For SportsIllustrated.com: Sweet 16 Matchup Issues

My latest is over at Luke Winn’s SI Tourney Blog. In it, I use adjusted efficiency data from Ken Pomeroy and adjusted box score data from TeamRankings.com’s possession-based college basketball game simulations to spotlight a few remaining teams that have matchup issues on defense. Summary: FSU should do great against VCU, Duke doesn’t want to see Kansas in the final, and Ohio State’s defense may be slightly overrated.

Gone, Gaddy, Gone

[EDIT: Ken Pomeroy posted a treatise on plus-minus which pointed out there’s a great deal of error inherent in the use of +/- data, something which has also been pointed out to me by John Ezekowitz.  At this point, I’d advise you to take everything I wrote below with a huge grain of salt.  And I doubt you’ll be seeing any more +/- analysis from me.]

About a month ago, I predicted that Duke would be fine without Kyrie Irving.  My reasoning was that, in the games while Irving was still healthy, Duke had actually performed better with Irving on the bench than they had while he was on the floor – about 7 net points per 40 minutes better.  Well, since the toe became The Toe, Duke has actually played ever so slightly better, with a post-Irving-injury adjusted efficiency margin of 39, compared to 37 with Irving:

Obviously that difference is insignificant, but the main point is that, so far, they’ve been fine.

I fear Washington’s prognosis for life without Abdul Gaddy is not so optimistic.  The same +/- data that soothed Blue Devil worries paints an uglier picture for the Huskies (click to enlarge):

Whereas Duke was 7 points per 40 minutes better with Irving on the bench, Washington has been almost 7 points per 40 minutes better with Gaddy in the lineup.  Some of the Twitter buzz hoped that the injury would give freshman CJ Wilcox a spot in the limelight.  That’d be great, as he has a team-high 131.8 ORtg in his limited time.  Taking a quick look at his +/- data, though, Washington has struggled with him in the game, despite his good offensive rating.  A safe bet here would be that Wilcox’s defense is a step down from Gaddy’s, though the KenPom individual stats don’t paint a big defensive difference between the two, other than Wilcox’s more frequent fouling. Whatever the reason for the struggles, somebody will have to step up if Washington hopes to retain its lofty rating.  If I’m Seth Davis, I’m changing my Washington grade from BUY to HOLD.

[On a side note, it’ll be a shame if this injury does end up impacting Washington, as I expect it to.  The Huskies were looking like a great ratings litmus test, as they were in the top 5 in both Pomeroy and Sagarin’s PREDICTOR, yet #23 and unranked in the two major polls.  Now watch, instead of tearing through the Pac-10 like their namesake through the Delaware, they’ll decline due to the impact of this injury, and the “you either win or lose” crowd will get a chance to trumpet their demise as a black mark against predictive ratings.]

How much will Kyrie Irving’s Absence affect Duke?

[EDIT: Ken Pomeroy posted a treatise on plus-minus which pointed out there’s a great deal of error inherent in the use of +/- data, something which has also been pointed out to me by John Ezekowitz.  At this point, I’d advise you to take everything I wrote below with a huge grain of salt.  And I doubt you’ll be seeing any more +/- analysis from me.]

There was a great post by the basketball distribution a few days ago about the effect of individual players on a team’s offense.  It ended up being extremely topical, given A) his choice of Duke as one of the example teams, and B) Kyrie Irving’s toe.  He calculated that removing Irving’s production from the Duke team would in theory reduce their offensive efficiency by about 3.1 points per 100 possessions, if the vacated minutes were filled proportionally by the other Duke players according to their share of minutes played so far, and if they all played at the same level.  (Obviously, those assumptions are questionable, but it’s the best that can be done with the available data.)

I thought I’d take a look at it from a different angle, one that is probably on even more tenuous footing, but that is nonetheless interesting.  I thought that perhaps, as a freshman, Irving might not be as advanced as his teammates defensively, so losing him might actually improve Duke’s defense.  The only way I could think of to investigate this was to use StatSheet’s plus-minus data to find out what has actually happened this year when Irving sits on the bench.  Before I get to the numbers, I should strongly emphasize that this data is very dependent on who all the other players in the game are, and we shouldn’t take it to seriously.  But I thought the results were drastic enough, and surprising enough, that they’d be of interest.

Championship Game Preview

[NOTE: This will be cross posted over at UFR, hence the duplication of some info from previous AOH posts.]

Time for the last preview of the season (*sniff*). In the last two games, I told you that Butler was slightly favored to win a defensive struggle, because they’d take away Michigan State’s main offensive strength of rebounding and force a lot of Spartan turnovers; and that Duke was slightly favored against WVU, but whichever team could hit their jumpers and/or dominate the boards would win. Well, the Butler-MSU prediction was spot on, as the Bulldogs held Michigan State to their 2^nd lowest offensive rebounding % of the season, and got 19 points off turnovers (according to CBS). The Duke forecast was spot off, as Duke blew out the Mountaineers. But a look at the Four Factors box score shows that the teams were fairly even, except for eFG% - which the Blue Devils dominated largely due to an abnormally strong shooting night, making 13 of 25 from 3-pt range.

I won’t go into as much detail for the championship game, partly because I covered both teams pretty extensively in the semifinal previews. Check those out if you’re looking for the offensive/defensive key traits and similarity scores. By now we all know that Butler wins by playing a smothering man-to-man defense, controlling the defensive boards, forcing turnovers, and hoping they can scrape together enough points via transition opportunities, Matt Howard’s post play, Shelvin Mack’s drives and jumpers, and Gordon Heyward’s versatility – those three combine to take 75% of Butler’s shots while they’re in the game. Meanwhile, Duke wins by playing the best perimeter defense in the country, doing a bit better than average at limiting opponents’ offensive rebounds, and using what John Gasaway calls the “barrage factor” on offense – limiting turnovers and grabbing tons of offensive rebounds, so they get a lot of extra chances to make up for their usually non-elite shooting.

So what will happen when these two teams clash on Monday? Butler has been winning almost entirely due to their defensive rebounding and forced turnovers, but Duke is both the best offensive rebounding team and the least turnover-prone team that Butler has faced – not only so far in the tournament, but all season. However, Duke usually relies on those two factors to score – last night’s jump shot barrage notwithstanding. This is one of the clearest examples there is of a game where a couple of key areas will decide who wins. There’s always a chance that one team will get hot and make all the analysis moot, but it sure looks to me like Duke’s turnovers and offensive rebounds will be hugely important.

This weekend, I put together an Excel spreadsheet that adjusts Ken Pomeroy’s Game Plan data to account for opponent strength. If you want details, check out my last post here on Audacity Of Hoops. I used these adjusted numbers to predict the Four Factors numbers for the championship game, to give us an idea of what to expect:

You can see that Duke is expected to significantly outshoot Butler, and out-rebound them. Both teams should be able to limit their turnovers, and both may be able to get to the line more than average, with Butler having a slight advantage there. But the advantage in eFG% for Duke is huge, and Butler will need to do something to counteract that. Given the way they’ve been playing lately, they may be able to limit Duke’s offensive rebounding, and force more turnovers than predicted by the numbers. They must if they want to have any shot of winning, because it’s unlikely they’ll be able to outshoot the Blue Devils.

Now let’s take a look at the similar-opponent prediction:

The Vegas line is Duke by 7 as I write this, and both Pomeroy and the Similarity system have Duke as an even slightly larger favorite. All the signs point to a comfortable Duke victory. The only thing I can see that would make me second guess these numbers is the fact that Butler has done even better than predicted on the defensive glass, and in terms of forcing turnovers, during the NCAA tournament. They need to continue that in a big way to have any shot against Duke.

Butler-Duke Four Factors

I updated the Opponent-adjusted Four Factors spreadsheet to include last night’s games.  The actual team values didn’t change much, so no point in showing those again, but here are the predictions for Monday’s championship game:



I don’t think any of these should be a surprise to people who have been paying attention.  Duke’s offensive clinic against West Virginia was impressive, but a lot of that was due to them making a higher-then-expected percentage of their jumpers.  Obviously, if they’re on fire again Monday, it’ll be a blowout.  But a more likely scenario is a game that looks a lot like Butler-Michigan State, except with Duke turning the ball over less than Michigan State.  I expect Duke will win without the need for any last minute heroics, mostly by outshooting (and possible outrebounding) Butler.

[EDIT: I took a page from the basketball distribution, and used linear regression to map single game Four Factors values onto efficiency margin.  The numbers above work out to an 11.1 efficiency margin.  Adjusting for the 62-possession pace predicted by Pomeroy, that's a point margin of 6.9.  Obviously in Duke's favor.]

Opponent-Adjusted Four Factors

This is something I’ve been thinking about for some time, and I finally gave it a shot yesterday.  I should point out right up front that I haven’t done any kind of testing to see if the way I’ve implemented it makes sense, nor checked to see if the adjusted numbers are more predictive than raw Four Factors data.  But I wanted to get a rough draft of the system done before today’s games are underway – I’ll test and tweak in the off season.

My method was basically to reproduce the Pomeroy ratings, except using (for example) offensive and defensive OR% instead of offensive and defensive efficiency.  I tested the method first on efficiency, just to make sure I was able to reproduce Pomeroy’s numbers.  He actually weights the numbers based on how recent the games are, and I didn’t try to mimic that, but my numbers still essentially aligned with his:

That’s the easy part; I’ve done that before.  The trickier part was deciding what value to use for home field advantage for the various factors.  Pomeroy uses 1.4% per team for each number - he adds 1.4% to the home team’s offense and visitor’s defense, and subtracts 1.4% from the home defense and visiting offense.  I don’t know where he got that number, but I was able to roughly reproduce it (1.25%) by looking at only home-and-home games from this season, finding the average overall efficiency, and the average home efficiency, and then taking the square root of the ratio between the two:

( [Ave Home Eff] / [Ave Overall Eff] ) ^ 1/2 = (103.6/101.0)^0.5 = 1.0125

Since this makes sense, and seems to reproduce Pomeroy’s HFA number, I used this method to come up with the HFA adjustments for the Four Factors:

• eFG%: 1.007
• TO%: 0.980
• OR%: 1.007
• FTR: 1.031

Once I had these, all I had to do was re-do the opponent adjustments using the Four Factors and their HFA’s, instead of the efficiency values.  Then I looked to see if the outputs passed the smell test.  I’d say they look fine; here is a comparison of the raw and adjusted Four Factors rankings for the Final Four participants (click image for larger version):

I highlighted a few of the significant changes.  For the most part, all the teams look better in all the categories, but there are a few exceptions.  Here are a few notes:

• The only instances where the adjustment moved a team’s ranking down more than a couple spots were Butler’s eFG% and Michigan State’s FTR.
• Duke and West Virginia’s shooting numbers are not as bad as they seem – the adjustments pull them up to basically even with Butler and MSU.
• Michigan State’s turnover problem is as bad as it seems – especially with the adjustment improving Butler’s defensive TO%.
• The best three offensive rebounding teams in the nation are still alive.
• Butler doesn’t have as much of a defensive rebounding advantage as I thought.
• The FTR adjustment for MSU is interesting – I’m wondering if that is a result of Big Ten officials “letting them play.”

Of course, now that I have these numbers, the obvious temptation is to use them to predict the Four Factors numbers for tonight’s games.  I of course gave in, but right now I have no faith whatsoever in the accuracy of these.  Just for fun, though:

Eyeballing those, it looks like Butler wins by forcing Michigan State turnovers, and Duke wins by forcing West Virginia into a poor shooting night.  Sounds about right to me.

Similarity Preview: Duke Vs. West Virginia

[NOTE: Cross posted at UFR. For more info on similarity scores and predictions, see here and here.]

Saturday’s headlining game features the offenses ranked 1^st (Duke) and 12^th (West Virginia) in adjusted offensive efficiency, compared with 25^th (Michigan State) and 46^th (Butler). So it obviously features the better shooting teams, right? Nope:

Duke and WVU made it this far not because they make the most of their opportunities, but because they get so many more opportunities than their opponents. They’re both great rebounding teams, and also come out on the plus side of the turnover balance sheet. In fact, when you add together their rebounding and scoring margins, they are the top two major conference teams in the country, in terms of creating extra chances for themselves, with both averaging over +6 in combined Reb+TO margin. Obviously they can’t both keep this up on Saturday, and whoever wins the “extra chances” battle will have a very good chance of extending their season.

Now let’s get more specific, and look at what to expect when Duke has the ball:

Duke’s not going to be able to get a lot going from inside the arc, as they’re below average in 2P% while WVU is on the plus side. And not shown here is the fact that the same is true for Block%, meaning the interior defense of Wellington Smith and John Flowers may end up playing a key role. Flowers had 3 blocks in 23 minutes against Kentucky, and I’d expect the two players to combine for at least that many against Duke.

But as indicated above, Duke’s emphasis is on using offensive rebounding and a low turnover rate to ensure they get a lot of looks at the basket – a good shooting night would just be icing on the cake. West Virginia is above average at defensive rebounding and forcing turnovers, but just barely. Here is how they fared this season against major conference teams in the top 30 in OReb%:

It’s going to be tough to beat Duke if they allow another 40% offensive rebounding night. They were able to overcome that against Kentucky by holding them to a low shooting percentage (37.3 eFG%) and forcing a lot of turnovers (22.6%). They might be able to hold Duke to similar shooting numbers, but likely won’t be able to force them into that many turnovers. Duke should be able to take care of the ball, and get a lot of first and second shot opportunities, but their best looks will be long jumpers. How efficiency they are will ultimately come down to whether they are hitting those jumpers.

You may have noticed above that West Virginia plays at a slow pace, and are wondering whether that will frustrate Duke. No, not at all – the Blue Devils have played 12 straight games at a sub-70-possession pace, and for the year they are 17-1 in games with 65 or less possessions. Shouldn’t be an issue.

Now how about when West Virginia has the ball:

This is going to read a lot like the section above, so I’ll keep it relatively short. West Virginia should also have trouble getting open first looks on offense, but Duke defends the perimeter (1^st in 3P% against, 10^th in fewest 3PA/FGA) better than the interior (39^th in 2P%), so the Mountaineers won’t have as many open long jumpers as Duke will (nor as many as they had in the first half against Kentucky). However, WVU is even less dependent on good shooting than Duke is, as they’re even better at offensive rebounding (and because they shoot more 3’s, there are a few more rebounds for them to grab). They also get to the line slightly more, but it’s a small advantage.

So if everything holds true to form, West Virginia’s offense will look largely the same as Duke’s. They’ll turn it over a bit more, and probably shoot a bit worse (especially from long range). But they’ll draw a few more fouls, and grab a few more rebounds. The core strategy will be the same, though – throw it towards the hoop, then go and get it in the likely event that it misses.

Let’s look at the Similarity Prediction:

Vegas has the Blue Devils favored by 2.5, and Pomeroy’s numbers have them even stronger. The similarity analysis disagrees, showing that both teams have performed nearly the same in games against similar opponents – which makes perfect sense, given that both teams use the same volume-over-efficiency strategy on offense, and both rely on good FG% defense (as opposed to turnovers or rebounding) at the other end. Duke and West Virginia usually miss a lot of shots, but make up for it with excellent offensive rebounding. If one of them starts hitting their first chance shots, or if one can dominate the boards, that team will probably win. Duke is better at shooting and defending the three point line, and that advantage is what separates the two teams statistically. But given West Virginia’s first half against Kentucky, it should be clear that anything can happen in a span of 30 possessions. Duke’s perimeter advantage will likely be less important than the advantage that one of these teams gains through luck – or clutchness, or heart, or whatever you want to call it. So I feel comfortable with the similarity prediction – Duke as a slight favorite, but really anybody’s game.

Something’s Gotta Give: Extra Chances

I noted in a pre-tourney post that Duke makes up for their poor interior shooting by corralling 40% of their misses, which gives them more cracks at the basket.  That’s really only part of the larger story, which is that this Blue Devils team is one of the best in the country at getting themselves more scoring chances than their opponents.  Let me explain what I mean.

Given the national averages listed on Pomeroy’s site for TO% (20%), 3PA/FGA (33%), 3P% (34%), 2P% (48%), OReb% (33%), and FTA/FGA (38%), I estimate that about 2/3 of all possessions are simple one-chance affairs, where a team gets exactly one shot attempt (or one trip to the free throw line).  The actual number’s not important – the point is that one-and-done is the natural state of things.

There are two things a team can do that will disrupt this natural state – grabbing offensive rebounds and forcing turnovers.  We can count how many times a team does these things, and how many times they let their opponents do them, and the difference will represent the “extra chances” that a team has over the course of the game.

Using Duke as an example (numbers pulled from TeamRankings.com):

ExtraChances/G = (OR/G – OppOR/G) + (OppTO/G – TO/G)

ExtraChances/G = (12.9 – 9.7) + (14.2 – 10.8) = 6.6

This can be further adjusted for pace:

EC/100 = 100 * (ExtraChances/G) / (Poss/G)

For the teams in the Final Four, this doesn’t make much difference, so I’ll be ignoring pace for now. (Plus, you could argue that a higher pace for these teams is a good thing, and we don’t want to toss that info.)  I pulled the stats for every 2010 team and found their ExtraChances/G.  Here’s a Google Spreadsheet that shows them all – I’ve highlighted the Final Four teams in blue:



Saturday’s main event will be a battle between the best two major conference teams in the country, in terms of creating extra chances for themselves.  These teams win by exploiting volume, as opposed to efficiency, and obviously they can’t both come out ahead.  If one of them does, there’s your likely winner.

Similarity Preview: Duke Vs. Baylor

[NOTE: Cross posted over at UFR.]

Well, the St. Mary’s game didn’t go at all as expected, with the Gaels not really putting up much of a fight. There’s no way the same thing happens with Duke. Let’s take a look at what the game will be like when the Blue Devils have the ball:

One of the knocks against Duke the last few years has been that they lack toughness and size, but this year’s team is better in most of the toughness/size categories. They’re 7^th nationally in effective height, and 8^th in OReb%, both of which are the highest they’ve ranked since Pomeroy started keeping track. The one area where they still seem to suffer is 2P shooting percentage, where they’re ranked 198^th This is partly due to getting their shots blocked at a high rate – 209^th nationally – which means Udoh may be in for a big defensive game.

Duke has subpar shooting for a supposedly elite offense, but they make up for it with all those offensive rebounds, and by rarely committing turnovers. Those happen to be Baylor’s defensive weaknesses, so the Blue Devils will be able to play exactly the kind of game they want. I expect them to do well offensively. Baylor will need to solve Duke’s defense in order to win:

In keeping with the theme, this year’s Duke defense is tougher as well – this is their lowest 2P% allowed since 2005, and their best defensive rebounding in the Pomeroy Era (2004-present). They’ve paired this with their usual excellent perimeter defense (ranked 1^st in 3P% against, and 8^th in 3PA/FGA), and the result is the 3^rd-best adjusted defensive efficiency in the country. However, despite being improved on the defensive boards, they’re still only 120^th nationally – and offensive rebounding is one of Baylor’s biggest strengths on offense (they rank 15^th). They’ll probably need a very big game on the offensive boards if they want to win.

To Baylor’s advantage is the fact that they’re not over-reliant on three pointers. Duke can shut teams down from outside, so it’s good that Baylor has a balanced inside/outside attack, ranking in the top 25 in both 3P% and 2P%, and right at average in 3PA/FGA. Duke will try to shut them down on the perimeter, but Baylor’s guards should be able to drive or get it to Udoh or Acy in the post. If the Baylor bigs can get the job done against Brian Zoubek, the Bears have a chance.

Vegas has Duke as a 4 point favorite, and my system basically agrees. The straight efficiency stats show Duke as 5.5 point favorites, but the similar opponents analysis shows that Baylor has done better than expected offensively against teams whose defenses are similar to Duke’s. I see no reason to disagree, so I’ll go with the similarity prediction here, and say that Baylor should be able to hang close, but Duke is still the clear favorite.

Similarity Predictions: Elite 8

Figured I should get these up before the games start this afternoon.

As I mentioned in the KSU-Butler preview, I think the prediction for that game is skewed by the early season numbers.  Butler’s playing better than they were then.  If I look at only games from this calendar year, then the Similarity prediction pretty much agrees with Pomeroy and Vegas.

I should get a Duke-Baylor preview done this afternoon, and get it posted here and at UFR.

Final Four Characteristics

Just a short post to share something I noticed when digging through data last night…

In the Pomeroy Era (2004-09), there have been 24 Final Four teams.  All of them except 2006 George Mason and 2006 LSU fit the following critera:

• 30th or better in Adjusted Offensive Efficiency
• 30th or better in Adjusted Defensive Efficiency
• 15th or better in Pythagorean Rating
• 150th or better in defensive eFG%
• 150th or better in offensive 2PFG%
• 150th or better in defensive 2PFG%

Here are the teams in each region that fit these criteria:

• EAST: Kentucky, West Virginia, Wisconsin
• WEST: Syracuse, Kansas State, BYU
• MIDWEST: Kansas, Ohio State
• SOUTH:

Yes, I left the South blank on purpose.  Duke is disqualified due to their terrible shooting percentage within the arc (46.9%, 205th nationally).  However, they make up for this by being a fantastic offensive rebounding team (40%, 10th nationally), so given the lack of alternatives, I’d slot them in as the best fit in the South by these criteria.

Tickets Punched: #27 - #31

This last post in the Tickets Punched series gives you the offensive and defensive comps for today’s four championship games, plus one that I somehow overlooked till now.

OHIO




The only one of these past comps to make the tournament was 2009 Mississippi State, and their offense was shut down in the first round by Washington.  The conventional wisdom is that teams who are weak inside (below average OReb% and 2P%) tend to do poorly when push comes to shove.  If true, that wouldn’t bode well for Ohio.

Similarity Predictions: 3/14

These predictions were 3 for 3 yesterday, nailing Washington over Cal.  Let’s keep going with today’s Big 6 games.

Similarity Scores: Title Contenders, Part 2

Now that we've seen the historical comps for the current AP Top 10, let's take a look at the 2010 comps for the 6 teams that I placed in the top tiers at the end of the last post: Kansas, Syracuse, Kentucky, Duke, Villanova, and Ohio State. [Again, data is from the games through March 2, 2010.]

When I first looked at 2010 comps over at UFR, the most similar team to Kansas was Kentucky, which made for a great storyline.  Since then, however, I've updated the data, and Kentucky has dropped a touch.  They're still in the top ten, but not at the #1 spot.

2010 Kansas - 2010 Comps

SCORE	YR	TEAM
91	2010	Maryland
91	2010	Minnesota
91	2010	Baylor
90	2010	Kentucky
89	2010	Texas
89	2010	Brigham Young
89	2010	Duke
89	2010	Syracuse
88	2010	Ohio St.
88	2010	Georgetown

Maryland is, unfortunately, a team I don't know much about this year.  However, I'll get a chance to watch them tomorrow while I'm wishing I could watch Kansas State @ Kansas.  Still, a score of 90 for Kentucky is reasonably similar, and they're the most similar of the elite teams.

Similarity Scores: Title Contenders

This is part 3 (or 5, depending on if you count the posts at UFR) of the Similarity Scores series. The post on how the scores are calculated is here, in case you missed it.  Tonight I'll be taking a look at which teams from the past are most similar to the current AP Top 10, and how those teams fared in the NCAA tournament.

[Data is from games through March 1, 2008.]

The Big 12 post ended up checking in at a Posnanskian length, which is usually a bad thing for anyone other than Joe, so I'm going to keep the commentary to a minimum this time.  Also, there will be a couple changes to the lists themselves.  First, I'm only including teams that made the NCAA tournament.  If they weren't good enough to make it, they can't be THAT good of a comp.  And second, I'm adding two new columns to these graphs: NCAA seed, and PASE (Performance Against Seed Expectation).  This tells to what extent each team exceeded or fell short of expectations, relative to their seed in the big dance.

2010 Syracuse - Historical Comps

SCORE	YR	TEAM	SEED	W's	PASE
90	2009	Syracuse	3	2	0.1
88	2005	Syracuse	4	0	-1.5
88	2008	Kansas	1	6	2.6
88	2006	Kansas	4	0	-1.5
87	2005	North Carolina	1	6	2.6
87	2007	Kansas	1	3	-0.4
87	2006	Florida	3	6	4.1
86	2007	Georgetown	2	4	1.6
86	2004	Providence	5	0	-1.1
86	2008	Georgetown	2	1	-1.4
		Average	2.6	2.8	0.5

Pretty all-or-nothing here - 3 champs, and 3 first round upsets.  But notice that the upsets are all 4/5 seeds, meaning they may have had good numbers, but they apparently didn't take care of business as well as this year's Orangemen.  Limit it to seeds 1 through 3, and you're looking at an average of 4 wins, and a +1.3 PASE.  Or, looking at just 1 seeds, where 'Cuse expects to end up this year, we see 5 wins and a +1.6 PASE.