Tag Archives: Men’s Basketball

Duke-State Podcast

In this installment, recorded on Valentine’s Day, we discuss Duke-State, the weekend win over Maryland, Miles Plumlee’s possible transformation into Brian Zoubek II, and the diverging paths of Seth Curry and Andre Dawkins. We also analyze the UNC-Miami game, even though this was recorded on Tuesday.

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First UNC Podcast!

Today, on the most romantic holiday of the year, Ben (@TheDevilWolf) and I look back on UNC’s impressive recovery against Virginia, preview Wednesday’s big clash in Miami, examine whether the ACC is the most exciting conference in the country, and even, against everyone’s wishes, spend two minutes on Georgia Tech-Wake Forest. You’ll want to skip that part.

This is part one of the podcast. Wednesday evening, I’ll post the Duke-centric part two. Enjoy, and feedback is appreciated as always.

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Does UNC lack a killer instinct?

I once had a forecasting class where the professor gave each one of us a bag of M&Ms. We were then supposed to count each color and report the results. Predictably some of the M&M bags had more blues, while others had more oranges. My bag in particular had one brown M&M, which was the lowest count of any color in any of the bags. The professor showed the results on a projector and asked the class to imagine each color to be a particular product and that each bag to be an individual store. She then asked what the results meant. Some people said that certain “stores” were better at selling certain “products.” My store in particular was said to be deficient in selling whatever product the brown M&M represented. There was a discussion among people in the class about reasons why certain stores had sold more of certain products. Maybe one store had better employees? Maybe one store sold more “oranges” because they were located in a college town like Syracuse?

At that time I had to raise my hand. I asked the professor if we should maybe consider that the results are random and that it would be a terrible idea to come up with a forecast based on these results. The sample size was way too small, and also we had the advantage of knowing that these results were completely random. For example I doubt that the 6th M&M bag opened in the next class would have a only one brown M&M. Generally speaking it was amazing to watch people try to assign reasons to what they knew were random events. Needless to say I didn’t understand the exercise and I don’t think I impressed my professor with my answer. I wasn’t trying to be a devil’s advocate or a jerk, but rather just start a discussion on the importance of luck in setting a forecast.

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Being wrong…

At no point before or during last night’s game did I think Duke was going to beat UNC. It was a combination of the previous game against Miami and the fact that Duke matched up terribly with UNC. I didn’t know who would guard Barnes, how they would stop Marshall from getting in the lane or how they could prevent UNC from dominating the offensive rebounds. During the game it looked like UNC took Duke’s best shot in the first half and was still up three going into halftime. It didn’t really surprise me that the lead fluctuated between 8 and 12 points for most of the 2nd half. Normally, I don’t text my brother-in-law (the enemy) during the game, but didn’t seem to be that big of a deal because it more closely resembled the Paulus/McRoberts Duke-UNC games. I was content with how Duke played and was actually somewhat ok with them losing to UNC. I was wrong. I was wrong about so many things, but most importantly I was wrong in thinking that Duke couldn’t beat UNC.

Also, I was wrong about questioning any of Coach K lineup decisions. I thought Quinn Cook should play more, and that playing Tyler Thornton wasn’t the best idea. Thornton didn’t have the best game, but this three to start the comeback was an intelligent, critical play. Coach K has been searching for what works with the team, and give him credit for taking a team that lost Nolan Smith, Kyle Singler and Kyrie Iring and leading it to impressive wins against Kansas, Michigan, Michigan State and UNC. I might complain about the team, but they have five wins against top 25 (RPI ranking), which just so happens to be four more wins than UNC has against top 25 teams.  

I was wrong for comparing Mason Plumlee to Josh McRoberts. The middle Plumlee didn’t have the best game, but his steal before Curry’s three was something that at least got him of the McRoberts line. There will be time to analyze his game, but after last night I would like to stay positive.

I was wrong about Austin Rivers. I never really liked watching him play. His outside shot seemed to be at best described as streaky, and I wondered if he was ever going to be a decent three point shooter. Ask Tyler Zeller how his three point shot looks? Anyway, his passion, heart and production last night made me a believer. No matter how the rest of his career goes, Rivers has given me a game and a moment that cements part of his legacy. Just like last year when Nolan Smith and Seth Curry led the comeback against UNC, Rivers never has to pay for another drink around me.

Last night was one of those sports miracles that makes following sports worth it. I had low expectations of the game, and just like a lot of things I was wrong. This was a classic UNC-Duke game and 30 years from now I will still smile whenever I see a replay of Rivers shot to complete the comeback.

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Duke-UNC Recap Podcast, Part 2!

If you missed part one, where Ben and I obsessively dissect the last 2.5 minutes of the game, check it out here.

In part two, we discuss the aftermath of the game, dish out some (dignified) gossip from the locker room, speculate on where Duke and UNC go from here, and analyze the outlook for the ACC. We also enlist your help for a podcast name.

Thanks to all the people who are downloading, and we’d love to hear your feedback. Enjoy!

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Duke – UNC Recap Podcast!

In Part 1 of our recap of Duke-Carolina, Ben and I obsessively pick over the minute details of game’s last two and a half minutes. Our wide-ranging theories are the capstone on the greatest Duke victory of the year.

My written takes on the game can be found at Grantland here (serious, stayed up til 5am writing it) and here (a lot of jokes, took me about 10 minutes).

Ben’s take can be found here, at the Oxford Public Ledger.

Enjoy the pod! Part 2 up later tonight or tomorrow morn.

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At the Quarter Mark: Some Defensive Charting Stats and Observations

We’re 10 games into a season that optimistic Tar Heel fans hope will go the full 40 (31 regular season games + 3 ACCT + 6 NCAAT). Through the season’s opening quarter, Carolina’s adjusted defensive efficiency places 11th in the country– a slight drop from last year’s final ranking of 6th. This post will try to shine some light on which UNC defenders are already in mid-season form, and which ones are still trying to shake off that early-season rust.

Kendall Marshall

2011 (all)
2012 (1st 10 games)
FG% All 37.6 40.0
3Pt% All. 26.5 35.3
FTA Rate 18.8 13.3
TS% All. 47.0 51.3
Pts. All. / 40 10.7 14.6
Deflections / 40 4.17 6.13
Forced TOs /40 2.56 2.30
Off. Fouls Drawn / 40 0.22 0.00
Denies / 40 0.91 0.77
DR% 7.6 7.5
Stop % 58.9 53.8
%Possessions 15.5 17.5
Def. On-Court/Off-Court +2.1 -8.3

Marshall, now firmly entrenched as a starter, is being game-planned against and attacked like one. Teams are challenging him more on the defensive end, hoping to exploit his relative lack of lateral quickness. After being involved (from a defensive charting perspective) in 15.5% of defensive possessions while on the court last season, that number has jumped to 17.5% this year. That, in conjunction with a drop in Stop% from 58.9 to 53.8, has resulted in Marshall allowing 14.6 points / 40– up from 10.7 as a freshman. Part of the reason for Marshall’s lower Stop% might involve some tactical decisions by Roy Williams. Marshall saw significant defensive minutes against both Jordan Taylor and Casper Ware– the types of assignments that might be increasingly handled by Strickland as the games get more and more important.

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The Case for Reggie Bullock

Carolina, the overwhelming preseason favorite to cut down the nets, has sputtered out of the gate to a 6-2 start. And, although one of the losses was on the road to fellow heavyweight Kentucky, that means the natives are getting restless in Chapel Hill. While it certainly wouldn’t solve all of the team’s problems (mediocre rebounding on both ends, inability to consistently finish in the paint, and poor free throw shooting, to name three), I’d like to propose one remedy for UNC’s tepid start: replacing Dexter Strickland in the starting line-up with Reggie Bullock.

Don’t get me wrong: I love Strickland. He’s made huge strides as a junior–namely as a ball-handler/back-up PG/facilitator of the offense and a mid-range shooter (hitting 45% (9-20) of his 10-20 footers through 8 games after connecting on just 27% last season). Strickland’s defense– his calling card– has also been better and more consistent as a junior. The logic for starting Dexter is compelling and straightforward: his strengths (attacking off the dribble in transition, defending ultra-quick point guards) help to offset the weaknesses of backcourt partner Kendall Marshall. He’s also Carolina’s best complementary ball-handler and play-maker– a trait Roy Williams covets from his 2-guard to maximize secondary break efficiency. Add all that to Strickland’s incumbency, and it’s easy to see why he remains in the starting line-up. From a purely basketball perspective, Strickland’s presence in the starting line-up makes far more sense than, say, Drew over Marshall last season. But, while Strickland’s strengths compensate for some of Marshall’s weaknesses, the two share a common flaw: the inability/reluctance to knock down 3-point jumpers. And in a system predicated on feeding the post as a primary option, this shared weakness has had deleterious effects on floor spacing/halfcourt offensive efficiency.

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Carolina vs. Miss. Valley St.: +/- and Defensive Charting

Caveat: Single-game +/- figures are so “noisy” (i.e., influenced by randomness) that they’re rendered practically useless. Even with a complete season’s worth of data, the +/- metric (especially in this– its unadjusted– form) suffers from this noisiness. Still, when taken in conjunction with the defensive box score, traditional box score, and old-fashioned “eye test,” the single-game +/- can be a part of the total evaluation process. It also serves as a good summary of Roy Williams’s substitution patterns/rotation.

Some definitions:

Pts-Pts All.: the points scored and points allowed by the team during a given player’s minutes
Off Eff: the points scored per 100 possessions with a given player on the court
Def Eff: the points allowed per 100 possessions with a given player on the court
Net Eff: the scoring margin per 100 possessions with a given player on the court

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Carolina vs. UNC-Asheville: +/- and Defensive Charting

Caveat: Single-game +/- figures are so “noisy” (i.e., influenced by randomness) that they’re rendered practically useless. Even with a complete season’s worth of data, the +/- metric (especially in this– its unadjusted– form) suffers from this noisiness. Still, when taken in conjunction with the defensive box score, traditional box score, and old-fashioned “eye test,” the single-game +/- can be a part of the total evaluation process. It also serves as a good summary of Roy Williams’s substitution patterns/rotation.

Some definitions:

Pts-Pts All.: the points scored and points allowed by the team during a given player’s minutes
Off Eff: the points scored per 100 possessions with a given player on the court
Def Eff: the points allowed per 100 possessions with a given player on the court
Net Eff: the scoring margin per 100 possessions with a given player on the court

+/- Stats vs. UNC-Asheville

Player Minutes Pts-Pts All. Off Eff Def Eff Net Eff
Watts 9.4 27-19 145.9 108.6 +37.3
Marshall 32.9 80-58 121.2 90.6 +30.6
Barnes 30.1 69-51 113.1 86.4 +26.7
Zeller 29.2 67-52 113.6 90.4 +23.2
Hairston 11.4 32-27 145.5 122.7 +22.8
TEAM 40.0 91-75 115.2 94.9 +20.3
Henson 29.2 63-54 107.7 92.3 +15.4
McAdoo 9.3 23-21 127.8 113.5 +14.3
Strickland 29.5 58-51 100.0 87.9 +12.1
Bullock 11.8 31-32 129.2 128.0 +1.2
Hubert/Simmons/Cooper/Crouch 1.5 1-2 50.0 66.7 -16.7
Dupont 1.1 0-0 0.0 0.0 0.0
White 0.4 1-2 100.0 200.0 -100.0

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