The Highs and Lows of LaQuinton Ross' Weekend

LaQuinton Ross sent Ohio State to the Elite Eight with a three pointer against Arizona. Just type his name into Google and you can pick from tons of articles that tell you that. However, Ross was involved in an equally as crucial three pointer that played a tremendous role in sending Wichita State to the Final Four. Ross' shot may have gotten the attention of the media, but his defense went virtually unnoticed (to my knowledge).

With 2:30 left in the game, Ohio State had nearly completed their comeback. Wichita State was up three and had the ball. Ohio State was really one stop away from getting in great position to win the game. Wichita State broke the pressure and with 17 seconds left on the shot clock had the ball pulled out:

In the photo above, you can see the start to Wichita State's high pick and roll. Ross is circled and at this point is in reasonable guarding position on Tekele Cotton considering the context of the play.

Continuing on with the play, off of the pick and roll Ross does the right thing by sinking into the lane. It looks like he had the defensive assignment of showing on the roll man. His job is to be in a position where he can make the pass to the roller difficult while also being able to close out on his actual man. At this point in the play (above), Ross is in position to do just that.

The pick and roll ultimately proves unsuccessful for Wichita State. Ohio State switched the screen and Deshaun Thomas winds up guarding Fred Van Vleet (the ball handler). It appears that Wichita State is content with simply spreading the floor and letting Van Vleet create as the shot clock winds down. However, before Van Vleet looks to make his move, this happens:

Maybe somebody reading this can shed light on what exactly Ross is doing in the GIF above. The pick and roll is over, so he should be closer to the passing lane between Van Vleet and Cotton. He points at a screen occurring behind him and then right after points at his man (Cotton). I think he just got mentally lost on the floor and pointed at Cotton only to realize at the last second that was his man.

The point here is not that Ross is a bad defender. Obviously this one play does not define Ross as a defender or as a player in general. The real point is the focus on offense over defense. In my opinion, Ross' defensive blunder was just as important as his offensive heroics. However, the two plays were not treated close to equally in the analysis of Ohio State's weekend performance.

Indiana's Weakness

If you were to force me to pick a team I think is going to win it all, I would likely take Indiana. On the Sweet 16 efficiency graph, the Hoosiers have the best offense of anyone and an average defense (relative to the other 15 teams). C.J. Moore pointed out recently that the Hoosiers' weakness is playing at a slow pace. Moore noted that Indiana's record is bad in games with 64 possessions or less.

I am naturally pretty skeptical of change in pace being a big factor in a team's success. Ty Lawson's UNC team from a while back is the prime example. They played at a tremendous pace, but were equally as deadly in the half court (contrary to popular opinion). Great teams tend to be great, pretty much regardless of pace. To examine Indiana, I wanted to go beyond simply looking at their record by pace. Instead, I looked at the effect of pace on offensive efficiency and defensive efficiency. I wanted to make sure to account for strength of schedule. To do this I calculated AdjO and AdjD for each game as:

AdjO = (Indiana's Game Points Per 100 Possessions) - (Opponent's Average AdjD)

AdjD = (Opponent's Average AdjO) - (Indiana Opponent's Game Points Per 100 Possessions)
Note: Higher numbers are a good thing for Indiana for BOTH AdjO and AdjD

The highlighted portion of the table shows the culprit of Indiana's struggles. In games with under 65 possessions, the Hoosiers are fine offensively but have been much worse defensively. This is probably an unexpected finding, but I think there are some reasonable explanations. First, I didn't think for a second that Indiana would be a worse offensive team in slow paced games. The Hoosiers have the number one offense in the country. The number one offense in the country isn't likely to have any big weakness. Regardless of the pace of game, Indiana can score the basketball. Still, the question remains: why does Indiana's defense struggle in slow paced games? 

The convenient answer is to blame it on Jordan Hulls. He has been perceived as Indiana's defensive weakness for most of the season. This very well might be a part of it. In the half court, opponents may be able to expose Hulls as an on ball defender. Maybe a better reason is Indiana's defensive style. The Hoosiers  don't let their opponents get good looks and don't foul. They are 18th in the country in opponent eFG% and 14th in the country in opponent FTRate. However, they are very average when it comes to rebounding (152 in DR%) and turning teams over (120 in TO%). I suspect that these defensive shortcomings are more exposed in a grind it out, slow paced game.

The following shows the effects of pace on Indiana in graphical form: 

As you can see, Indiana's round of 32 game was an exception to their season performance. Indiana was very good defensively on Sunday, but scored fewer points per possession than their opponent's defensive average for the first time all season. The thing that might stand out most to me from these graphs is Indiana's defense against faster paced teams. In games over 70 possessions, Indiana's defense has been great. Like I said before, IU's offense is great regardless of pace. So in uptempo games, it's going to be very difficult to beat the Hoosiers.

Summit League Championship Preview

Tonight in the battle for the Dakotas, Nate Wolters will attempt to get back to the NCAA tournament one more time for his senior season. The 24-8 North Dakota State Bison stand in his way. Both teams are dominant on one side of the ball. SDSU is ranked first in the Summit League in offensive efficiency, while NDSU is ranked first in the Summit League in defensive efficiency. The teams split their two regular season meetings this year.

We knew to expect big things from Nate Wolters and his team this season, but NDSU has been a big surprise. Defense has been the key to the Bison's success and it has been very Bucknell-ian. They don't create many turnovers, but they make you shoot a poor percentage and then hold you to one shot (rebound). Below is a look at their defensive FG% at the rim, using hoop-math's numbers:

NDSU ranks number 8 in the country at defending shots at the rim. These shots have been found to be much more controllable (from a defensive perspective) than three pointers. NDSU opponent's have shot 32.3% from three this season (91st in the country). The table below summarizes NDSU's FG% defense:

It's no secret that mid-range jumpers are not an efficient way to score in basketball. Ohio State leads the nation in opponent's two point jumper field goal percentage at 27%, while Portland is last at 45%. So NDSU is above average in relation to the rest of the NCAA. The 1.04 points per shot at the rim seems high compared to the other two shot types, but is nearly as good as it gets for NCAA teams.

Now that we have some background on NDSU's defense, let's take a look at the same analysis but for South Dakota State's offense:

South Dakota State has been about average for NCAA teams at the rim this season, and they have actually shot the same percentage from three as they have on two point jumpers. Obviously, these shooting percentages are not independent of each other. For instance, taking a pull up jumper may force the defense to play tighter and thus make it easier to get to the rim. Making threes stretches the defense and shots around the hoop make a defense collapse inside.

We know that defenses have a larger effect on two pointers than three pointers. However, I'm not sure exactly how much influence the offense has versus the defense. For simplicity, let's say that on any two point shot the offense and defense are equally important. So we can simply average NDSU's defensive FG% and SDSU's offensive FG% together to get an expected FG%. Let's also say (arbitrarily, I want to look more into this in the future) that the offense accounts for 75% of  3P% and the defense the other 25%. Using this, the table below shows SDSU's expected FG% by shot location in tonight's game:

South Dakota State has four very capable three point shooter in Nate Wolters (39%), Jordan Dykstra (44%), Brayden Carlson (34%), and Chad White (44%). The Jackrabbits should not be afraid to let it fly from downtown tonight. A semi-contested three from a great shooting team like SDSU is probably better than testing NDSU's great interior defense.

Quantifying Carrick Felix's Defense

Arizona State, picked to finish 11th in the Pac-12 preseason poll, has been a pleasant surprise this year. Currently they are right on the outside looking in at the bubble, but just about no one thought they would be in this position entering the season. Last month, I received an email from Arizona State's assistant coach Eric Musselman. In the email, he told me to check out Carrick Felix's "amazing" defense this season for the Sun Devils. Since then, he has also been quoted on the same topic in this article. Musselman said of Felix, "He’s got to be one of the top five defenders in all of college basketball." Naturally, I decided to try and quantify Felix's defense to dig deeper.

To look at Felix's defense, I decided to just look at Pac-12 games. Generally, ASU has used Felix to guard a top scorer. Felix's versatility is a tremendous advantage here, as he has guarded point guards, shooting guards, small forwards, and power forwards. I wanted to find conference games where Felix guarded just one player for a full game. Then, I could compare the player he guarded's game stats to season averages to get the "Felix Effect". I realize that this method has some limitations. First, the goal of defense is not solely to stop your man. Instead, teams tend to have a defensive philosophy rooted in help principles. Also, there are many circumstances where players stop guarding their assignment over the course of a game. The two most common are transition plays (where the primary goal is to stop the ball) and switches due to screens. Regardless, I identified nine conference games where I determined that Felix primarily guarded one man for nearly (if not all) of the game. The following is a graph of these nine instances. The head of the player Felix guarded represents that player's season ORtg, while Felix's head represents that player's game ORtg. When Felix's head is higher, it means he was "bad" on defense. When Felix's head is lower, it means he was "good" on defense.

 

As you can see, Felix started the year out with two great games against Andre Roberson (Colorado) and E.J. Singler (Oregon). The only player to significantly get the best of him in conference play has been Mike Ladd of Washington State. In total, Felix has held six under their average ORtg and three over their average ORtg.

The above table shows Felix's defense in more detail. Negative numbers are a good thing from Felix's perspective (hence the green formatting). On average, Felix has lowered a player's offensive rating by about seven points per 100 possessions. We can also see that although Ladd was very efficient in his game against Arizona State, his usage was lower than normal. A defender's ability to affect three point percentage has been heavily scrutinized, so we should probably take those percentages with a grain of salt. However, I fully agree with the numbers concerning free throw attempts. I thought Felix did a great job of not trying to do too much on defense and avoiding fouls. The numbers do say that Felix has had a tendency of not letting players get to the line as much as they are used to.

I wanted to take a look at Victor Oladipo, who is regarded by many as the best defender in the country. Tom Crean's usage of zone defense, however, complicated matters. I was only able to identify five conference games where Oladipo spent the vast majority of his time on one offensive player. Those games are below:

When watching film, it's easy to tell the difference in defensive style between Felix and Oladipo. The latter is very agressive, ranking 20th in the country in steal percentage and averaging 3.6 fouls per 40 minutes. it's hard to really take anything from this small of a sample size, but I was surprised that offensive players have gone at Oladipo. Ryan Evans was the only player who was used on offense less than normal against Indiana. 

It's no secret that defensive statistics are far behind offensive statistics. One of the biggest talking points at the  MIT Sloan Sports Analytics Conference last weekend was the use of new technology to better measure defense. This is especially true for the college game, where we don't have much beyond blocks and steals. I will be the first to say that the best way to judge a player's defense is to watch film. Clearly, Felix's defensive prowess is easily spotted by watching Arizona State play. My goal was to back up the film with numbers. Although the method has some flaws, I think combined with the eye it can give a better total picture of a player's defensive performance.

Bucknell and Turnovers

There has been a lot of talk all year long about VCU's havoc defense. The type of defense Shaka Smart's team plays is exciting to watch and pretty effective. Currently, VCU is 30th in the country in AdjD.  Bucknell is a team with an equally unique defense, but not even close to the same media attention.

Dave Paulsen's Bucknell squad currently sits at 22-5 and is coming off of a big road victory at Lehigh. The team is led by senior big man Mike Muscala and is ranked 50th in the country in AdjD. They have accomplished this by being the "anti-VCU". Bucknell does the fantasy sports equivalent of "punting" a category on defense. They don't look to create turnovers on defense at all, instead they focus on contesting shot attempts and keeping opponents off the offensive glass. Bucknell ranks number nine in the nation in opponent's eFG%, number two in the nation in opponent's in defensive rebounding, and number 345 in the nation in forcing turnovers. 

To make matters more interesting, the Bison also don't turn the ball over themselves (on offense). If you don't like watching teams turn the ball over, Bucknell games are the ones for you. If you think about this strategy a little deeper, it's a very odd concept. On offense, Paulsen stresses not turning the ball over and not crashing the glass (presumably to focus on getting back on defense). On defense, Paulsen forces his opponents to use the same exact strategy he uses! If Paulsen believes taking care of the ball and getting back on defense is the best way to play basketball, why does he enable his opponent to do exactly that? The answer here is probably that he believes that Bucknell can play Bucknell basketball better than their opponents play Bucknell basketball. Confusing, I know.

For fun, I added offensive TO% and defensive TO% together for every team this season. As I figured, Bucknell came out on top (the lowest total):

Basic logic says that the total (Off TO% + Def TO%) should have no correlation to winning/efficiency. A low total means your TO% is good on offense, but bad on defense. A high total means your TO% is bad on offense, but good on defense.  These should cancel each other out either way. However, the previous table shows that there are some pretty solid teams with low totals. To compare, the table below shows the bottom 10 of the table (their games consist of many turnovers):

VCU barely makes it on the list, but overall these teams are definitely weaker than the first list. I wondered if there was anything to this finding, so I added five more years of data and found the correlation between  Total TO% and Efficiency (AdjO-AdjD). I got an r-value of -.33, meaning there is a small negative correlation between Total TO% and Efficiency. In basketball terms, this means that teams who don't force turnovers but don't turn the ball over themselves tend to be better than teams who do force turnovers but also turn the ball over themselves.

Here's the top 10 Bucknell-esque teams for 2008-2013. Notre Dame and Mike Brey dominate this list and of course 2013 Bucknell is right there with them:

The Effects of Offense on Defense

Last month, I looked at the effect of Louisville's offense on its defense. When a Louisville offensive possession ends, they get to set up their press. Setting up their defense makes it dramatically more difficult for opponents to score. Both field percentage and turnover percentage are influenced by the Louisville press.

The one and done nature of the NCAA Tournament does not allow for teams to have an off night. Poor shooting can knock a heavily favored team out for good. A poor shooting night is fairly difficult to control because it happens to all teams at some point. Going back to the Louisville example, a team is going to be even more vulnerable to an upset if their bad shooting also affects their defense.

I looked at the 10 teams with the best NCAA Championship odds according to Vegas Insider (note: the odds were made before the Michigan-Michigan State game). I then took these 10 teams and compared their opponent's shooting efficiency when they make a shot leading to the defensive possessions versus when they don't. This data comes from hoop-math.com:

As you can see, Indiana and Louisville's defenses are most negatively influenced by missing shots. This does not account for the extra turnovers caused by the Louisville set defense, so Louisville is probably more dependent on making shots than Indiana. On the flip side, Michigan and Arizona's defenses hardly change regardless of their previous offensive possession. Defense is not quite Michigan's specialty (41st in AdjD), but Arizona is definitely respectable (23rd in AdjD). Thus, Arizona may be less susceptible to a bad shooting night because of strong "transition" defense than other championship contenders. I'll attempt to take a closer look at this in the near future.

Defending the Free Throw

Recently, there has been a lot of talk about foul shooting and luck. The discussion has been about the luck the shooter has during a foul shot. This is very controversial, because we as humans like to believe we are in full control  over everything. However, I don't think anyone would dispute the luck involved in foul shooting for the "defense". Using the word defense for a FREE throw by definition doesn't make sense. The defense simply watches while the opposition shoots.

St. Mary's is 11-3 this year, most recently with a comeback win over Harvard at home. They have shot the ball extremely well this season (4th in eFG%), but have also let their opponent's shoot well. The Gaels are 326th in defensive 3P% and 320th in defensive FT%. There has been much talk about opponent's 3P% being misleading and a lottery, but the same obviously goes for FT%. 

The following are graph of St. Mary's 13 D1 games this season. The graphs plots their opponent's 3P% and FT% in the game against St. Mary's relative to their season averages (average % - St. Mary's game %). Basically, if a data point is above the x-axis that means the Gaels were lucky in their game and if a data point is below the x-axis that means the Gaels were unlucky.

St. Mary's luck (or lack thereof) has very likely just been due to random variation. I would bet that their defense will improve by the end of the season simply from regression to the mean. Still, I came up with three ideas (I'm sure there are more) that would possibly affect opponent's FT%:

1) Tempo/Fatigue - It's possible a team could play at a level of speed or physicality high enough to influence their opponent's ability to shoot. 

2) Location/Game Environment - Crowd, travel, familiarity, etc. could all lead to bad shooting.

3) Player Being Fouled - Guards generally shoot better than big guys. If a defense had guards who were foul-prone, it's safe to say teams would shoot better from the line.

Next Up: Teams expected to gain from unlucky shooting

Butler's Winning Blueprint

Going into last Saturday's Butler-Indiana game, the question was how would Butler's shaky defense stop quite possibly the best offense in the country. Indiana scored 1.13 points per possession, a more than respectable number but still their 3rd lowest output of the season. The gameplan for Brad Stevens was pretty  obvious and discussed all over Twitter: let Freshman guard Yogi Ferrell take long jumpers. On the season, Ferrell is 35% from 2 and 25% from 3.

Stevens chose to put the stellar defender Roosevelt Jones on Yogi Ferrell. If the gameplan was to let Ferrell shoot, then Butler conceivably could have put someone like Rotnei Clarke on Farrell, saving Jones for a more efficient offensive player. However, Stevens purposefully put Jones on Ferrell  in order to more effectively stop the Ferrell-Zeller pick and roll. The video below of the opening play demonstrates this:  

Butler chose to switch screens and use Roosevelt Jones' versatility. Although only 6'4", Jones is a very good rebounder for his height and kept a body on Zeller at all times. Meanwhile, Ferrell felt compelled to go at the bigger/slower Andrew Smith. Smith did a solid job of keeping Ferrell in front of him while still baiting him to take shots. Of course, it should be noted Jones and Smith both fouling out can probably be attributed to at times playing defensively out of position. The results?

Yogi Ferrell: 3-9 from two, 2-4 from three, 6 turnovers, used on 30% of Indiana possessions (team high)

Cody Zeller: 4-9 from two, 0-0 from three, 2 offensive rebounds, used on 21% of Indiana possessions (4th highest)