Mini-Preview: UNLV-Kansas State

[EDIT: After writing this, Jacob Pullen and Curtis Kelly were ruled ineligible fro Kansas State.  So, umm, never mind.  KSU is no longer a “good” offense, so UNLV should be fine.]

[This post is really just an excuse to use a spreadsheet I whipped up, which takes a year and a school as input, and automatically creates a chart like the one below.]

UNLV tips off against Kansas State in Kansas City a mere hour from now.  The Rebels started off the year with a bit of hype, and lived up to it at first, topping Pomeroy ratings #10 Wisconsin at home by 3, and blowing out some scrubs.  But they’ve stumbled over the last 10 days, following up a very understandable loss at #13 Louisville with a much less forgivable home loss to #100 UC Santa Barbara.  In truth, their problems started to show up 2 games previous to the Louisville loss, when they beat a poor Nevada (#202) team by only 12, but sometimes a W can have a lipstick-on-pig effect.

It’s clear that a 12-point win over #202 isn’t fantastic (Pomeroy had predicted UNLV by 18), but sometimes it’s hard to get a feel for exactly how good/bad a performance is.  We can use opponent ratings to shed some light on the issue by using Pomeroy’s efficiency prediction formula:

Predicted Offensive Efficiency = ([Team Adj Off] + HFA) * ([Opp Adj Def] + HFA) / [Lg Avg Eff]

For each game that a team has played, we can replace the predicted efficiency with the team’s actual raw efficiency in that game, plug in their opponent’s rating, the league average rating, and the appropriate home field advantage (+/- 1.4% for each team, in a normal H/A situation) , and solve for [Team Adj Off].  That gives us the team’s single game adjusted offensive efficiency rating – essentially, this is how efficient a team would have been if they played exactly the same, but were facing an average opponent on a neutral court.  We can do the same for defense, and from those two numbers we can calculate the efficiency margin (which I find more intuitive to use) or Pythagorean rating (which Pomeroy uses to rank teams).  As a last step, we can take the single game Pythagorean rating, pretend that’s how the team has played the whole year, and see where they would rank in the Pomeroy ratings.  That allows us to say, for example, UNLV played like the #232 team in their loss to UC Santa Barbara.  The chart below shows this “played like” rank for each of UNLV’s games so far. (It also shows, from left to right, the location, opponent, opponent ratings, raw game efficiencies, and adjusted game efficiency ratings.)

 

You can see that UNLV played great through the first 7 games, and then has really struggled over the last 5.  They’re still rated #22 by Pomeroy, but taking a close look at the individual game adjusted ratings reveals something interesting.  Their overall defensive rating so far is 89.7, but that’s largely because of ridiculous defense in a few games against poor offensive teams.  Here are the teams they’ve managed to post a sub-90 defensive rating against so far, along with those teams’ offensive ratings (keep in mind, average is 100):

• UC Riverside (90.6)
• SE Louisiana (91.7)
• Illinois State (97.1)
• Southern Utah (90.9)

That’s it.  Their 30th ranked defensive rating comes in large part from really cranking the screws on the little guys.  If they want to compete in the Mountain West this year, that’s going to have to change.  And if they want to win their semi-road game tonight against Kansas State (offensive rating of 106.7), that’s going to have to change.  I’m not saying it definitely won’t, but I’d say KSU has a better chance than UNLV of bettering their Pomeroy prediction (KSU by 1) tonight.

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.

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.

Similarity Preview: Michigan State Vs. Butler

[NOTE: Cross posted at UFR.  Also, for background on the similarity scores and predictions, check out here and here.]

The early Final Four game on Saturday pits Michigan State against Butler. To get there, the Spartans squeaked by a parade of low seeds, winning by a total of 13 points against teams seeded #12, #4, #9, and #6. Butler, on the other hand, beat #2 Kansas State in the regional final by 7 points – more than Michigan State’s combined margins for their games against New Mexico State (3), Maryland (2), and Tennessee (1) – and led #1 Syracuse by double digits before eventually winning by 4. This is all a long way of saying that in the games I watched, Butler won by outplaying their opponents, while MSU won by out-lucking them. But what’s done is done, and the way a team advanced to Indy isn’t going to affect this weekend’s final score. The only thing that matters is what goes down on the hardwood. Let’s take a look at what to expect when Michigan State has the ball.

Despite losing Goran Suton, and having no regulars taller than 6’8”, Michigan State’s 2010 offense is a near clone of the 2009 version. OK, not that weird, right? Well, how about this:

Despite never having Goran Suton in the first place, Butler’s 2010 defense is also a clone of 2009 Michigan State. If ever there were a game perfectly set up to let Tom Izzo demonstrate his supposed March coaching genius, this is it. He’s facing a Butler team that’s drawing (justified) raves for its tremendous tourney defense, having manhandled two offenses that are significantly more efficient than MSU. His team’s leader in minutes, points, and assists is out of commission, and other significant players are nursing injuries. His opponent will be playing a mere 6 miles from their home gym. But the basketball gods have handed him an advantage to exploit – this fabulous defense that he’s up against is a whole lot like the one he happened to coach last year, and you’re fooling yourself if you don’t think a great coach like Izzo wouldn’t know how to best attack his own defense. How much is that style-familiarity worth? Beats me.

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 Preview: Kansas State vs. Butler

[NOTE: Cross posted at Upon Further Review.]

If Kansas State wins on Saturday to reach the Final Four, basketball historians will look back and think they had a relatively easy path to Indianapolis, playing no team seeded better than #5. That’s misleading, though, as BYU, Xavier, and Butler are all much better than their seeds indicate. Take a look at the RPI, Pomeroy, and Sagarin ratings for each team, along with the average of those, what seed that would entail, and what seed they actually received (I included Pitt to show that Xavier is actually better than Pitt):



They will have basically played three Sweet 16 games in a row, which is no tough task. Though all three teams are rated roughly equal, the game against Butler will have a very different feel. Butler is a slow-paced defensive-oriented team, while BYU and Xavier were more than happy to turn their games into offensive shootouts. If Butler can avoid turnovers – and Butler usually can, but it’s a big if when facing a KSU team whose main defensive strength is creating them – then they should be able to impose their tempo on the game. Butler’s fastest-paced game so far in the tourney was 67 possessions, in the opening round against UTEP. The Wildcats have only played 6 games all year that were that slow, going only 3-3 (compared to 26-4 in faster games). All three of those losses were to Kansas, while the wins were over Colorado, Oklahoma, and North Texas – so they haven’t beaten a good team in a slow game once this year.

On the other hand, the tempo argument can be used against Butler as well. KSU has reached at least a 70-possession pace in 2 of 3 tourney games. Butler has only played 5 games that fast all year, going 3-2 (compared to 28-2 in slower games). Their losses were to Minnesota and Georgetown, and their wins were against Youngstown St., Illinois-Chicago, and Valparaiso. So they’ve also not beaten a good team and Kansas State’s preferred tempo. My guess is that neither Butler’s nor KSU’s trend will change – whichever team gets to play their style of game will win. As you’ll see below, my system picks K-State as a large favorite, but I think it may have a blind spot here in regards to the tempo issue.

Let’s go over what the game will look like when Butler has the ball:





I think the most important category in the above two tables is TO%; you can see this is a strength vs. strength match up, with Butler being as good at avoiding them as K-State is at causing them. As I mention before, if Kansas State can win this battle, and force Butler to commit more turnovers than usual, I think they can force the pace and win this game. Another area that could be key is offensive rebounds – Butler doesn’t get many, but Kansas State doesn’t prevent them very well, either. If the Bulldogs get more second chance points than they’re accustomed to, it could be a bonus for them.

One facet of the game where it seems clear what will happen is free throws. Butler gets to the line often, and Kansas State puts their opponents there often, so expect a parade of trips to the line for Matt Howard and Ronald Nored (who have the top FTR’s on the team).

Last game, I told you that Curtis Kelly should be salivating, as Xavier was relatively weak inside, and he ended up with a line of 21 points, 8 rebounds, and 5 blocks, near his season highs of 22/11/6. Butler’s not quite as bad inside as Xavier, but they do get blocked quite often, and aren’t very tall (293^rd in effective height). Expect another big game from Kelly, though perhaps not quite as good as last night.

Now how about when Kansas State has the ball:





Kansas State likes to push the ball up the court, but Butler will get everybody back to make this more difficult. That’s part of the reason Butler has such a low offensive rebounding percentage – they choose transition D over crashing the boards. If you watched the Kentucky-Cornell game, you saw one of the more dramatic examples of this that I can remember, with at times literally zero Cornell players within the three point circle when their shot hit the rim. Rebounding on Kansas State’s offensive end will be the direct opposite of this – they hit the boards hard (5^th nationally in OReb%), but Butler is one of the best in the country at boxing out (13^th in OReb% allowed). This is another strength-on-strength battle that will go a long way towards deciding the game.

Though it’s not shown above, Butler has been forcing a high number of turnovers during the NCAA tournament. Being careful with the ball is not a huge strength of KSU, so there’s a chance Butler can keep this new trend going.

We all know by know that free throws are on of Kansas State’s main weapons. Butler has only been middling at avoiding fouls overall this year, but have done much better during the tournament. I’m guessing this trend will end Saturday.

Putting it all together, here’s what the similarity system says:



Frankly, I don’t agree with this at all. Something I want to address in the offseason is that early games are weighted equally to later games (this was a problem with the Xavier prediction as well). Most of Kansas State’s advantage here is derived from some bad defensive games early in the season against (as that’s when they played the major conference teams that are similar to Kansas State). If I take out games from November and December, the similarity system changes it’s mind, and basically agrees exactly with Pomeroy:



That’s what my gut says as well – I expect a close, tough game with Kansas State a slight favorite.

Similarity Preview: Baylor vs. St. Mary's

Just a quick post to relay info that I forgot about yesterday: my preview of Baylor vs. St. Mary's is posted over at UFR.  To make a long story short, the system predicts a very close game, with a slight advantage to Baylor.  Head over to UFR if you want more details!

Similarity Preview: Kansas State vs. Xavier

[NOTE: Cross posted at Upon Further Review.]
[NOTE 2: More problems with tables.  I apologize in advance.]

Today I’ve gone more in-depth than I expected do, as there are so many interesting factors influencing this prediction.  So I’ll spare you the BS intro and get right to the fun part.  As always, since this is a post design for UFR, I’ll assume you’re already intimately familiar with Kansas State, and the first half will focus on Xavier’s style of play.  We’ll start with Xavier’s offense.

XAVIER OFFENSE
Key Traits:			Off Eff	TO%	3P%	2P%	OReb%
	2010	Xavier	115.8	17.8	37.4	50.4	33.7
Std Dev from Ave			1.6	1.4	1.0	0.7	0.1
SIM	Similar Teams		Off Eff	TO%	3P%	2P%	OReb%
94	2010	Villanova	116.7	18.7	37.3	50.4	37.6
93	2010	Memphis	114.8	17.0	38.8	50.6	32.5
92	2010	Mississippi	113.4	17.1	36.7	50.8	34.7
92	2010	Vanderbilt	113.7	19.2	36.9	51.5	32.2
92	2010	Virginia Commonwealth	112.3	18.2	36.7	50.4	36.3

Xavier can shoot well and doesn’t turn the ball over, but these stats indicate they're not great on the offensive boards.  One game ago I would have warned you to look past the stats, as in their 10 games leading up to round two against Pitt, they averaged an extremely high 39.4% offensive rebounding percentage (which would rank them 12^th in the nation if they’d done it all year.  I thought they had put the pads on during practice, and solved their issues.  But then they came out in the last game and went back to their old ways, only grabbing 19% of their offensive misses.  If weak sauce Xavier shows up again in the Sweet 16, they’re likely finished.

One stat not listed above is Block% - Xavier gets blocked on 12% of their shots, which ranks 323^rd out of 347 teams.  This plays right into Kansas State’s hands, as they block 12.8% of opponent shots, 25^th best nationwide.  Curtis Kelly should be salivating.

Similarity Previews: KC-Area Teams

[NOTE: Some of this is cross posted over at Upon Further Review, a great KC-area sports blog.]

With the success of the similarity predictions so far (WARNING: extremely small sample size):



I figured I’d continue down this path, at least until I start to see some bad results.  I’ll be doing a comprehensive preview of the first round games that highlights the instances where the similarity prediction dovetails from the standard Pomeroy prediction, but first I’m going to tackle the match ups involving teams that are of interest to UFR readers.  Any system that pegs the KU and KSU games as anything other than huge mismatches probably involves throwing things off the Empire State Building, so I won’t spend much time on those games.  The more interesting game is Missouri-Clemson, so that’s the one I’ll start with, and focus on.