a possible concern about my methodology:

  • Strength of schedule - Yes this matters, but KenPom adjusts his numbers in some manner to the schedule strength. No I do not know what this is or what their raw numbers are aside from the adjustment.
  • Pace matters. London Perrantes isn’t the 7th best PG in the conference, but he ranks there, even in the "adjusted category". He has fallen off a bit since last year, but he is better than this article would have people believe. He is pretty much the perfect example of being a great fit for his team. The same thing applies to Quentin Snider at Louisville to some extent. He’s obviously not the 12th best PG in the ACC.
  • A lot may argue that Frank Jackson is Duke’s "point guard", but that’s fine. I used Allen. Same thing for Kitchcart over Artis. That may be right now, but Artis is for this study.
  • In terms of ranking the Pace-Adjusted numbers into a chart I realize that a lot of the categories are already ranked within the ORTG category. I decided to go ahead and rank them all anyway to provide more context for a player. On the defensive side of the ball I used defensive rating to determine how good a player was on defense. There are several issues with this, and you can read more about it in the footnote, but it basically focuses on the steals and blocks that a player generates along with how good the team defense is as a whole. It’s admittedly not perfect, but it’s better than nothing at all on the defensive side of things.
This wraps up Part II and pretty much all the nerdy numbers. Part III holds the overall big picture conclusions that can be drawn from the data so far!

1- Offensive Rating - According to Dean Oliver, "The number of points produced by a player per hundred total individual possessions. In other words, ‘How many points is a player likely to generate when he tries?’" The basic building blocks of the Offensive Rating Calculation are Individual Total Possessions and Individual Points Produced.

2-Defensive Rating- According to Dean Oliver, "Defense Rating estimates how many points the player allowed per 100 possessions he individually faced while on the court. The core of the Defensive Rating calculation is the concept of the individual Defensive Stops. Stops take into account the instances of a player ending an opposing possession that are tracked in the box score, in addition to an estimate for the number of forced turnovers and forced misses by the player.

3. Usage Rate- According to Ken Pomeroy, "A measure of personal possessions used while the player is on the court. Simply assigns credit or blame to a player when his actions end a possession, either by making a shot, missing a shot that isn’t rebounded by the offense, or committing a turnover. "

4. Assist Rate- According to Ken Pomeroy, "This is assists divided by the field goals made by the player’s teammates while he is on the court."

5. Turnover Rate- According to Ken Pomeroy, "This is the percentage of personal possessions used on turnovers. It can be highly dependent on context. Players that do little passing or dribbling (i.e. spot-up shooters) will have an artificially deflated TO%."

6. Steal Rate- According to Ken Pomeroy, "This is the percentage of possessions that a player records a steal shile he is on the court. It is computed by Steals/(%Min * Team Possessions).