🚨 STATE OF THE PROGRAM 🚨

This will be our first official blogersation although we have had many unofficial ones. Is Bucky just in the middle of a minor setback, or is this program in trouble? 

CHORLTON:  

UW was a nothing basketball program before Dick Bennett. Maybe there are defenders of Stu Jackson and maybe even Steve Yoder. They did do their part to push the program forward, but there was still precious little in results on the court. Other than the magical final 4 run in 2000, Bennett didn’t do anything that would be considered miraculous at any other mediocre program. It was just miraculous for UW. 

Prior to Bennett, UW had only 2 winning seasons in conference play since 1954. Bennett had 3 NCAA tourney appearances which matched the program's total prior to his arrival. In 1998-99 he coached the team to their first ever 20 win season. 

I won’t get into the greatness of Bo Ryan here, as we have discussed it much before. If Bo did what he did at any school, it would have been great. The fact that he did it at a program that was as horrible as UW shows his genius. Now that he is gone, and many of the players he recruited and developed are gone, is UW returning to its history of awful basketball?

I heard a sportscaster discuss this idea a while ago. I don’t remember who it was, but I liked what they said. Paraphrasing from memory- 

There are only so many basketball geniuses in the world. UW had one in Bo Ryan, and that’s what allowed them to have 15 years of unprecedented success. What are the odds they had 2 sitting on the bench at the same time?

What do you think Torvik. Is UW headed back to another 40 years of losing basketball?

TORVIK:

No, I do not think UW is headed back to Yoder era and beyond. I actually don’t think that’s even possible anymore. For better or worse, Wisconsin is a sports school now. If Gard doesn’t get it done, he will be replaced. And they will be willing to spend big bucks to bring in a worthy successor. There’s just too much money at stake. 

But it is probably unreasonable to expect the miraculous success of the Bo-era will continue. You quote an unnamed sportscaster wondering about whether there were two basketball geniuses on the bench at Wisconsin all these years. I’m almost 100% sure that unnamed sportscaster was me, because this has been a talking point of mine, almost word for word. In any event, I agree with the premise that some slippage is almost inevitable. The only question is how much. Let’s break this into three possible tiers:

1) Tier 1: Still a regular contender, but with occasional down years. Still capable of putting together a team that might make a final four. Similar to Purdue and Michigan have been the last 5-10 years, but below the Ryan-era teams and Matta-era OSU teams.

2) Tier 2: A step below—almost always at least on the bubble, in the tournament most years, but hardly ever a contender. I’m thinking post-2005 Bruce Weber at Illinois and Kansas St. here.

3) Tier 3: Bottom level of acceptable high major success: some bad years, some years where you make the tourney, but never a contender. Illinois, Minnesota.

Based on the history you describe, I think Badger fans should be ready to embrace being a Tier 2 team. I put Bruce Weber in Tier 2 and Illinois in Tier 3 for a reason. If Gard is able to have Tier 2 success and it isn’t good enough for the fans, a fall into Tier 3 is really, really likely. 

And I think Gard can keep UW in that Tier 2. He’s no Bo Ryan, and there’s reason to be concerned about how this year is going, but it’s pretty silly to look at his overall performance and not be optimistic that he’ll be able to take UW back to the tournament regularly. For example, I’m a big optimist about next year. This team has no scholarship seniors, a genuine star in Happ, lots of promising Freshman minutes, and two starters injured. So there is good reason to think this is a blip, and next year will be a quick bounce back.

What’s your feeling—does Wisconsin still need a basketball genius to stay out of the cellar?

CHORLTON:

No, I agree that the UW program has fundamentally changed since those lost decades. Donna Shalala, Pat Richter, and Barry got UW to invest in the athletic program, and unless there is a change in that philosophy the program will not be what it once was. Now that UW has built the Kohl Center, renovated Camp Randall, built new practice facilities, and upgraded locker rooms, scoreboards, etc. their facilities are on par with the best programs around. They may not pay their coaches the highest salaries, but they are competitive, and they will pay to keep a head coach who shows they can win. 

Before I start predicting tiers, let’s discuss a few points about the direction of the program. I’ll break it into 2 sections, players and systems. I’ll start with the players, and leave systems for the next section. I mean both recruiting and player development, and I think there is reason for concern with Gard on both. 

The recruiting got off to a pretty decent start. With Bo leaving midseason Gard didn’t have much time to put anything together his first year, and took what looked like 2 big reaches in Ford and Trice. Trice looked like a guy that could be a player last year in limited minutes, but appeared to take a step back this year before getting hurt. Ford has showed enough promise in his first year to give you some hope that Gard can find diamonds in the rough. In addition to that, he kept the commitment of King through the Ryan retirement, and added Reuvers and Davison who look like they could be great players someday. 

Then we had the decommit of Herro, and the miss on Hauser. Bo missed on big time instate recruits too, like Matthews and Vander Blue so this is nothing new for UW, but it doesn’t help either. I don’t know a ton about the 2 guys that replaced them except that the center wasn’t even promised a scholarship for his freshman year, and they both have already said they intend to redshirt. Hard to get excited about guys that plan to redshirt before they have even practiced against the guys they are competing with for minutes. No commits for 2019 recruits yet, but it is still early, and there is still a scholarship open for 2018. If Gard doesn’t get some players to get excited about, it makes him vulnerable if UW struggles again next year. 

On to player development which worries me a lot more, especially this Junior class. With Bo, we all just got used to the idea that the players got better every year and took that for granted. With 3 years learning under Gard, Van Vliet, Illikainen, and Thomas show little to no progress, and Iverson and Pritzl have only shown minimal gain. You could argue that Happ is the only player to make significant strides since Gard took over. Player development may have as much to do about picking players that want to get better as it does coaching, and the Junior class are Bo’s players. Still, it’s hard to ignore how little that class has progressed. While the Freshman class looks like it will be great someday, that assumption is based on those guys all getting much better, and the Junior class makes me doubt that the freshman will progress like the Bo players we are used to.

Any of this making you nervous Torvik?

TORVIK:

I admit you’re making me a little nervous, but more in anticipation of your “systems” breakdown (which I have reason to fear will be withering). I’m more optimistic on the players.

Gard’s first two classes as the man in charge yielded Trice, Ford, Davison, Reuvers, and King. Though I agree he probably got a little lucky with Trice and Ford, that is a very solid core—exactly the kind of core that the Badgers have regularly developed into Big Ten contenders this century. Assuming King comes back full strength and Davison isn’t permanently hobbled by his shoulder, I expect that core to compete in the upper half of the Big Ten the next three seasons.

But I can’t argue with your analysis of the 2015 class. It was a poorly conceived class: four forwards and a shooting guard, which left them reaching for a point guard the next year—and contributed to them not recruiting Sam Hauser, which everyone can agree now was a mistake. They took a gamble on a raw athlete in Iverson, and they didn’t hit the jackpot. The struggles of Illikainen, Thomas, and Van Vliet are well documented. Pritzl, who should have been the jewel of the class, seemingly lost his mojo when he stepped on a crack and broke his … foot. That said, I have not given up on Pritzl and Illikainen could still surprise us with a Duje-type senior year.

Is it Gard’s fault that these guys haven’t developed as hoped? I don’t really buy it. I’m frankly not a big believer in coaches really developing guys in terms of actually making them better players. For example, I roll my eyes when people say that Kentucky turns out pros. What happens is the future pros choose Kentucky. Something similar typically happens at Wisconsin. Players who are willing to put in the work to develop, and spend some time on the bench while they do, are the kind of players that Wisconsin attracts. But ultimately the development is mostly on the player. It’s not that coaching doesn’t matter at all—it does, though I think the ways in which it matters are pretty mysterious—it’s just that the basic formula doesn’t require a Svengali as coach. So maybe I’m being naive, but I give Gard a pass for that Junior class. I think it was just a bad break.

Future recruiting has become a bit concerning, though. It’s funny—there was a moment last summer when I thought it seemed that Gard had really ushered in a new era of improved recruiting at Wisconsin. Obviously the 2017 class was very good on paper. Gard had a commitment from Tyler Herro, not the kind of player that typically chooses Wisconsin. (Spoiler alert.) And it seemed that they actually had a shot to pull Joey Hauser in despite Bo’s snubbing his older brother. 

But it all fell apart. Hauser picked Marquette, as he was probably always destined to do. Wisconsin’s primary backup plan, Nate Laszewski (whose dad played at UW in the 80s), blew up on the AAU circuit and committed to Notre Dame. Tyler Herro decommitted. Suddenly the 2018 class was kind of a disaster. They’ve partially redeemed it by getting the Currie kid, who had previously committed to Michigan, but as you say he is not an immediate contributor. While top-level recruiting has never been a huge part of the Ryan-era formula for success, my hope was that Gard could potentially make up for not being a basketball genius by being a bit better at recruiting than Bo was. It’s still possible that will turn out to be true, but the jury is still out.

CHORLTON:

OK, I think we agree that there is at least some reason to be concerned with the players, but maybe not enough to panic yet. Next year should be very telling. I’m pretty much writing off the 2015 class, but if all the freshman and sophomores that are getting so much playing time this year don’t take a big step forward, Gard is in trouble. It’s probably too late for Gard to salvage the 2018 recruiting class after the big misses. He’ll have 5 open scholarships for the 2019 class, so he had better get some quality commits early in the process to maintain excitement for the future.   

On to the offensive and defensive systems. It would be nice if this group did one well, but both offense and defense are awful this year. I fear the system that has served UW well for the Bo Ryan era is fading away. When I look at the box scores for a game, I look at shooting percentage and the differentials between turnovers, and offensive rebounds. Those things usually tell you the story of the game, and the Badgers, like all good teams have done a good job dominating the differentials over the Ryan era. In any given game your team can go cold, or the other can get hot, but if you get more opportunities by dominating the differentials you will prevail despite shooting woes. 

There are various ways to win the differentials, but Bo used limiting turnovers, and dominating the defensive glass. This year’s team is bad at both, but all of Gard’s teams have not performed in these areas. For turnover percentage Gard’s teams have ranked 120, 68, and 102. Since 2008, Bo’s worst rank was 68, and that was an anomaly, as the 2^nd worst rank was 9. For opponent’s offensive rebound percentage Gard’s teams ranked 61, 42, and 78. Bo’s worst since 2008 was 32. To be fair Gard’s first 2 teams won 22 and 27 games including 12 conference games and both went to the sweet 16 despite those numbers, so there is more than one way to skin a cat. I just think it’s clear that Gard is going a different direction than what has worked in the past. 

I had intended to use this section to go on a rant about this year’s offense and how they can’t figure out if they are running isolation or swing, and how the defense is too complicated for inexperienced players. In the end though, I’m not sure it matters when they have at times put a team on the court that has 3 guys that walked on to the program. It’s hard to limit turnovers when Iverson constantly travels, gets the ball swiped, or passes to no one, and the alternative is more TJ Schlundt. While this year’s team is frustrating to watch, the change in turnovers and rebounding are not isolated to this year’s team.

Do you think Gard is intentionally changing Ryan’s system for success, or is he just not as good at teaching guys how to do it? Is Gard changing the system because the Ryan system at UW is past it’s time? The freedom of movement rules have changed the game, and change is not necessarily bad. Gary Anderson’s offensive changes were a disaster, but the 3-4 defense he brought has kept UW’s defense humming right along. 

What do you think?

TORVIK:

I do not think that Gard is intentionally changing the Ryan system—but I do think the formula may be outdated. Not because it doesn’t work, but because everyone is using it now. Bo was at the vanguard, and used shot volume to wring wins out of lesser-talented teams. After about ten years of doing this, other coaches finally grudgingly admitted that it was ingenious and started doing it (namely: protecting the defensive glass and limiting turnovers) themselves. At around the same time, however, Wisconsin got super talented and put together its best sustained run ever. So we didn’t notice that the underlying formula might not work as well without elite talent.

Let me explain this a little further. You correctly point out that Wisconsin used to rank among the elite in turnover percentage and defensive rebounding percentage, and now they rank as mediocre. That is correct, but it obscures the fact their actual performance hasn’t changed much. Look at the turnover numbers:

Year   TO% Rank

2018  18.0  120

2005  17.9   22

An even starker example, using last year’s full year numbers:

Year   TO% Rank

2017  17.0   71

2006  17.4    9

In other words, a turnover percentage that used to rank among the elite, now ranks among the mediocre. Wisconsin hasn’t really gotten that much worse at committing turnovers, it’s just that literally everybody else has gotten better. A lot better. Last year’s turnover percentage would have been top 10 nationally in any of Bo’s first five season at Wisconsin. I think this is an extremely important and overlooked fact.

A similar, though less drastic, thing is happening with defensive rebounding:

Year   DR% Rank

2018  26.1   61

2014  27.4   15

2007  26.7   15

2003  26.7    9

(Lower is better in this stat.)

As recently as 2014 (when the Bo got to his first Final Four) a defensive rebounding performance like this year’s Badgers would have been considered elite rather than mediocre. 

My conclusion is that the game has changed, in large part because of Bo Ryan’s success. And now that it has changed, it is far from clear that the Ryan formula for winning at Wisconsin will continue to work. After all, his last half-season was an unmitigated disaster—and these problems of relatively higher turnover rate and relatively poor defensive rebounding were big factors in that disaster.

If I’m right, what that means, unfortunately, is that Gard will have to make changes to keep the level of success up. As I mentioned earlier, the easiest path to success would be to use the same sound formula but increase the average talent level. If he can’t increase the talent level, he’ll have to figure something out schematically—some kind of inefficiency that others haven’t seen—to maintain the level of success. And that’s the kind of thing that typically only a basketball genius can do.

CHORLTON:

Fantastic points. So, if we are going off the assumption that Gard is not a Bo Ryan like genius, Tier 1 is looking less and less likely to me. I would add 2 other changes to the game that will probably adversely impact UW. I have no empirical data to back these up, just have a feeling from what I see in games and how I feel things are going. The rule changes to the game at all levels seems to be favoring 2 types of players; guards that can create for themselves and their teammates off the dribble due to freedom of movement rules, and stretch big men. 

Freedom of movement, and specifically the removal of the hand check, allows smaller quicker players to flourish. Those players were marginalized for a long time because bigger/longer guards could keep up with them by just sticking a hand on their hip and controlling them. Now they can blow by that bigger, slower player and get opportunities in the lane they never had before. Once they beat their man, they also cause help to collapse and this opens up a lot of open 3 pointers. 

Here is where the stretch big man comes in. When you have a big guy that can shoot that means he has to be guarded on the perimeter. This just makes that little guy better, because the lane isn’t clogged with a 7 foot center who only cares about protecting the rim. The stretch big also gets wide open 3s from the guards that break down teams off the dribble, and can shoot right over the top of any smaller guards that may rotate out to challenge the shot. 

I don’t think either of these are groundbreaking or controversial observations, but I bring them up because they specifically relate to UW recruiting. Traditionally UW has not recruited those ball handling guards very well, while they have had a never ending stream of stretch big men. I don’t think anything is likely to change with UW's struggles recruiting those types of guards. Davison is as close to one as we have had since Traevon Jackson, and Traevon certainly wasn’t a big time recruit. The only other that comes to mind was Trevon Hughes, and he wasn’t special either. While UW should be able to keep getting stretch big men, now every other team in the country wants them too, so we have a lot more competition for them. 

There will probably be a lot more of these kinds of players to pick from in the future, so maybe this concern is overblown. Young kids see the stars of today and emulate them, and the stars of today are those types of players. So maybe in the long run UW is still able to get their types of players, but this trend doesn’t seem to favor UW.

TORVIK:

Completely agree with those observations. Ties into the main cause of this year's disappointment, which is that Andy Van Vliet could not stay on the floor. He was the stretch four we were promised, and it hasn't worked out. (At least in Gard's mind—and the fact that he went from a guy that Gard thought was our most improved player to a guy who he wouldn't even put in during mop-up time is a possible red flag, in my opinion.) 

I actually think Trice is more of the model for a point guard that can exploit the new freedom of movement than Davison, at least right now. Davison is not particularly quick, and when he does get by his guy it's by using strength and going full steam ahead—so he has little ability to make good passes on his drives. (Which is related to the fact that he usually ends up on his back out of bounds.)

So the Trice injury and the Van Vliet experiment gone awry have been absolute killers for this season, in my opinion. I don't look at those as permanent new features of the program though.

Ultimately, it seems like we're in agreement that the program is likely to take a step back, but hopefully can remain in the "tier 2" range as I've defined it. I'll give you the last word.

Chorlton:

Yep, I think tier 2 seems most likely long term, because the program will get rid of Gard if it looks like they are falling toward tier 3. I would not have thought firing Gard this year was remotely possible before this season. I still think it is unlikely, but I wouldn't rule it out anymore. We didn't even get into some of the other questionable decisions, like the Reuvers redshirt, then not redshirt. Or remember when the Badgers played that awful zone defense?

The team doesn't look like it is quitting on Gard which would be a big warning sign. They just look frustrated with the losses, and bad play. With all the injuries and youth Gard gets a pass, but I think we will have to revisit this post around this time next year.

Big Ten Season Predictions

Big Ten conference play starts tomorrow, including a couple of surprisingly important games (Northwestern at Penn State, Michigan State at Minnesota). Time to get our picks in for the record.

Before I do that, an aside. Before the season I had two bold predictions: (1) Michigan State would be a bubble team, and (2) Wisconsin would win the Big Ten by at least three games. I feel pretty good about one of those. A guy can dream for the other.

Now let's take a look at what T-Rank is saying:

Rk	Team	Rec
10	Purdue	14-4
12	Wisconsin	13-5
17	Indiana	12-6
29	Michigan	11-7
32	Minnesota	11-7
40	Northwestern	10-8
43	Ohio St.	9-9
55	Illinois	8-10
68	Maryland	8-10
67	Michigan St.	7-11
83	Iowa	7-11
86	Penn St.	6-12
93	Nebraska	6-12
95	Rutgers	6-12

If that came to pass, we have the top six Big Ten teams in the tournament, with Ohio State, Illinois, and Maryland on the bubble, and Michigan St. on the outside looking in. You can also see the (relative) strength of the bottom of the conference this year, with even Rutgers projected to win 6 games.

Here are the T-Rank title odds:

And here is the T-Rank WinMatrix™

Finally, my subjective predictions:

Wisconsin	14–4
Purdue	13–5
Indiana	12–6
Michigan St.	11–7
Michigan	10–8
Northwestern	10–8
Ohio St.	10–8
Minnesota	9–9
Maryland	9–9
Illinois	8–10
Iowa	7–11
Penn St.	5–13
Nebraska	4–14
Rutgers	4–14

Badgers vs. Creighton in gifs

After fighting back from and 8-0 deficit and taking a 26-20 lead last night, the Badgers went very cold from the field, missing 11 straight threes. It started with Trice missing an open three after a great find from Iverson:

At least that play ended with an offensive rebound that was eventually converted into a layup by Happ. The Badgers led 28-20. It would be their biggest lead.

The Badgers continued to play patient, frankly beautiful offense against an overly aggressive and shaky looking Creighton defense. Here, Creighton aggressively doubles Charlie Thomas in the post, and a second later Nigel Hayes gets a wide open three thanks to a clever Showalter screen:

Again, a ludicrous doubling of Charlie Thomas leads to crisp ball movement and an open three for Alex Illikainen:

Showalter breaks down the D off the dribble and drops it back to Illikainen for another wide open three:

Now things get a little nutty, with Charlie Thomas hanging out on the perimeter. But still, an open three for a capable shooter after an ineffective double team in the post:

Koenig breaks down the D off the dribble, gets triple-teamed, wide open three for Thomas again:

The only questionable shot in this sequence is Koenig off the dribble. My guess is he was sick of watching other people miss:

 

Showalter gets into the lane and dishes to Illikainen for another open three:

Creighton D running around aimlessly leads to open three for Showalter:

Wide open three for Nigel Hayes after Jordan Hill draws a lot of attention down low:

Vitto Brown also missed an open three in this period but my recording of the game flaked out for that.

That's 11 open threes, all missed, most of them great shots, most of them the result of nice offense against ineffective defense.

Hit four or five and the game is probably won. Oh well. Keep shootin', boys.

A legendary sequence REDUX

Since Vine is going away, thought I'd post here for posterity's sake a gif of my one quasi-viral Vine:

As you know, Adam, I was always a pretty big Bill Murray fan. I even ran two separate "Bill Murray for President" campaigns: one in 1996, which involved chalking up Bascom Hill with various slogans ("It's a Cinderella Story...") and one in 2000, which involved plastering the University of Minnesota Law School with "Bill Murray for President" posters.

Alas, those days are gone. Now Bill will forever be "sad Xavier fan" and hopefully soon also "sad Cubs fan" to me...

How much do unbalanced conference schedules matter? Not much.

One of the many downsides of the trend towards mega-conferences is the death of the round-robin conference schedule in basketball. The resulting unbalanced schedules raise the distinct possibility that regular season conference championships will be decided by quirks of scheduling fate rather than talent and coaching tantrums directed at referees as God intended.

The Investigation

But how much difference do unbalanced schedules actually make? To find out, I looked at every season since 2008-09 and used T-Rank to calculate each team's:

1) Expected wins against the conference schedule it actually played;
2) Expected win percentage against a true round robin, and used this to calculate expected wins based on actual number of conference games;
3) Expected chance of winning a share of the title against actual schedule;
4) Expected chance of winning a share of the title against round-robin schedule.

The differences between 1 & 2, and 3 & 4 show the effect of an unbalanced schedule, though in slightly different ways. So I looked at both.

First, the conclusion

Overall, the data is pretty clear that unbalanced schedules are rarely extreme enough to be decisive. By far the dominant force in college basketball is variance, and that's why we love it. All the data is available here.

An Extreme Example: Wisconsin 2016

Let's look at the results for Wisconsin last year as an example.

Expected wins against actual schedule: 10
Expected wins against balanced schedule: 10.8
Chance of winning title against actual schedule: 1.8%
Chance of winning title against balanced schedule: 4%

Obviously, the Badgers got a bad draw last year. Indeed, the -.8 wins is the second most difficult schedule in the entire database. But it's hard to say that even this extreme schedule had much of an effect on anything. The Badgers finished a full 3 games behind Indiana. Even accounting for Indiana's favorable schedule (+.34 expected wins) the Badgers still finished 1.86 adjusted games back:

Team	Wins	EW Diff	Adj. Wins	Actual EW	Blnced EW	Actual Ch%	Blnced Ch%	Ch% Diff	Adj GB
Indiana	15	0.34	14.66	13.4	13	29	22.4	6.6	0
Wisconsin	12	-0.8	12.8	10	10.8	1.8	4	-2.2	1.86
Michigan St.	13	0.22	12.78	14.5	14.3	61.9	56.6	5.3	1.88
Iowa	12	-0.59	12.59	11.3	11.9	6.3	10.8	-4.5	2.07
Maryland	12	-0.37	12.37	11.5	11.9	6.8	11.8	-5	2.29
Purdue	12	-0.2	12.2	13	13.2	23.3	25.7	-2.4	2.46
Ohio St.	11	0.23	10.77	8.3	8.1	0.1	0.1	0	3.89

Perhaps more importantly, the Badgers were an extreme long-shot to win the title under a balanced schedule (just 4%) and while the unbalanced schedule cut those long odds by more than half, it's still hard to complain too much about that.

The few examples where it made a difference

Now for the fun stuff: Looking for examples where an unbalanced schedule actually made a difference. First, I looked for teams that didn't win the title and finished less than .5 "adjusted games back." Here they are:

Team	Year	Conf	Wins	EW Diff	Adj. Wins	Actual EW	Blnced EW	Adj GB
Coastal Carolina	2014	BSth	11	-0.22	11.22	10	10.3	0.43
VCU	2012	CAA	15	0	15	14.3	14.3	0.47
Dayton	2009	A10	11	-0.46	11.46	9.7	10.2	0.48

So just three teams over 7 seasons finished less than .5 adjusted games back, and even these three barely cleared the .5 threshold.

VCU is an interesting one because their schedule actually did not disadvantage them compared to a balanced one. The problem was that that the Colonial champs that year, Drexel, had a very favorable schedule, worth +.53 wins. Most importantly, Drexel only had to play VCU once, and that game was at Drexel. This is when an unbalanced schedule can be really unfortunate: when there is a clear top two that play only once, the team that gets the home game has a big advantage.

The other way I looked at this was to calculate likelihood of winning a championship. I think this is less good than looking at the "adjusted wins" because it's entirely hypothetical. For example, Wisconsin vastly outperformed expectations in conference play last year -- winning 12 games when T-Rank would have expected a team of their quality to win only 10 on overage. As it happened, Indiana also won two more games than expected. But if they'd won 13, as expected, it would have been fair to say that their easier schedule and Wisconsin's harder schedule combined to rob UW of a championship. But if you just look at the simulated difference in Championship expectations (4% vs. 1.8%) for Wisconsin, that doesn't show up.

That said, here are the five teams whose championship odds were negatively affected by 10% or more:

Team	Conf	Year	Wins	Actual Ch%	Blnced Ch%	Ch% Diff	GB
Mount St. Mary's	NEC	2010	12	37.1	53.9	-16.8	3
VCU	CAA	2010	11	28	43.5	-15.5	4
VCU	CAA	2012	15	48.6	60	-11.4	1
Syracuse	BE	2013	11	12.9	24.3	-11.4	3
Butler	A10	2013	11	15.1	26	-10.9	2

VCU's 2012 team shows up again, as does its 2010 team. But the 2010 team illustrates the downside of this purely hypothetical analysis: that team actually finished in a tie for 5th pace, a full four games behind Old Dominion. Similarly, each of the other teams (other than 2012 VCU) finished at least 2 games out of first. So although all these teams definitely got screwed by their schedules, they didn't perform well enough to really feel sorry for them.

Caveats

So the overarching conclusion is that most of the time unbalanced schedules are not that big a deal. But a couple caveats:

1) The conclusion that unbalanced schedules don't really affect conference championships doesn't mean that there aren't other effects. Clearly, a tough schedule can easily cost a team one win, and it's not that unusual that one win is the difference between making the NCAA tournament and sitting at home. Pertinently, the 2010 VCU team noted above has a good claim to losing one win based on a bad schedule. That team ended up losing in OT to Old Dominion the Colonial Tournament Championship game, and didn't make the tourney -- despite being No. 51 in Kenpom. It was the next year that VCU snuck into the tournament, as a First Four participant, despite a significantly worse profile, but rode Almighty Variance to the Final Four.

2) Although most schedules are balanced enough most of the time, this is only true in the end. It's still very important to look at who's played whom at a given point in the season. For example, Indiana got a lot of flack about its Big Ten schedule last year, even though in the end it was just marginally favorable. But the real issue was that their schedule was extremely unbalanced temporally, with a very soft 7-game stretch to start. That was a legitimate thing to point out at the time, even though IU continued to surprise even when things got tougher, and cruised to the title in the end.

3) I haven't looked into this systematically, but the trend does seem pretty clear toward more extreme results recently. This is not a surprise, as the rise of the super-conference is relatively recent, and is still in progress. So although we haven't definitely seen it yet, we likely will see an unbalanced schedule decide a major-conference championship soon enough.

Who's gaming the RPI this year?

Among the RPI's well-known flaws is that it can be easily gamed. As Luke Winn explained several years ago:

Seventy-five percent of the RPI formula is about strength of schedule (SOS), and because the RPI uses the flawed metric of raw winning percentage to assess SOS, it fails to provide a true measure of the quality of opponents. The truest measure available is kenpom.com's NCSOS ranking, which creates a pythagorean winning percentage based on opponents' adjusted efficiency, and even adjusts for home/neutral/road situations, which the SOS portion of RPI does not.

So in the RPI, your schedule is essentially your destiny. To show this, I set up a hypothetical bubble team (with a pythag of .8000 on a neutral court) and ran the RPI for that team playing every team's announced 2016-17 schedule. Obviously, this excludes later rounds of holiday tournaments and unannounced games, but these have just minor effects at this point.

The results are available the T-Rank bubble-rpi page. About half the schedules produce a bubble-team rank between 40-60, which is what you'd expect since the hypothetical bubble team in question would be around #50 in the T-Rank. So bubble-rpi rank around 50 shows that a team's current schedule is reasonably neutral for RPI purposes.

The team with the "best" schedule for maximizing the RPI of a bubble team is North Carolina's. A bubble team playing North Carolina's announced schedule (notably missing two rounds in Maui, including a possible game against Wisconsin), would be expected to go 17-12 and rank 16th in the RPI. Would that be enough to get into the tournament? Assuming those 17 wins include a number of top 50 conquests, I think so. It compares to what Oregon State did last year: 18-12 on Selection Sunday with an RPI rank of 33 and a number of "good wins" got them a 7-seed (!) despite a Kenpom / T-Rank around 60th.

That said, a schedule like North Carolina's is probably not the most advisable for a true bubble team, because it comes to its high ranking rather honestly: by playing a lot of tough games. Sure, the average bubble team would win 17 games, but a bubble team that got a few bad bounces could easily miss the NIT with that schedule.

The schedule with the best mix of good projected record and good projected RPI rank is probably Rhode Island's. A bubble team playing Rhode Island's schedule would project to 21-8 with an RPI rank of 18 -- pretty much a sure thing for the tournament. Rhode Island will also play either Duke or Penn St. in their preseason tournament, in which case the projected RPI rank changes to 17 or 20, respectively. In any case, a bubble team playing that schedule is looking at very likely at least 19 regular season wins and a top 20 RPI. Well done Rams!

How did they do it? The old-fashioned way: lots of beatable mid-majors, and no worthless sub-250 cupcakes. The only downside of their schedule is that it doesn't provide a lot of opportunity for resume-building top-50 wins, and that's why T-Rank currently projects the Rams among the last 4 teams into the tournament (FWIW).

On the flip side, the schedule with the absolute worst RPI profile belongs to North Carolina Central out of the MEAC. A bubble team playing that schedule would be expected to go 22-3 but rank 128th in the RPI. The big problem for NC Central is the MEAC: it has no good teams, and they're all going to get ground to dust in the non-conference.

But of course no potential bubble team plays a schedule like NC Central's, so let's look instead at the worst RPI schedules among high major teams that might have designs on a tournament berth. In that cohort, there are really just four teams that have unusually unfavorable schedules:

Texas Tech rather famously gamed the RPI last year, but Tubby's successor will have a much less favorable slate this year. Their non-conference schedule includes a pathetic seven games against sub-250 projected teams, plus #232 North Texas.  That said, they benefit from playing in the Big 12, which projects to be strong top to bottom, so even if they are a bubble-quality team this year (and T-Rank thinks they'll be slightly better than that) they should pick up enough quality wins in conference play to neutralize the stigma of a low raw RPI rank.

Two teams that could suffer from their unfavorable schedules are Utah and Northwestern. Of Utah's eight D-I scheduled non-conference games, six are of the RPI-killing cupcake variety. Throw in Utah's two games against non-DI teams (which don't count for RPI) and 80% of Utah's scheduled non-conference is garbage. Utah does have two games TBD in the Diamond Head Classic, and if they play Illinois St. and San Diego St. that would lift the bubble-projected RPI to 58th. But they've got probably an equal chance of playing Hawaii and Tulsa, which would change the projection back to 68th. Given that Utah could well be a bubble team this year, this schedule could do them in.

Northwestern is less likely to be a bubble-quality team, but if it is its schedule could be a limiting factor. Northwestern also plays six RPI-killing cupcakes. Even more respectable opponents like DePaul and Wake Forest are probably a negative, because those are major conference doormats likely to end up with a bad record -- but they're also very capable of pulling an upset. So it's taking a risk of a loss without any SOS bump.

Ultimately, this exercise illustrates the most damning thing about the RPI: a hypothetical bubble team could finish anywhere between 16th and 128th, completely dependent on its schedule. In other words, the RPI is primarily a metric that measures schedule quality, not team quality.

Some thoughts on Nigel's Decision

As we all know, Nigel Hayes is contemplating whether to turn pro instead of returning for his senior year of college. The deadline for him to decide is May 25th.

Fans and pundits (including Dickie V himself) are nearly unanimous: Nigel, come back!

There are a few fans -- seemingly put off by Hayes's outspokenness on the NCAA's essential contradictions -- who think Nigel is gone. He's sick of college, they say. He'd rather do anything that play another year of basketball for free. 

I think that's wrong. Hayes has been very open about his thought-process: he wants to whatever will give him the best chance of having a long NBA career. If that means coming to back to college for another year, that's what he's going to do. He's not going to play in the Turkish league out of spite.

It would be an easy call if he was relatively assured of being drafted in the first round. That's a guaranteed tanker full of money to play basketball, and except in rare cases going pro in that situation is a no-brainer.

It would (will?) also be an easy call if Hayes is assured that no one will draft him at all. That's a virtually guaranteed ticket an extended stint in the D-League or Europe, and Nigel has been pretty clear that's not his goal.

But the situation is this: Nigel may well get drafted in the second round. That's not ideal, but it's not necessarily a dead end, either. A few things have changed recently that make getting drafted in the second round potentially not-so-bad:

1) NBA teams are starting to realize the value of second-round picks. Players like Draymond Green are showing that there's plenty of talent still left. And teams are free to negotiate any deal they want with second-round picks, so they can be creative about structuring deals with players who are intriguing and may well develop into something. 

2) In Hayes's case in particular, his "type" is something of the flavor of the month. "Position-less basketball" is the watchword, as everyone tries to copy the magic of the Warriors. A few years ago, Hayes might have been ignored as a tweener. But now there's a chance teams may key in on this as an attribute -- particularly given his rather freakish 7'3" wingspan.

So if Hayes is given some indication that he'll be taken in the second round by a team that is willing to work with him, that is a very intriguing and tantalizing opportunity.

The flip side of this is: can he really prove anything to pro teams with one more year of college basketball? Of course, if he come back and shoots 45% from three, he will raise his stock considerably. But how likely is that? And how much opportunity will he have in the strictures of the Wisconsin offense to show off the shooting guard skills that NBA teams would want to see out him? Unless he has a great year next year, or at least a great tourney run, the second round may well be his destiny no matter what. In that case, why not get started now?

Ultimately, I think Hayes probably will be back, because I don't think he's going to get any assurance of being drafted. He knows he can play better than he played last year, and a good senior year should at least assure him of a spot in the draft. But it's not a slam dunk.

Thoughts on the bracket selection, part 1

I followed the "bracketology" debate more closely than usual this year, for two reasons: (1) until recently, the Badgers were a bubble team (at best), and (2) I used the power of T-Rank to produce an objective bracket prediction (T-Ranketology).

I was satisfied with T-Ranketology's results. It missed three at-larges: Syracuse, Vanderbilt, and Tulsa (instead of Saint Mary's, St. Bonventure, and South Carolina). This was about average for the brackets over at bracketmatrix.com, and if you look at the final "consensus" bracket, T-Ranketology would have had 67 of 68 (with only South Carolina not being a consensus tourney team). Seeding predictions were pretty good, too. All in all, not bad for an algorithm.

There's a lot of hootin' and hollerin' about the committee's selections, and I agree with much of it. But I wanted to take a look at the six teams T-Ranketology was wrong on, plus one other, to see maybe what the committee was thinking and if the algorithm could be improved to reflect that thinking or lack thereof.

Syracuse

Syracuse's overall resume was not great, but the one big trump card they had was a road win at Duke, which is worth like a million resume points. Add a couple other decent (early) wins, and they're left ranked No. 32 in T-Ranketology's "resume" ranking, which is an attempt to simulate the committee's fixation with "top 50" wins, etc. They were also 50th in T-Rank's "wins against bubble" rating, so right on the bubble there. But they were very poor in basic RPI, and had tanked coming down the stretch, leading to a bad elo ranking (which usually pretty well approximates current "sentiments" about how good a team is). All in all, this left Syracuse the sixth team out in T-Ranketology.

But I'm not going to worry about fiddling with T-Ranketology to get Syracuse into the field, because they were clearly a special case.

@bkbtNUmbers It certainly should be. But I interpret committee chairman's remarks re Boeheim as "they're in."

— Bart Torvik (@totally_t_bomb) March 9, 2016

The committee chairman had been saying for weeks that Syracuse was going to get special consideration because Syracuse played like shit when Jim Boeheim was serving his 9-game suspension in the middle of the season. Basketball people can look at that argument and see the absurdity on its face -- Syracuse lost five games without Boeheim, and even if you think he is super-god-coach, they almost certainly lose 4 if not all 5 of those games with him. But the committee is not composed of basketball people, so alas. In any event, the handwriting had been on the wall: barring a monumental collapse (which almost happened) Syracuse was going to be in the tournament. If I had been manually fiddling with the T-Ranketolgy bracket, I'd have put Syracuse in for sure.

Vanderbilt

Vanderbilt was the eighth team out in the final T-Ranketology, mainly because it was not in the top 50 of any of the four resume-based metrics the algorithm considered. On the other hand, unlike Syracuse, it was not terrible in any of those metrics, finishing top-70 in all of them.

Clearly Vanderbilt got in because of its efficiency rating. Vandy finished the season ranked 27th in the Kenpom ratings, and top-30 teams always get in nowadays. I think this is why they're slotted in the play-in round against another Kenpom darling, Wichita St.: the committee put two good teams with bad resumes into the ring against each other and said, "If you're so good, prove it."

When I first started T-Ranketology it was loosely modeled after the Easy Bubble Solver, which just averages RPI and Kenpom ranking. Of course, I used T-Rank instead of Kenpom rating, but it was pretty much the same idea. Eventually I took out the efficiency rating component because for good or bad I think it just doesn't play a very big role in the selection or even seeding process, at least not systematically. But I think there's good evidence that it comes into play in edge cases, and I think it's pretty clear that's what got Vandy in. I may have to work in some kind of "top 30" efficiency rating bonus to account for this.

(By the way, I think Syracuse was also helped by a decent Kenpom rating, though I don't think it wouldn't have been enough without The Boeheim Excuse.)

Tulsa

Tulsa was the real shocker, what John Gasaway calls the committee's annual "grenade." But it wasn't a huge shocker to T-Ranketology, which had Tulsa just the fifth team out -- ahead of both Syracuse and Vanderbilt! Indeed, before its loss to Memphis in the AAC tourney on Friday, T-Ranketology had Tulsa the last team in the field.

Why? Like Syracuse, Tulsa scored well in the "resume" score that approximates top 50 wins, etc. This is by far the stupidest possible measure you could come up with, but I'm pleased to say that I think I've done a pretty good job of modeling this particular madness. Tulsa's inclusion in the field of 68 shows that I probably need to weigh it even a little more.

But I think there's another lesson for Tulsa's selection. The committee first gets together early in championship week to get ahead start on the process. As a result, by Friday (when Tulsa got stomped by lowly Memphis) the committee has already made some provisional decisions about which teams it thinks are good enough. I'm pretty sure that Tulsa's resume had already been found deserving by Friday. Here's the way the human mind works: once it decides something, that decision sets. It's like a boulder in a divot; you need a big shove to get it moving again. When new information comes in, we don't start at square one and reevaluate the decision with a blank slate. We say: is this new information enough of a big deal to make me go through this whole process of deciding again? Unsurprisingly, the answer is usually no. This fundamental quality of human psychology (call it laziness if you wish) got Tulsa into the tourney.

(This, by the way, is why college-football-playoff-style in-season tourney rankings are a terrible, terrible idea.)

Well, this has gotten tl;dr so I'm going to stop now. I'll try to post later today with my profound insights into the "snubs."

Is Kenpom biased in favor of significantly lower-ranked teams? (Yes.)

***
NOTE: Kenpom changed his rating system significantly for the 2017 season (after I did this study) so the results don't necessarily apply to his current system—indeed, there's reason to think the changes he made alleviate the issues discussed below.
***


One of the big problems in college basketball—particularly with regards to NCAA tourney selection—is giving proper weight to road games. It is difficult to intuitively grasp how much harder it is to win on the road against a lesser team than it is to win at home against a better team.

This question came to a head when Greg Shaheen was asked about Wichita State’s big home win over Utah, and specifically what he thought an equivalent road win would be. He answered somewhat absurdly: “Utah.”

Seth Burn set out to answer the question using Kenpom numbers, and what he found was that Wichita State playing No. 25 ranked Utah at home is equivalent to them playing No. 109 rated New Mexico on the road. What this means is that the Kenpom system gives them the same chance (about 73%) of winning in each game.

This is kind of shocking, and my own investigation confirms that it is a correct statement about the Kenpom system. But that doesn’t mean it is necessarily a true fact about the universe. Because Kenpom could be wrong about these things. Importantly, it could be biased in favor of lower-rated home teams.

Indeed, it has been my anecdotal observation that this in fact the case: Kenpom seems to have a systematic bias in favor of significantly lower rated teams when they play higher rated teams, particularly at home. So I set out to test this hypothesis.

First, let’s look at all games that Kenpom would predict the home team to have a margin of victory of +/- one point (favored by 1 or a 1-point underdog). By definition, these will be games where the home team is lower rated than the road team, because home-court advantage is built in. Here are the results:

Games where projected MOV is +/- 1 (Kenpom)

Total games: 372

Home team avg expected MOV: 0.01

Home team actual MOV: -1.81

Home team expected win %: .500

Home team actual win %: .438

What we see in these 372 games that Kenpom would expect to be pretty much pick ‘ems is that the better team (the road team) actually won 56.2% of the time, and had an average margin of victory of +1.8 expectations.

Now, this could just be a quirk of this season—maybe the home teams are just underperforming in close games. But when I run the same test using the T-Rank algorithm, the bias pretty much disappears:

Games where projected MOV is +/- 1 (T-Rank)

Total games: 345

Home team avg expected MOV: 0.06

Home team actual MOV: -0.21

Home team expected win %: .502

Home team actual win %: ..487

This still shows a slight bias toward the (better) road team, but it is much less, and looks much more like random variance.

Next I wanted to test my impression that Kenpom particularly breaks down when the spread between the teams is larger (e.g., games like the nearly 100-spot spread between Wichita St. and New Mexico St.). So I looked at games where the home team was rated more than 50 spots lower than the road team. Using Kenpom projections, here are the results:

Games where home team is more than 50 spots lower than road team (Kenpom)

Total games: 1227

Home team avg expected MOV: -4.34

Home team actual MOV: -6.65

Home team expected win %: .345

Home team actual win %: .271

In this rather large set of games, the home team now actually performs 2.3 points worse, on average, than Kenpom’s system would project, and wins only 80% as often as projected. Compare this to the same experiment with T-Rank:

Games where home team is more than 50 spots lower than road team (T-Rank)

Total games: 1150

Home team avg expected MOV: -6.05

Home team actual MOV: -6.80

Home team expected win %: .311

Home team actual win %: .272

Again, we still see a slight bias in favor of the home team, but a much lower one than with the Kenpom system.

Overall, Kenpom has a very good record of prediction and projection, so if there is a systematic bias in these mismatches, we would expect it to be counterbalanced by good results between more evenly matched teams. And that is in fact the case:

Games where home team and road teams ranked within 50 spots of each other (Kenpom)

Total games: 1804

Home team avg expected MOV: 4.1

Home team actual MOV: 3.58

Home team expected win %: .645

Home team actual win %: .652

(For the record, T-Rank performs similarly in these games, but not quite as good.)

In this set of games, the Kenpom algorithm is extremely well calibrated. My speculation is that the shift from Kenpom 1.0 to Kenpom 2.0 made the algorithm more accurate in these (more common and more important) games, at the expense of some loss of calibration in more mismatched games. This seems worth it, and you can see why it would improve the overall performance of the system.

But I think it’s important to consider this evidence that Kenpom’s projections are systematically based in favor of significantly lower ranked teams when doing this calculation about home/road equivalencies, because the results using Kenpom are not only unintuitive, but in all likelihood just plain wrong.

For example, using T-Rank the equivalent road game to Utah at home for Wichita State is a hypothetical team between No. 83 Temple and No. 84 Hawaii. Utah is ranked 25th in both systems, so this is a great comparison: Kenpom says the road equivalent is No. 109 New Mexico St., and T-Rank says it’s No. 83 Temple or No. 84 Hawaii. Since T-Rank gets better results in these kinds of games, and its results are more in line with most of our intuitions, I’m sticking with T-Rank.

***As to why these difference between T-Rank and Kenpom exist, I believe it has to do with the different "spread" the systems create, and the different "exponents" we use to calculate the Pythagorean Expectation (Kenpom uses 11.5, T-Rank uses 10.25). The different spread is caused mainly by the fact that Kenpom much more aggressively caps margin of victory and the effect of blowouts in mismatches than T-Rank does. My hypothesis is that by mostly ignoring those mismatched games, his system ends up being less accurate in mismatched games, but the upside is that it may be more accurate in games between teams of similar quality.