Sunday, December 10, 2017

Time to quit the switching?

As you 2 regular readers of this blog know, I have had a long running interest on the changing way the Badgers have defended ball screens over the years. As anyone who watched yesterday's Marquette game can see (or really any game this year), the defense sucks. Much of that has to do with playing a bunch of young players who are not great individual defenders, and lack the awareness needed for good help defense. For the past 20 years the Badgers have had a core of experienced upperclassmen virtually every year that were well schooled in the team's defensive principles. That is not the case this year, and it shows.

UW has played nothing but man to man defense over that time except for a very brief flirt with the 2-3 zone under Gard which was a disaster. There have been changes within the man to man, from going over the screen and hedging, to switching all screens, to going over and sinking. Currently, I'm not exactly sure what the system is, and that is a big part of the problem. Here are a series of clips from the Marquette game showing different ways they play the ball screen.

This is classic switching. Davison runs into the screener and stays with him after the dribble hand off, and Ford goes with the ball. Then there is another dribble hand off, and Ford stays on ball while Iverson switches with the guard going to the corner. Ford then hands off the ball carrier to Davison and stays with the big that floats off to the left side of the floor. At this point Happ's man comes up from the post to set another screen, and Davison hands off the ball carrier off to Happ. Happ does not come out to take him on the switch, and he gets a wide open 3.

In this clip Davison runs into the screener, Happ switches to the guard, and Happ shows this time to take away the jumper. The guard takes a dribble to create space, and Happ steps back, then comes out again to challenge but it's a shot fake. The problem is that Davison does not switch, he goes over the screen and comes over to the guard, instead of staying with the screener. The guard passes to an open man for a dunk (notice the other 3 defenders are all standing 18 feet from the hoop where they can't help).

Here there is no switching on the ball or off. There is a bunch of off ball screening action, a dribble handoff, and finally a ball screen, but everyone stays home with their man. On the final screen, Iverson shows on the ball carrier, before retreating to his man, and Davison "fights" over the screen to get back to his man.

Here Schlundt fights over the screen, and Charlie sinks to take away the lane instead of showing on the ball carrier to take away the jumper (I actually think Charlie has no idea where he is or what he is doing, but let's just say he was sinking on this one).

Finally, one last switch clip. On this one, both Happ and Davison leave the ball carrier, and go with the screener. Notice after the guard gets the wide open 3, Happ and Davison are fighting over who was responsible for what.

As I am known to say on occasion at Badger games, "What the hell are they doing"? Some of this is on the players as they are obviously getting torched routinely. More has to go on the coaches. They are playing a bunch of young players who are still learning how to play defense, and I think they are overloading them with too much responsibility. They should get rid of the switching. Switching requires a lot of communication, and a lot of feel for when to switch, when to switch back, and none of the young players are good enough for this.

When Bo started at UW, the defensive rules were simple. The on ball defender goes over the screen and stays on ball. The screening defender hedges every time and recovers to his man afterwards . All 3 other guys sink in when that happens to take away the lane. Everyone has a job, and everyone knew what the other's job was. If you did not do your job then you go to the bench.

Simplicity is a great thing. The Badgers need more of it on defense.

Thursday, November 30, 2017

FPI is annoying

Before I get into this post, I want to make clear that I don't have any animus toward Espn or their analytics people. I like them! I've defended them! (Though they've gone backwards a bit since I wrote that "In defense of BPI, etc." post.)

With that throat-clearing out of the way...

Espn has a predictive metric for college football called FPI. It is relatively good* at predicting the results of college football games. So if you want to lose a little (instead of a lot) of money, use FPI to pick games against the spread. Or you could just toss a coin and do slightly better.

For the most part, the analytics people at Espn are admirably clear that FPI is a predictive tool. But lately they've been doing two things with FPI that annoy me: First, they've been touting it as an accurate and objective arbiter of team quality. Second, they've been openly clamoring for an FPI-based metric—Strength of Record—to be used in selecting the teams for the college football playoffs.

Here's why I'm annoyed.

FPI is not an accurate measure of team quality.

I said above that FPI is relatively good at predicting the results of games. I say relatively good because college football is a crazy sport where crazy things happen on the regular. People say "Vegas knows, man" but Vegas don't know much about college football: the mean absolute error for closing betting lines in college football is about 12.2 points (and FPI is at 12.4). In the NFL, the mean error is 10.5 points—significantly better.

Why is this? It's because there is just not enough good data in a college football season to produce a highly accurate measure of team quality. Each team plays just 12 games, and only 8-10 of those are games that we can extract much useful information. (The other 2-4 games are mismatches that are likely to be all but useless for discerning differences among quality teams.)

So this is not a knock on FPI in particular. There simply does not exist a highly accurate measure of team quality in college football. What annoys me is that Espn pretends that there does, and that it is FPI.

We can see this hubris in an article today where they purport to show that the playoff selection committee is not selecting the "best" teams because it is not selecting the teams rated highest in the FPI and is considering teams rated poorly by the FPI (poster boy: Wisconsin). In other words, FPI is the arbiter of "best." Bullshit! If the question is: "Who are the best teams?" the only intellectually honest answer is:

"We don't know."

FPI-based "Strength of Record" should not and cannot be used in playoff selection 

As I mentioned above, there is not enough good data in a single college football season to construct an accurate enough measure of team quality to reliably discern between the best teams. To help make up for this, Espn incorporates its preseason prior — which is based on things like historical performance and recruiting ranks — into the FPI all year long. It never goes away. And while they refuse to say how much it still, at this point, influences the ratings, it is pretty clear that is still doing a lot of work. There is no other explanation for how Florida State (preseason No. 3, but 5-6 with bad losses) is still ranked 21st.

There is nothing wrong with keeping the preseason prior part of the formula. Espn's guys say that using the prior makes the predictions more accurate, and that's what the FPI is supposed to be maximizing. Fine!

But keeping the preseason prior means that FPI cannot be used in any way for selection to the playoffs. No one would argue that selection should be based on recruiting ranks or last year's performance. But if you rely on a strength of record measure based on FPI, that's what you'd be doing. You're giving Alabama extra credit for beating a bad Florida State team because FSU has five-star recruits and used to be good. Completely unacceptable.

Who benefits?

Obviously, a system that maintains a significant prior based on program strength and recruiting ranks will boost teams like Ohio State and Alabama. It makes sense if you are trying to predict games to give those teams a boost, because even in the middle of a down season they probably still have a lot of good football players could put it together at any time.

And obviously it hurts Wisconsin, which has not ever had a recruiting class better than 30th in the country. Which is why it is particularly annoying to see Espn touting Wisconsin's low FPI as a reason that it can't truly be considered among the best teams. It's crazy-making.

Saturday, November 18, 2017

WI is better than MI

Quick revisit of one of my favorite Blog posts of all time.

With the win today. UW clinches another year in which MI will not win more games than the Badgers. The last time MI won more games was in 2003.

2003 was a long time ago. For some reference I'm sure one MI fan will appreciate:

In 2003 the show "Friends" was still on the air with new episodes.

Friday, November 17, 2017


6-10 after splitting the double bet last week. I'm doubling down again.
UW is a 7 point favorite, and the over under is 41.

I'm taking UW to cover, and the under.

UW wins. 23-14.

Friday, November 10, 2017

On board with Van Vliet, but....

OK, that was a decent game for Van Vliet. I'm on board with him in this rotation, but there are concerns. Hard to argue with the line. 18 points on 7-11 FG, 4-5 3FG, 8 boards, 2 blocks and just one turnover. Any player puts up those numbers and you have to be a bit crazy not to be encouraged. I can already hear people starting to compare this with Kaminsky's break out junior year. A bit premature? Yes. Will he put up those numbers all year long? No way, but he doesn't have to to be an effective part of this rotation.

Here are the concerns. Chuckers are great when the shots are falling, but can be a cancer when they aren't. Remember those games when Vitto would jack 10 long 2 point jumpers and only hit 2or 3 of them. Van Vliet won't hit 80% of his 3s in many, if any more games this year. The concern is as much the types of shots, as the volume. At least 3 of the 3 pointers were attempted very early in the shot clock, (I was at the game so I'll have to check the tape, could be more) and came from a pass from the top of the key instead of from a post feed. He needs to let the offense roll a bit and they can get a better shot.

He also had 3 fouls in 22 minutes against competition that was not imposing on the inside. SCS hardly even tried to get it inside in the first half, as they shot jumper after jumper. Badgers only had 9 team fouls all night, he had a third of them. Defense is still not his thing. Finally, with about 6 minutes left in the 2nd half, Van Vliet looked like he was about to fall over. He was subbed out with 5 to go, and to be fair he had played a stretch of about 7 straight minutes. However he only played 9 total minutes in the 2nd half, and 22 overall. Conditioning is not his thing yet either.

Maybe that last part is OK. If he only gets 20 minutes a game, that may be for the best. Gard can roll with him when he's hot, and bench him when he's not. Having a guy with no conscious isn't always bad. When Vitto was hitting shots it totally changed the team. Van Vliet is certainly a better shooter than Vitto, so he should hit more often.

So, I'm much more encouraged about Van Vliet than I was before, but not as encouraged as all the people I will talk to tomorrow at the bar, who will probably be calling him the 2nd coming of Kaminsky already.

Thursday, November 9, 2017

UW Iowa

4-8 after another 0-2 week. Haven't got a single win since that meaningless FG Torvik likes to make fun of me for. Badgers are a 12.5 point favorite, and o/u is 46.

In honor of Torvik, I am changing up the rules. When everything is going wrong and you can't buy a win, what do you do? Double the bets! All picks count double from now on.

I'm taking Iowa and the points and the over this week.

Is Illikainen out?

I saw today Reuvers is still considering taking a redshirt year. After watching him in the exhibition I can see why. He needs body development and practice in the system, but I would like to see him play this year. We'll see what happens, but it got me to thinking about Illikainen.

Reuvers is behind Happ, Thomas, and Van Vliet at this point, and maybe Ford too. It's not clear that he is behind Illikainen. Illikainen did not show anything special in the video I saw of the Australia trip. I didn't hear anything about him against Missouri, and while I didn't see the N Iowa game, his line was telling. In a game the Badgers dominated, he was 1-2 for 3 points and had  2 rebounds in 8 minutes, with 3 fouls and 3 turnovers. He wasn't any better against UW-Stout with 0 points, 2 rebounds, 1 foul and 2 turnovers in 6 minutes.

Last year I floated the idea that a sophomore Badger big man should redshirt. That didn't happen, and now it looks more likely that Illikainen would transfer than redshirt as a junior. Thomas seems destined to be the physical presence we need when Happ is on the bench. Van Vliet may be a chucker, but at least he has some confidence, unlike Illikainen who looks scared every time he is on the floor. Not many minutes left for the remaining 3 guys, and at this point Ford looks to be the first guy up to get a crack at those minutes.

It's really too bad. Maybe he turns it around and gets in the rotation, but it doesn't look good. In his first 10 games as true freshman he showed tons of promise. Then his confidence went somewhere and it has yet to return. I know they haven't even played a real game yet, so there is plenty of time to turn things around, and an injury could open an opportunity at any time. Here's hoping he does better tomorrow night,  but if he continues to sit I'd be surprised if he wasn't gone by season's end.

Wednesday, November 8, 2017

Likelier Things

There's been a lot of focus lately on a scenario—let's call it the Doomsday Scenario—that could arguably keep a 13-0 Wisconsin out of the college football playoffs. I have a few things to say about this.

To start, a 13-0 Wisconsin team is making the playoffs. "But what if the Doomsday Scenario occurs? What are the chances that the Badgers would miss the playoffs then?" The chances are zero. ZERO. It's not happening. "How can you be so sure?" Because I have a functioning brain. If you disagree with me about this, I'm sorry: we can't be friends anymore. Not even on Facebook.

Even if I am wrong about this—and I am not wrong about this—it's super unlikely that I'll be proven wrong. This is because the chances of the Doomsday Scenario even materializing are still extremely small. For the Doomsday Scenario to occur, each of the following must occur:

1) The Badgers must win out. Let's be chipper and put the odds of that at 1 in 3. Here, already at step one, we have a Likelier Thing that submarines the Doomsday Scenario. But we still have hope. 

2) Either Alabama or Georgia must win out, and the other must finish with just one loss (to the other, preferably by a slim margin). I'll be generous and say Georgia has a 40% chance of winning its final three games, and Alabama has a 75% of winning its final three games. That makes this another 1 in 3  shot, and one of them losing not to the other is another Likelier Thing that pierces the Doomsday Scenario bubble.

3) Either Oklahoma or TCU wins out. FiveThirtyEight says Oklahoma has a 33% chance to win out and TCU has a 17% chance to win out. That's a total chance of one of them winning out of around 45%. This may be off given that they play each other at least once, but close enough for these purposes. Another Likelier Thing that defeats the Doomsday Monster.

4) Finally, the most likely iteration of Doomsday Scenario involves both Notre Dame and Clemson winning out. Being generous again, let's say both of those are 50/50 chances, meaning the chance of them both happening is 1 in 4. Yet another Likelier Thing kneecapping Dr. Doomsday.

So, the odds of the Doomsday Scenario emerging in the face of all these Likelier Things is .33 * .30 * .45 * .25 = 1% — and that's being generous.

5) Now, if you plug the Doomsday Scenario into the FiveThirtyEight playoff calculator—which has not been informed that a 13-0 Wisconsin team is actually a 100% lock to make the playoffs—it says that the Badgers currently have an 83% chance of making the playoffs even in this Doomsday Scenario. In fact, they're actually the third-most likely team to make the playoffs in this scenario, meaning that they'd still likely be the 3-seed ahead of either Oklahoma or Notre Dame. 

Bottom line: even if we pretend we don't know that the Badgers would be a 100% lock to make the playoffs at 13-0, there's about a one-sixth of one-percent chance the Doomsday Scenario ensnares them. So let's talk about something else. 

How about college basketball?

Friday, November 3, 2017

UW Indiana

Drop to 4-6 after another 0-2 week. UW is a 13.5 point favorite this week and o/u is 48.5.

This sure seems like a trap game. UW has Iowa, MI, and at Minn before a date at the Big Ten Championship game. Indiana is an improved team, and Bucky is on the road.

I'm taking Indiana and the points, and the under.

Friday, October 27, 2017

UW vs. IL

4-4 after last weeks meaningless FG with less than a minute to play covered the spread and the over. The lesson again, if you don't have a good feeling, don't bet. Bucky is a 26.5 point favorite and the o/u is 50.

Not much time this week, and Illinois sucks. I'm taking Bucky and giving the points, and taking the over.

Saturday, October 21, 2017

T-Rank: New Stuff for 2017-18 ICYMI MEGAPOST

I've added a bunch of stuff to the T-Rank site this offseason (or at least since the start of last season) and thought it might be a good idea to inventory & explain it somewhere. Somewhere like here.

First, a little back-patting. Three different aspects of the T-Rank site were validated as pretty useful last year: the ratings system itself, the "T-Ranketology" tourney predicting algorithm, and the preseason projections.

The rating system performed well. In terms of predicting games, it was the best full-season predictor, at least according to this analysis. At the very least, T-Rank is in the same league with Kenpom (no surprise, since I copied Kenpom liberally) and Sagarin. This means the adjusted efficiencies that drive the ratings are likely sound as well, and all the fun stuff that I use those adjusted efficiencies to power has at least some relation to reality.

The T-Ranketology algorithm did a great job last year, finishing near the very top of the Bracket Matrix competition. Of course, this was probably lucky, and last year was a bit of a strange year in that most people were able to correctly pick the field. But again, the main takeaway is that T-Ranketology is "good enough" to use for other fun stuff, such as the new Teamcast and Tourneycast features, and feel confident that the results are at least worth taking seriously.

Finally, last year's preseason projections turned out the be the best 1 to 351 projections, at least according to Dan Hanner's analysis. This is somewhat of a bittersweet victory because—as I've explained in an update to this old post—I have actually totally revamped the preseason projections for this year. But I'm confident that the new system is even better, and I'm also quite certain that last year's "victory" was mostly luck. Still, coming out ahead of Hanner and Kenpom by any metric at least shows that the ideas behind the system aren't garbage.

So putting these three facts together, I think it's safe to say that T-Rank's underlying algorithms and ideas are reasonably sound, which makes the tools on the site even more fun to play around with. Speaking of those tools:


This is probably the coolest thing I've added: a tool to play around a team's schedule (picking wins and losses, adding dropping games) to see how it affects their tourney chances and seed, based on the T-Ranketology algorithm.

The last two columns there show how much of an effect a win or loss would have on a team's T-Ranketology score (in isolation from all other games). Teamcast is also retroactive back to 2008, so you can go back and look what would might have happened if a certain game had come out differently.

I'm excited for Teamcast this year to play out various bubble scenarios—especially given the likelihood that the Badgers will be on the bubble.


Daycast is similar to Teamcast, except that instead of playing around with a team's schedule, you play around with the games on a given day to see how it affects the tourney. As part of this, I've developed a new thrill quotient, the "Torvik Tourney Thrill Quotient" or "T3Q" which ranks games in their anticipated effect on the tourney. Basically, games between potential bubble teams reign supreme.


For TourneyCast, I run 10,000 simulations of the season (including simulations of every conference tournament), run the results of each sim through the T-Ranketology algorithm to get a projected field of 68, and then simulate the NCAA tournament. The output is odds for every team to get to the tournament (whether through an autobid or at-large) and then odds for advancing to various stages of the tourney.

ADDED: one cool feature of the TourneyCast is that if you filter by conference you get the projected number of bids, at-large chances (interesting for mid-majors), final four chances, and championship chances.

Backfill to 2008

Not sure exactly when I did this, but the site is completely backfilled with team and player stats all the way back to 2008. This includes advanced stats boxscores, which certain other sites don't have back past 2011.

The only exception to this is play by play based stats (win probability, game score). I have a complete set of PBP for last year (2017) and 95% coverage for 2015 and 2016. I will probably add more backfill on that in the coming months, but my impression is that available PBP peters out around 2011 anyhow.

This also includes conference-only advanced stats, and all the other various ways I've got to split the player stats, back to 2008. Notable other sites have conference-only advanced stats back to just the 2014 season.

More Player Stats Splits and Filters

As I just mentioned, I've added new ways to split player stats in the pretty awesome Player Finder tool. Now you can filter out the stats so you look at performance against only top 50 (adjusted for venue) opponents. You can even filter by date, to see who the stars of November were. I've also added a "max height" filter so you can see who the best short rebounder is, for example.

Player Histories and Game Logs

Part of the backfill is that I have advanced player stats back to 2008, including game logs. In addition, one of my major projects this summer was to create a linked database of player histories, so that when you click on a player's name, all his seasons come up. You cannot imagine what a supreme pain in the ass this was. The things I had to learn, I shit you not, were things like natural language processing. Woo boy. But at this point the player histories are about 99% linked. If you see any any discrepancies, please let me know.

Charts and graphs! Charts and graphs!

I just learned how to make some awesome interactive charts and graphs, replacing the old jpeg-based graphs it took me a week to learn how to make. Pretty proud of myself. This new skill is on display in three areas:

Win probability charts

I blogged about my fun foray into created a win probability model here. I've now learned how to make the result more useful and interactive.



Also: Win probability calculator.

Team Trends Charts

Previously, I had team trends charts for just offensive and defensive efficiency, and they were pictures like the old win prob chart. Now I've got em for most team stats, and they are interactive and fabulous. Note: these charts are also available at the bottom of the "Team Results" page.

Player Stats Trends

Not to be done, the player stats department demanded access to the charts and graphs technology.

Strength of Schedule Stats & Page

Every team page has strength of schedule stats, and there's also a comprehensive page for strength of schedule. These are broken down by overall SOS and non-conference SOS, and also broken down by the SOS so far, and projected SOS for the entire season. (Conference SOS calculations are on the conference pages.)

Might as well say a word about my SOS metrics, since they're a bit unusual. The "basic" metric is just the average of the team's opponents' pythagorean expectancy (adjusted for the location of the game).

The "elite" metric is different, and better. This is the percentage of games an "elite" team (approx .9000 Barthag) would be expected lose against a given schedule. This is better because it reflects how little difference there is between playing mediocre and bad teams at home, and really rewards playing games that a good team could realistically lose.

To see what this is better, imagine three potential opponents: one good team (Barthag of .9000), one mediocre team (.5000), and one terrible team (.1000). Under the basic method, playing two mediocre teams is the same as playing a good team and terrible team because (.5 + .5) / 2 = (.9 + .1) / 2. But this really isn't right for most teams that we care about, because an elite team's chances of losing to the mediocre team (at home, at least) aren't really that different than its chances of losing to the terrible team, while its chances of beating the elite team are quite a bit different: (.05 + .01) / 2 < (.50 + .01) / 2.

Coach History and Team History pages.

A concise way to look at team and coach performance back to 2008.

Advanced Analysis of Unbalanced Conf. Schedules

I blogged about the underlying analysis here: I run simulations to see how differently teams would perform against a true round robin schedule (both winning percentage and chance of winning the conference) and log the results. 

RPI Forecast

Here's one I forgot about: a page showing the projected RPIs of every team based on their current T-Rank rating. This page also shows projected records in each of the selection committees newly delineated "quality win" buckets. If you hover over those records, you can see which teams are in each bucket:

Wednesday, October 18, 2017

UW vs. Maryland

4-2 on the season after last weeks split. UW is a 24 point favorite and the o/u is 50.5. Don't have a strong feeling on this game, which means I shouldn't bet it, but since I'm not betting I'll still pick.

Maryland is bad. They can't score with their 3rd string QB against a quality defense. Bucky has the 5th best scoring D in the country and has given up more than 17 points only to NW. Don't see this Maryland team going higher than 17.

Bucky's offense has played better than they have scored. Even in the 17 point debacle last week they had almost 500 yards and 300 on the ground. All the injuries worry me though. If this team gets healthy the offense could be special, but they may not get healthy until the bowl season break.

24 is a lot of points. Vegas really has no respect for Maryland after consecutive blow outs against OSU and NW. I don't like my choices in this one, but I'll take Maryland and the 24 points, and the under.

Friday, October 13, 2017

How much longer until the season starts?

So, I’m getting pretty antsy waiting for the Badger Basketball season to start. Getting a taste by watching the Australia/New Zeeland footage was nice, but I am ready for the real thing. In an effort to assuage the anxiety of waiting, I am going to put up some ideas/hopes for the season, and keep telling myself that it’s just a few more weeks.

Unsurprisingly, I am more bullish on this season than most people seem to be. With so many players leaving from last year’s team that may seem foolish, and I won’t argue to much with that. At this point any projections are long shots with so many unknowns. This is more about what I am hoping the Badgers will become, as much as it is what I think they will become. In any case, here goes.

I like the guards. This is going to be a fun bunch of players to watch. All 4 seem to have a good all around skill set with some ability to shoot, handle the ball, and drive. They all obviously have strengths and weaknesses, but I see this group as less of the "one skill" kind of guards UW has had a lot of in years past. Think of Jason Bohannon who shot great, but did nothing else on offense and was limited athletically on defense. Think of Jason Chappell who provided a big body and rebounded, but nothing else. This group seems to be better all around players.

The guards will all play, not because they have to because of the numbers, but because they deserve to play. UW recruiting since Bo Ryan took over has been big man heavy, usually having only 4 scholarship guards at a time (out of 13 scholarships). That way more scholarships could be used for big guys that are more hit or miss in terms of recruiting, or take a couple years to develop. That sometimes means you have to play young guards, and that’s all we got this year. Luckily guards are better equipped to play right away, and with a healthy Pritzl, and 2 physically mature players in King and Davison, this group should not hold Bucky back.

I kind of wish Jordan Hill hadn’t transferred. As anyone who went to a game with me the past 4 years knows, I was no fan of Jordan Hill. Call me crazy, but I don’t like point guards that can’t dribble and take bad shots. Nevertheless, with 4 young guards it is almost inevitable that this group struggles on the defensive end of the court. While he had his faults, Hill was an effort defender, and you could get by with him on the court for a spell. Sometimes when you have young players, it’s nice to have that effort defender you can put on the court, and let them watch from the pine while a less talented player gets their minutes because he is doing the right things on defense. 

I expect Iverson to play a lot this year. His quickness and defensive versatility is going to let him take over Showalter’s role last year taking on the best perimeter player, but with his size he can guard a bit bigger players too. In my many fantasies about the Badgers lineups this summer, (yes, I know that is kind of weird) I have had Iverson playing everything from 2 guard to 4. While he fits this team as a 3, depending on what other players step up, I could see him playing a lot at any of three positions to accommodate other talent, because he is so versatile defensively. I sure hope he gets better at shooting and dribbling. If he can improve those 2 skills, he can be a star. I think Iverson eats up almost all the minutes at the 3 position this year, and Bucky ends up playing 3 guard lineups the rest of the time, but Moesch, Ford, and even Illikainen may get some backup minutes there too.

Then there’s Happ and the rest. Happ is poised to break all kinds of Badger records including some I teased last year. I have no doubt Happ will be great fun to watch as he was the last 2 years, but seems likely he will struggle statistically this year. With no Koenig and Hayes around, it’s all Happ. He will get doubled and tripled mercilessly this year. Kaminski had that happen to him too, and he went through a stretch where he struggled while figuring out how to pass out of/dribble out of/split doubles. I expect Happ will have similar growing pains, and while it will ultimately make him better, stats will suffer.

I have no idea what to make of the rest. I don’t want to take too much from the trip down under as that was a different kind of game, with different rules, and the coaches had different goals in mind with regard to playing time. That said, what I saw from the 3 other Juniors was not encouraging. Van Vliet scored well, but only because he is a chucker. To me he looked like a taller, thinner version of Vitto, minus the quality post defense and rebounding. Illikainen still shows effort on defense, but nothing but promise on offense. For some reason he just seems to have no confidence or aggression on offense. If he doesn’t find it, he won’t be any better than last year. Thomas is sort of the same. He has yet to realize his body is a freight train on the offensive side of the court. He had games last year where he showed he can dominate the defensive boards with his body, and I hope that grows. Bucky will need his bulk at some point to man up against bigger, more physical teams. My hope is that one of those 3 steps up. Just one guy please! I don’t really care which one. The other 2 guys can then battle with Reuvers and Ford for backup minutes.

There you have it. 4 guards, Iverson, Happ, and someone else makes a nice, tight 7 man rotation, with 4 other big guys that compete with each other to provide some depth. 25 wins and a sweet sixteen later, and I have had a lot of fun.

God, I can’t wait for the season to start. Maybe I need another fantasy.

What if Iverson starts at the 2 guard, and then...........

Wednesday, October 11, 2017

UW vs. Purdue

Moved to 3-1 after last weeks 2-0 performance against Nebraska. UW is a 17 point favorite against Purdue and the over/under is 51.

Much of the talk leading up to this game seems to be about how improved Purdue has been under first year coach Brohm, especially on the defensive side of the ball. No one is predicting Purdue to win a B1G championship, or even this game, but there is a lot of praise for Brohm. Purdue has been so bad since Joe Tiller retired that pretty much anything looks good at this point. Purdue has 3 wins already, but much of the improvement talk is based on the 2 losses against ranked MI and Louisville. Purdue held a halftime lead against MI, and a 4th quarter lead before losing to Louisville. Competitive games vs. ranked opponents have been a rarity for Purdue fans lately. After UW, Purdue's schedule is easy, so it is possible they get to 6 wins and a bowl game which would be a remarkable turnaround. Also possible they don't win another game this year, and look like the Purdue of recent years.

Purdue's defense is not the atrocious unit it has been recently, but it is still not good. Against Jackson's one man show at Louisville they gave up 35 points. Jackson is such a unique player I find it hard to judge them much on that game. MI is equally vexing, as Speights got hurt early in that game leading to what looks to be the O'Korn show for the rest of the year. MI was held to 28, but MI's offense hardly seems imposing this year, especially after last weeks disastrous game with the O'Korn lead offense. Minnesota rushed for 227 yards, but scored only 17 points as they don't know how to throw the ball. I'm not saying Purdue's defensive improvement is not for real, I'm just not convinced yet. My guess is that Purdue stacks the line of scrimmage early and has some success stopping the run, but UW will not stop coming at them. UW also probably hits some big plays over the top that their offense has been missing so far this year, and then runs over Purdue in the 2nd half just like they did against Nebraska.

Purdue's offense on the other hand looks more familiar. Little to no running game. Lots of short passes to the boundary and very few over the top throws. With no deep threat Purdue should get eaten up by UW's defense. The only comparable defensive unit they have faced was MI, and MI held them to 10 points, 189 total yards and 0-12 on 3rd downs. This leads to a lot of time on the field for the defense, which will wear down just as it did against MI.

So 17 points is a lot in a conference game, but UW is at home, and Purdue's only true road game was against a reeling Missouri program. I expect Purdue to crumble under the Camp Randall crowd, whether it comes early or late. I'm taking Bucky and giving the points, but I'm taking the under this week, as what could be a sloppy weather day could keep this game from getting too crazy.

Bucky 31
Purdue 6

Thursday, October 5, 2017

UW Nebraska

Last week I split, as Bucky had the spread covered before 2 late NW scores, but I got the over under. 1-1 on the season so far. This week Bucky is an 11.5 point favorite on the road, and the over under is 45.5.

Vegas doesn't like Nebraska much. I would bet that it has not been that often that Nebraska has been a double digit underdog at home in a night game in the past 30 years. Vegas also appears to be buying into the Nebraska of the past few weeks as opposed to the Nebraska of the first couple weeks.

Nebraska has been a Jekyll and Hyde act so far this year. The first 2 games was all offense as they put up 43 in a win vs. Arkansas St, and 35 in a loss @ Oregon, while the defense gave up 36 and 42 respectively. The next 3 games against NIU, Rutgers, and @Illinois, Nebraska has only scored 17, 27, and 28 against some pretty crappy teams. The defense played better those 3 games giving up only 21, 17, and 6. So which is it?

Nebraska is running a Bucky style offense this year with a pocket QB who doesn't run, and they have more rushes than passes. My guess is Vegas has the low over under because they are expecting to see 2 teams that want to run the ball and control the clock, so that means fewer possessions all around. I'm not buying. Nebraska has not seen a defense like Bucky yet, and they won't run the ball against that D. That means more throws, more clock stopping, more possessions for Bucky, and probably a pick 6 as Nebraska has also been very turnover prone.

I'm repeating last week, taking Bucky and giving the points, and taking the over.

Bucky 38
Nebraska 17

Tuesday, September 26, 2017

UW vs NW

Back by popular demand, I'm picking this week. I never like picking too early in the season until I have an idea of what type of team we are dealing with. Still a bit early, but the season is short, so here goes. UW is a 15 point favorite, and the over under is 51.

UW is scoring well this year at 43.3 ppg, despite having some struggles with injuries on offense. Haven't heard much about the offensive line, but it sounds like Shaw should be a full go in this game. The Northwestern D was destroyed by a Duke team that ran over 100 plays on them in racking up 41 points. They are down 3 corners that will not be back for this game or likely the season. I'm thinking UW scores well Saturday. If the line is healthy the 3 RBs should rack up a ton of yards.

The UW defense is not as talented as last year, but still very good. They seemed to figure out stopping Jackson last year, and let Thorson try to beat them. Even with a talented WR in Carr they couldn't get the offense going. They don't have anyone as good as Carr this year, so I think they struggle again.

So obviously I like Bucky to win, but 15 points is a lot. This is a NW team that looked to be as good or better than teams of the recent past. Those teams have beat UW 2 of the last 3 games. NW always does weird things to Bucky, so this game seems like a horrible one to start with, but here goes.

Bucky has been very good at covering spreads in recent years, even high ones in conference play, so I'm not letting the 15 points scare me off. I'm taking Bucky and giving the points. I'm also taking the over for points.

Monday, July 31, 2017

Badgers' Big Ten schedule

The Big Ten finally released its conference basketball schedule today—well, at least the pairings. Here's the Badgers' schedule, ordered by Torvik Thrill Quotient:


Based on the current preseason T-Rank projections, such as they are, it's the 4th toughest conference slate, and T-Rank projects the Badgers to go 9-9 and tie for 5th place. 

Here's a more subjective take:

Big favorite:


Slight Favorite:

at Rutgers
at Nebraska

Pick em:

at Illinois
at Penn St.

Slight Underdog:

at Iowa
at Maryland
at Northwestern

Book an L:

at MSU
at Purdue

Based on this, we've got four games in the "should win," two games in the "won't win," and 12 games that could easily go either way. Based on that, I'd say 10 wins is the target. That would likely be enough to get into the tournament, and could well extend the "top 4" streak. If I were setting an over/under, I'd probably go with 9.5.

What do you think, Chorlton?

Saturday, July 22, 2017

How I built a (crappy) basketball win probability model

The Internet is amazing. Given that I'm a philosophy major / lawyer, I really have no knowledge or skills whatsoever. But I've been able to put together the T-Rank website by just asking the Internet how to do it. Every time I run into a problem, I just ask google how to solve it. Usually this leads me to more or less step-by-step instructions on how to solve the problem, or at least gives me enough information to figure it out.

There has been one big exception to this: for a while I have wanted to see if could use play-by-play data to build a "win probability model." Not a good win probability model, just a sort of functioning win probability model. Not for any good reason, just because. But my google searches came up empty. Not only were there no step-by-step guides, there weren't even any general instructions to set me down the right path. I was lost. Harumphf.

Nevertheless, I persisted. Although I have no independent "knowledge" or "skills" I do have an epidemiologist wife who does, so one day while we were waiting in the office of a pediatric specialist (don't worry, it was a nothingburger) I ran the problem by her. I had learned just enough by then to explain the problem somewhat coherently, and she was able to set me down the right path.

Now I thought I would fill the void and put a step-by-step guide on to the Internet, mainly so future lawyers can build their own deeply flawed basketball win probability models. Also, if anybody who knows something about this stuff wants to help me improve this, just because, that would be terrific.

Step 1: Get the data.

Okay, I'm not going to walk you through this part, but obviously if you're going to use play-by-play data to make a win probability model, you need play-by-play data. Luckily, there is play-by-play data on various websites, and using google and a little pluck you can figure out how to get it. I started acquiring this data last season to calculate the "game script" average lead/deficit stat. Unfortunately, to get a complete set of data I had to use three different sources, which leads to some problems later on... (This is not just a step-by-step guide, it's also kind of a suspense novel.)

Step 2: Make the model.

Now the easy part: make your model. Done! Thanks for reading my guide.

Now you feel my pain, folks.

Step 2, actually: Figure out what kind of model you need.

This is the point when you have to figure how what you're going to do with the data. What I eventually figured out is that I was going to run use the data to run a "logistic regression." As I understand it (and really, I don't understand it), you can use this statistical method to take various variables (like score, time left, strength of teams) to predict the likelihood of another variable (win or loss, 1 to 0).

It's one thing to know that you need to a "run a logistic regression" and quite another to actually do it. As we'll see below.

Step 3: Get PBP data ("training data") into usable form.

Here's what I did: I went through (most) of the play-by-play data I have for the past two seasons, and for every second of those games I recorded the following data:

1. Seconds remaining
2. Score difference (team 2 score minus team 1 score)
3. team 2 initial expected win percentage (based on T-Rank)
4. who won (team 2 win = 1, team 2 loss = 0)

I actually recorded some more data, but this is what I ended up using for the current model.

One thing you might notice that's missing: who has the ball. This is a big flaw in my model, and I'll discuss it more below. (Suspense!)  But for the moment I'll just say that although this is a big flaw, I don't think it really makes much difference until the last two minutes.

Another thing that's missing is home court. This is another thing I left out mainly because it was kind of a pain to figure out based on the PBP data. But, also, home-court advantage is already built in to the third variable (expected win%), so there could be kind of a double-counting problem if I included it separately. I dunno, gimme a break.

Step 4: Run the logistic regression for each second

This might not be the best way, but what I did is run a logistic regression for each of the "seconds remaining" variables (2399, 2388, ... 2, 1, 0), with score difference and initial win percentage as the variables for predicting win/loss (I don't know the proper nomenclature for discussing regression, so bear with me).

Originally I ran a single regression with time remaining as another one of the variables, but the results were unsatisfactory, particularly at the margins. For example, it was obviously wrong very early in the game — I think because linearity was being imposed, but not sure. Anyhow, running it for every second worked out pretty nicely.

As I mentioned above, saying "run a logistic regression" and actually doing it are different things, so here's how I did it: I used Python, a programming language, which has a module for doing this called LogisticRegression. Here's a link to the code.

Step 5: Test it, see if it passes the smell test

The result of this model is that you can plug in "seconds remaining" (to get the right model), score (in the form of score differential), and initial win percentage expected to get an expected win probability.

For example, here's the result using Minnesota versus Middle Tennessee in last year's NCAA tourney:
For comparison, here's the Kenpom win probability graphic for that game:

Hey, not bad!

Step 6: self-loathing

Based on comparisons like the above, I'm satisfied that the model is "good enough for hobby work." But I'm also aware that the model is flawed. I took shortcuts along the way because I was just trying to see if I could get it to work. Then once I tested it and saw that it worked reasonably well, I had very little desire to perfect it. This serves no purpose and shouldn't be relied on. :(

As mentioned above, a core flaw here is that possession is not part of this model. I actually did subsequently attempt to add possession to the model, but the results were screwy. The core problem, I think, is that I'm not parsing the PBP data correctly for possession. This goes back to the fact that when I originally acquired the data I stripped out some useful info when I saved it. It's not impossible to deduce possession from what I've got, but it's not simple either. In the end, I'm not confident that my parsing was 100% accurate, and I think that led the model-with-possessions to be unstable. 

The second problem, I suspect, is that I'm not using enough data to include possession. I'm training the model with only about 10,000 games. Adding a possession variable slices the data another way which I suspect adds some craziness.

As you can see above, though, the lack of a possession variable usually doesn't matter much. It's instructive to look at the scoreless stretch starting at the 14:00 mark of the first half. In my model, that scoreless stretch is more a less a straight line, since score is really the only variable that affects things much. In the Kenpom model, there are noticeable squiggles as possession changes hands. But, the squiggles are pretty small -- looks like about two percent change in win probability. So my model is presumably cutting that in half and is "wrong" by +/- one percent for most of the game.

Of course, this will have a big effect in late game scenarios. If you're down two with ten seconds left, whether or not you have the ball makes a big difference. My model is significantly wrong in those end-game scenarios, but based on my experimentation it still gets the gist: the team down two with ten seconds left is very likely to lose whether or not it has the ball.


There you have it, googlers, that's how I built an obviously flawed basketball win probability model. May you have better ideas and more energy!

Sunday, March 12, 2017

T-Ranketology note

Well, it's Selection Sunday and the current version of the T-Ranketology algorithm has the same at-large field as the consensus (of which it is a small part) over at Bracket Matrix.

Mission accomplished.

I say this because the point of T-Ranketology isn't to try to predict the most accurate bracket on Selection Sunday. The point is to project a reasonably plausible bracket earlier in the season, so that we can see where things are reasonably likely to end up if teams keep performing like they have been. That T-Ranketology is able to basically produce the consensus field on Selection Sunday, with most teams seeded within one line of the consensus, shows that it is "good enough" to provide those useful projections earlier in the season.


Should note somewhere, so might as well be here, that I added one tweak to the algorithm on Selection Sunday: a good record bonus. One of the notable things about the bracket the algorithm was producing over the past few weeks was that it was notably down on the three PAC-12 teams. It seemed to me that this was probably a result that those teams just had really great records in their so-so conference. Whatever you want to say about the Pac-12, it's just hard not to be impressed by a team that's 29-4 or 30-4.

But I resisted adding a good record bonus—until Gonzaga fell off the one-line. I thought it was pretty clear that Gonzaga was going to get a one seed. The only drama on the one line was whether Duke or UNC would get the ACC's slot. After winning the ACC tournament, Duke did indeed sneak onto T-Ranketology's one-line—but at the expense of Gonzaga, not UNC.

So I pulled the trigger on a record bonus—really a "few losses bonus:" Teams got one point subtracted from their score for each loss under five. In other words, four-loss teams (like Arizona and UCLA) got one-point subtracted, and teams with one loss (Gonzaga) got four points subtracted. This not only got Gonzaga back on the one line, but it was also just enough to push Arizona onto the two line, which was pretty clearly where it was going to end up.

The result was that T-Ranketology was one of the few brackets to nail both the ones and the twos. I'll take it.

Wednesday, March 8, 2017

Big Ten Tourney madness

I think Chorlton is on a cruise in the Caribbean—oh, to be childless—so it looks like he'll lose this year's Big Ten Tourney Challenge by default. Nonetheless, I'm about to spend my requisite 20 seconds thinking about this and make my picks

Before we start, here are the current T-Rank odds, first assuming no home-court advantage for Maryland:

Now, if we give Maryland a one-half home-court advantage:

Play-in games:

Ohio State over Rutgers
Nebraska over Penn State

Second round:
Nebraska over Michigan St.
Northwestern over Ohio State
Iowa over Indiana
Michigan over Illinois

I'll be rooting for either Nebraska or Penn St. to beat Michigan St. so they have to sweat things out a little on Selection Sunday. Although MSU will probably win this game, I don't have a good feeling that they have a run in them, so I'm taking them out early for funsies.

I'd like to root against Northwestern as well, mainly so their fans go through the ultimate Selection Sunday Experience (one way or the other) but when I search my soul I find that I just do not have it in me.

Michigan over Purdue
Wisconsin over Iowa
Maryland over Northwestern
Minnesota over Nebraska

My earlier upset is robbing us of a third Minnesota / MSU game, which would be interesting if it happens. Michigan vs. Purdue is probably the game I most want to happen, since we just saw Michigan's spread-offense attack pick Purdue apart—will Purdue be able to adjust? Or will Michigan just not hit shots this time? In any event, Michigan seems like a bad match up for Purdue, and it's a tough draw for the 1-seed in its opening round game (Michigan is actually the third best Big Ten team in terms of adjusted efficiency, and was second-best in conference play).

Badgers would love to get Iowa again, I think, and it's not a team I see them losing to twice in short succession.

Michigan over Minnesota
Wisconsin over Maryland

Michigan over Wisconsin

My pick of Wisconsin to the final is pure homer, but I would love to see another Wisconsin-Michigan game. They've played two really tight, interesting games this year, and the Wagner - Happ battles have been great.

There you have it, that's how it's going down. Chorlton, if you're able to rouse yourself from your quarters and shake off the piƱa colada haze, put your picks in the comments.

Sunday, February 26, 2017

Good training

I found this ad weird. I guess Karl Anthony is not living in the past. He is a very successful pro. Good to know he is still working hard to try and beat badgers.

Wednesday, February 15, 2017

Anatomy of a Loss: Northwestern

About eight minutes into the Northwestern game, I was pretty sure Wisconsin was going to win. Charlie Thomas had just hit a three, and the Badgers were up 14-6. Northwestern had been garbage on offense, relying on floaters and whatnot, which were predictably missing.

The Badgers would go on to score just 8 points on their next 19 possessions, and head into halftime down 31-22 thanks to a three-point barrage from Northwestern (including one lucky bank shot). How did this happen?

The main narrative coming out of the game was that Northwestern's aggressive double-teaming of Ethan Happ shut the Badgers down. This is true in a sense, but the real truth is that the Badgers just didn't make Northwestern pay. Happ was good, really good, the rest of the first half in handling the double teams. Problem was, the rest of the team did nothing. Let's break it down.

Possession number 1: Now up 14-8, Trice tries an ill-advised drive and misses badly. Vitto Brown corrals the long rebound, however. Eventually he gets an open 3:

Possession number 2: After another McIntosh miss, Charlie Thomas passes cross-court to Koenig for a relatively open three, which he misses. Note that Thomas's pass is low, which throws Koenig out of rhythm:

Possession number 3: The Badgers still lead 14-8 after McIntosh misses again. Happ is back in the game and gets aggressively doubled. He finds Koenig cross-court, again he misses. Again, the pass left something to be desired, so you could credit the double team for that.

Possession number 4: Hayes gets called for a ridiculous phantom double dribble after the post-entry pass is deflected. Inexcusably bad officiating. The kind of stuff that makes you embarrassed to be a fan of the sport.

Possession number 5: Another open 3 for Brown, this time he gets the shooter's roll.

Possession number 6: One of the evening's more depressing possessions, as Koenig fumbles a rebound out of bounds. I don't know if this counted as an official turnover or just a team rebound for Northwestern, but it was a harbinger of things to come.

 Possession number 7: Another turnover, this time Showalter trying to find a cutting Hayes.

Possession number 8: This will be the only shot Ethan Happ takes in this slideshow, and it's from the top of the key. He had the line, I guess.

Possession number 9: With the shot clock running down, Nigel pulls up for a long two and banks it in. Not pretty. But note that the Badgers have now extended their lead to 7 points while scoring 5 points in 9 possessions. Still had to feel pretty good at this point, as Northwestern had scored just 12 points in 12 minutes, and you had to figure Wisconsin would snap out of their doldrums soon.

Possession number 10: After a Northwestern 3, Ethan Happ turns it over trying to find Brown before the double team arrives.

Possession number 11: This was when the game really turned. On their possession, Northwestern hit a tough two point jumper and Showalter was called for a foul for boxing out too hard on the made basket. This is a call that is pretty much never made, particularly against a home team. Really weird. So Northwestern got a make-it-take-it possession, and capitalized with another bucket to tie the game after a 4-point possession. How do the Badgers attempt to take back control? Charlie Thomas in the post.

Possession number 12: Game still tied, but Northwestern played great D on this possession (with Koenig and Happ resting) and Trice turns it over late in the shot clock.

Possession number 13: Now things are starting to slip away, as Northwestern hits another three and the Badgers again turn to Charlie Thomas to stem the tide. Alas, no.

Possession number 14: After another Northwestern 3, the Badgers again get nothing on offense. Hayes tries to create off the dribble at the end of the shot clock, but mostly is trying to draw a foul. Fruitlessly, it turns out.

Possession number 15: Northwestern has now hit three straight threes and scored 16 points on 6 possessions to take a 28-19 lead. Badgers get an open three for Showalter but he comes up short.

Possession number 16: Happ beats a weak double team and finds Showalter for another open 3, this time he nails it.

Possession number 17: Happ finds Koenig for a nice open 3, but Bronson just doesn't have it tonight.

Possession number 18: Happ again finds an open man, Hayes, but he can't score.


This is the moment when it started to seem pretty likely the Badgers would lose. Northwestern goes "2 for 1" at the end of the half, which consists of McIntosh chucking up a prayer, that gets answered by the backboard. Backbreaker. 

Possession number 18: The final possession of this sad stretch. And so it ends, not with a bang, but with a whimper.

Here's one fun thing that happened during this stretch:

Saturday, February 11, 2017

Simulation Saturday Preview!!

Edited: Crap, I forgot Louisville.

Today, FOR THE FIRST TIME EVER, the NCAA will give us an early look at how the top four seed lines would look if the season ended today.  I call this "Simulation Saturday" (as opposed to the actual "Selection Sunday") and you should too. I'm getting a trademark, probably.

It will be kind of interesting to see how this shakes out. Without the benefit of full conference seasons and conference tournaments, things are really up in the air, and this is obviously a pointless made-for-tv exercise. But that's true for all sporting events.

The 1-Seeds

Right now the clear consensus among bracketeers is that Kansas and Baylor are both deserving of a 1-seed. But I think there's also a general consensus that the Committee will probably not actually award two 1-seeds to the Big 12 on Selection Sunday (unless there's absolutely no other choice). Instead, it seems likely that the leader of the ACC—whoever that turns out to be—will be given the fourth one seed (presuming that Gonzaga and Villanova are the other two).

Right now North Carolina, Louisville, Virginia, and Florida State could all make a case for being that team. (And Duke, I guess...) But things haven't shaken themselves out yet, and at this moment picking any one of those teams for the 1-line would really be an exercise in predicting which one of them comes out on top in the ACC.

So for Simulation Saturday, will the committee grant the 1-seeds based on current resumes, or will it bend its processes a bit so that this ends up looking more like the final product?

I'm predicting they will go with current resumes. The main rationale put out for this exercise is to provide a little "transparency" into the selection process, so I think they'll want to come out armed with their "record against RPI top 50" and "conference affiliation is never mentioned in that room" factoids. Accordingly, I predict the 1 seeds will be:


The 2-seeds

One of the reasons I think they'll stick to the script on 1-seeds is that there's no clear leader for elevation among the potential 2-seeds. 

You've got the four ACC teams mentioned above, but right now they haven't really differentiated themselves. 

There are three Pac-12 teams arguably in contention—Oregon, Arizona, and UCLA—but all of them lack the magical "top 50 RPI wins" that the committee loves so damn much. (More on this later.) 

Wisconsin is sitting at No. 7 in the AP poll, so you might think they'd be in the mix. But they also lack the magical top 50 wins, and will likely be punished for it. 

Two teams from the SEC, Florida and Kentucky, should make the top 16, but they're both long shots for even the two line at this point. 

One dark horse is Butler, which is up there with Baylor for most impressive resume. For example, they are an incredible 12-3 in tournament quality tests (similar to Kenpom "Category A" games), which is three more wins of that type than anyone else. Unfortunately for them, this doesn't quite translate into the committee's stupid "magic top 50 RPI" wins, where they are a mere 7-2. The committee won't pay much attention to what are actually very impressive wins like at Marquette, at Georgetown, at Utah, vs. Indiana (neutral). Butler also has lost two of three, and it has two "bad losses" (at St. John's and at Indiana State) that are always hard to evaluate. Still, Butler's 7-2 against the top 50 is pretty good, and I think there's a chance they show up higher than people are thinking.

Another contender purely on the numbers is Creighton. But they've been on somewhat of a slide recently, corresponding to their loss of Maurice Watson for the season. I think they'll be dropped at least for purposes of this exercise and used as a talking point.

Although it would be defensible, I don't think the committee is going to come out with four ACC teams on the two-line. But North Carolina and Florida State are probably locks for a 2. Louisville is only 3-5 against the RPI top 50, so I think they'll be demoted.  So, after all that, here's my guess:

North Carolina
Florida State

That final spot on the 2-line is really hard. I think the main contenders are Florida, Kentucky, Arizona, and Oregon. (With a possible "popularity contest" slot for UCLA.) Arizona and Oregon are only in contention because it seems like the Pac-12 should get a 2, but their "resumes" (as traditionally defined by the committee, anyway) are lacking. Florida has only 4 top 50 RPI wins, but it is No. 7 in the RPI and boast the 6th hardest non-conference SOS (though this is somewhat juiced by "neutral court" games played around Florida while their arena was being renovated). So I'm just taking a wild stab that Florida will be elevated to allow for the talking point of rewarding a tough non-conference schedule.

The 3-Seeds

Let's talk about the Pac-12. It has three really good teams: Arizona, Oregon, and UCLA. It has one other likely tourney team, USC, one bubble team, Cal, and one or two other okay teams (Utah and Colorado?) The rest of the conference is sort of like a mid-major division. As a result, the Big Three are lacking in quality wins, or even opportunities for quality wins. They are also at risk for some "bad losses" when they play the mid-major division on the road.

I'm seeing UCLA on the two-line in some places, and I'm a bit mystified. They are 3-3 against the magic top 50, 21st overall in the raw RPI, with the 280th ranked non-conference schedule. You can obviously make an argument that UCLA is a really good team, but not using objective metrics normally cited by the committee. I'm predicting they'll be demoted and used as a talking point.

Arizona and Oregon are slightly better than UCLA on the top-50 metric, and vastly better on non-con SOS. I think they'll be here on the three line, but could really see either of them anywhere between 2 and 4.


The 4-Seeds

The Big Ten has a problem similar to the Pac-12's, in that there are few opportunities for magic top-50 wins. The bottom of the conference is much better than the bottom of the Pac-12, but that typically doesn't matter much to the committee. So Wisconsin, with its 2-3 record against the top-50 and 246th rated non-con SOS, will likely be relegated to the 4-line for now—at best. Wisconsin might also suffer from application of the "eye test" given its recent inability to dominate inferior opponents.

Besides the teams already mentioned but not placed (UCLA, Creighton, Wisconsin), other possible contenders for the four-line are Cincinnati (great record, but lacking magic top-50 wins), West Virginia (great team, lacking some of the stuff the committee likes), Duke, and Purdue. Possibly Xavier, I guess. Can make a case for any of these teams, obviously, but here's my guess:


I'm betting Duke will get a Coach K bonus, and that UCLA will get a Hollywood bonus.

Edited to add: in my morning haze, I forgot to put Louisville in there on the three line when I demoted them from the two. Of the original fours, I'm demoting Cincinnati just cuz.

Saturday, January 28, 2017

Head Games

Daylight turns into night
We try and find the answer, but it's nowhere in sight
It's always the same, and you know who's to blame
You know what I'm saying, still we keep on playing
Head games

First of all, Foreigner Rocks. 

Second of all, I hate the stupid NBA 3 point line being on the court in college games. UW kids can’t handle the head games. College kids are either too stupid, or too egomaniacal to pretend like it isn’t there. All it takes is the presence of that line, and they feel like they have to shoot the ball from NBA range.

By my official count, the badgers launched 18 of their 25 3PA from NBA range or with their feet on the NBA line. They shot 4 more from well behind the college line, and only 3 from what would be considered a normal college 3. I’m not totally making this up. I went through my DVR of the game and took photos of every 3 point shot. Most look like this:

Or this:

Or this:

Or this:

Or this:

I won’t put up every photo, but there were way too many long threes, especially for a team that only made 3 of 25. UW eventually stopped messing around, launching 0 3PA in overtime, while they made 5-6 FG.

One more thought from an ugly game I almost wish I didn’t watch. Was tonight Happ’s coming out moment. You may remember Frank set a Badger record with 43 points vs. North Dakota in an early season game in his Junior Year. After that, Frank wasn’t always dominant, but it was the coming out moment from which his dominance started. It was his team after that day. That team was loaded with good players, but it was Frank's team. Happ is not the same player, and is only a Sophomore, but I feel like this was his coming out moment. 

After setting a career high with 28 against Minnesota, he set another with 32 vs. Rutgers. Both games on the road, and both wins in OT. Most important, after the Badgers were down 9 with three and a half minutes to go, Happ scored 8 of the final 13 Badger points, including the basket with 2 seconds left to tie. On that play he could have handed off to Bronson, but Bronson was guarded pretty well, so Happ just backed his guy down and took him. Happ then went on to add 7 more points in overtime, outscoring Rutgers by himself 15-13 in the final 3+ minutes and overtime.