ADVERTISEMENT

Prediction Contest Results Through Syracuse - Contest #2

Prediction Contest results through Syracuse
Contest #2
Check your results!




111​
venom660turbo
99​
Heels5150
87​
IDUNK4HEELS
87​
montana_heel
87​
slothrop8
87​
Travis2262
84​
the Sky is Carolina Blue
84​
gobblercalls
84​
Goheels83
81​
shane023
81​
adwood81
81​
RoseHeel
78​
heels05champs
73​
djones1975
72​
Munkles
72​
Go Heels #1
69​
notashelbyfan
69​
Camacot
68​
Tarheelsman71
66​
39 Feet Above Sea Level
66​
dtodd4475
66​
tarwhiz
63​
Steat
63​
gregkb14
62​
HOWSWEETITISTOBEATARHEEL
60​
Ozheelfan
60​
imajericho
60​
jrhessey
57​
DSouthr
57​
HeelzLover
57​
jim0742
54​
al would
54​
TPFKAPFS
54​
srcmt
51​
SorryNotSorry
48​
NorCalTarheel
45​
Kadyn930
45​
tarheel0910
42​
sctarheel30
42​
racinheel
40​
Tarheels39
39​
gauchoheel
33​
uncrph
30​
Rabidfrog
27​
Frog77
24​
pooponduke
24​
uncboy10
24​
Camel79
24​
lum1-h-dogg
24​
Sk1310
24​
whitie1234
24​
RobJones__
24​
ChiShankCity851
24​
roadmaster
24​
strummingram
21​
What Would Jesus Do?
8​
KinstonNC

Stat Dive (part 2): Possessions Per Game

I acquired all of the Division I team data since 2002, and from that we can observe some fascinating trends and data relationships in the data. This is a multipart series exploring some of that data.

MBB_PossPerGm.png


Next up is game pace. The graph shows total possessions per game, by year, for the last 23 seasons, through the morning of February 15, 2024 (242,559 games in all). This analysis uses the "Smith Method" of defining a possession which is defined as ending whenever a team loses control of the ball. A possession can end with a made basket, a trip to the free throw line (1-and-1, 2, and 3-shot situations), a turnover, or an attempted field goal. It is important to remember the latter when gaining an understanding of this data compared to data published elsewhere. Stay tuned for much more on the topic of Possessions when I address the Ken Pomeroy data.

The grey line shows the per game average for all of Division I, while the green line shows the possession average for teams that made the NCAA tournament that year. Once again we see little difference in pace of play between tournament teams and the national average. Therefore pace isn't very useful in predicting a team's propensity to make the tournament.

In 2023 the average game had 158.7 possessions, with a standard deviation of 8.2. So, 2/3 of the games generally ranged from having 150 to 167 possessions, and 90% of games fell in the 142 to 175 possession range.

The national average, incidentally, is trends steeply upward in 2016,. This was the effect of reducing the shot clock from 35 seconds to 30 which increased game tempo by about 4%. This also explains the upward movement of scoring that we saw in the scoring graph in Part I of this series. Since that point, however, there has been a slight downward trend in pace of about 0.55 possessions per year.

UNC, shown in blue, has had significantly higher-paced games than the rest of the nation. We know that one of Roy Williams' tenants of coaching was faster play, so it stands to reason that his teams had more possessions than others. On average, his teams had 8.1% more possessions than the rest of the nation.

In addition to Possessions, I'll circle back later about Points Per Possession in great detail soon.

Next up: Field Goal Percentage
  • Like
Reactions: TarHeelMark

Lack of minutes being played by the bench lately

Andrew have a question which you may not be able to answer, but maybe you can ask Davis on Thursday. Does the starters still use the philosophy which some teams use that when they are fatigue they give the tired sign for some rest? Or is this dictated by Davis when he believes they are tired and he substitutes, since most of our starters never want to leave the game. Yet it appears there are a lot of tired legs out there toward the end of the game, and it shows with the execution.

UNC at Syracuse game thread on Tuesday 13 February 2024

The last two Tuesday night games have been awful for UNC so hopefully Carolina can navigate all the snow that New York have gotten the last two days and MELT AWAY any chances the Orange have of getting into March Madness.

Coach Adrian Autry and his team come into this contest badly needing a big win as they just stand 15-9…They have some excellent guards in Notre Dame transfer JJ Starling and the always reliable Judah Mintz. Chris Bell and Quadir Copeland also are big time scorers for the Cuse.

Syracuses biggest weakness might be in the paint where center Naheem McLeod is out for the year and their other center is like Trimble a game time decision. If Carolina is smart they will feed Bacot all night long and take full advantage of him in the paint.

Like the Clemson game the Orange can come out and hit everything in sight and build up a big lead but even with a large crowd despite all of the snow outside of the Carrier Dome cheering them on in my humble opinion Carolina just has to much firepower to lose another dreaded Tuesday night game.

As much as I too would like to see a Trimble suit up again in the visiting Carolina blue he might be held out again and have him ready for a Virginia Tech team on Saturday…

I might miss portions of this game especially at the beginning because I took the wife to Myrtle Beach to celebrate Valentine’s Day but if that is the case I will chip in when I can because the wife in my case is a priority…Give em Hell Heels and take no prisoners and leave no doubt…
  • Like
Reactions: Heels5150

Stat Review: @Syracuse (2/13/24)

STATVALUEPCTLEHISTORICAL COMPARISON
Base Stats
FG%48 54
UNC_statBox_50.png

3FG%44 77
UNC_statBox_75.png

2FG%50 45
UNC_statBox_40.png

FT%82 84
UNC_statBox_80.png

fg%63 0
UNC_statBox_0.png

3fg%47 11
UNC_statBox_10.png

2fg%71 0
UNC_statBox_0.png

ft%72 40
UNC_statBox_40.png

PTS/POSS1.03 75
UNC_statBox_75.png

pts/poss1.26 0
UNC_statBox_0.png

TOTPOSS145 7
UNC_statBox_5.png

POSDIF9 84
UNC_statBox_80.png

%LOB14 62
UNC_statBox_60.png

%lob12 19
UNC_statBox_15.png

SmithIdx-0.33875
UNC_statBox_0.png

Interesting Stats
ast/poss0.16 47
UNC_statBox_45.png

AST/FG0.66 72
UNC_statBox_70.png

OR%0.41 73
UNC_statBox_70.png

or%0.17 81
UNC_statBox_80.png

%FROM344.395
UNC_statBox_95.png


STAT = Statistic being reported
VALUE = Value of reported stat from the current game
PCTLE = Percentile When Compared to All UNC Games since 1996
Historical Comparison = Graphic Portrayal of PCTLE. Marks depict 20% quintiles, as well as 50%.

FG% = UNC Total Field Goal Percentage (47.0% avg since 1996)
3FG% = UNC 3-point Field Goal Percentage (35.6%)
2FG% = UNC 2-point Field Goal Percentage (51.4%)
FT% = UNC Free Throw Percentage (70.0%)
fg% = Opponent Total Field Goal Percentage (41.6%)
3fg% = Opponent 3-point Field Goal Percentage (33.8%)
2fg% = Opponent 2-point Field Goal Percentage (45.9%)
ft% = Opponent Free Throw Percentage (68.2%)
PTS/POSS = UNC Points Per Possession (Smith Method, 0.934)
pts/poss = Opponent Points Per Possession (Smith Method, 0.846))
POSS = UNC Total Possessions (Smith Method, 85.6)
POSDIF = UNC Advantage in Total Possessions (Smith Method, 2.03)
%LOB = UNC Percentage Loss of Ball (TO/POSS, 15.9)
%lob = Opponent Percentage Loss of Ball (to/poss, 16.4)

MOV = Margin of Victory (9.43)
%FROM3 = UNC Percentage of FG Attempts Taken From 3 (35.6%)
AST/POSS = UNC Assists Per Possession (Smith Method, 0.20)
AST/FG = UNC Assists Per Field Goal (0.59)
AST/TO = UNC Assists Per Turnover (1.4)
OR% = UNC Percentage of Missed Shots that are Rebounded (0.344)
%from3 = Opponent Percentage of Shots Taken From 3 (33.8)
ast/poss = Opponent Assists Per Possession (Smith Method, 0.16)
ast/fg = Opponent Assists Per Field Goal (0.52)
ast/to = Opponent Assists Per Turnover (1.1)
or% = Opponent Percentage of Missed Shots that are Rebounded (0.241)
poss = Opponents Total Possessions (Smith Method) (83.6)
TOTPOSS = Total Possessions in the Game(Smith Method, 169.3)
SmithIdx = UNC Total of Pts/Poss minus Offensive Goal (0.95) + Defensive Goal (0.85) minus Opponent Pts/Poss (avg: -0.01)
Discussion
The Heels, coming off a near loss against Miami, found themselves on the true loss column again at Syracuse, with a 7-point defeat.

Contrary to much of the post-game analysis, this was a very good offensive game for UNC, scoring 1.03 points per possession. The Heels shot a bit above average overall (48%), but were excellent from 3 (44%). They did turn it over on 14% of their possessions, which is a bit more than average.

Defensively, however, the Heels were, once again, not good. Syracuse scored 1.26 points per possession, a level only seen 3 times in the last 1,013 games. Syracuse did it with red-hot shooting, especially within the arc (71%). We've only seen 1 team shoot better, 2015 Pitt.

Once again, UNC didn't for many turnovers, allowing Syracuse to turn it over on 12% of their possessions.

This was very slow-paced game, as well, with only 145 total possessions. We've only seen 62 slower games in the last 1,013 games.




So was this a putrid defensive performance or was Syracuse just out of their minds? We pondered the inverse a month ago when teams like Syracuse were shooting under 20% from 3-point land. Was it great defense or did UNC just face teams that happened to be cold? This is where the Percentage Loss of Ball is useful. Defensively we usually see an inverse relationship between Pts/Poss allowed and %LOB; the better the team is at preventing scoring, the better they usually are at forcing teams to turn it over.

When UNC was "holding" opponents to such low shooting numbers, I was suspicious because those teams were turning it over on less than 10% of their possessions as well. I have never believed that this is an elite defensive team. That said, while last night's defense was the biggest problem, it wasn't that bad. I've maintained that this team is, defensively, below the program's standard. Under Hubert Davis, guards are not forcing turnovers. We saw Duke penetrate and easily get to the ball 8' from the basket, but we also saw Syracuse penetrate with ease. This will be a key differentiator for this team in March.
ADVERTISEMENT

Filter

ADVERTISEMENT