A look at assisted-on data
03.30.12
In today’s fast-paced society, it can be difficult to carve out time to break down video on your favorite team’s next opponent. One way to cheat the system and get a rough feel for offensive tendencies is to look at ‘assisted-on’ data, which indicates how many of a player’s made shots were assisted. Does a player primarily score off the pass or the dribble (or put-backs)? Does this change depending on where a player shoots? This kind of information can be derived from play-by-play data and I’ve done that for each team currently in New Orleans. The data below is in the from of assisted baskets/field goals made and there are a few interesting nuggets to be mined from reviewing this sort of data.
Ohio State
Name 2Pt(Short) 2Pt(Long) 3-Pointers J Sullinger 67/116 .578 31/91 .341 14/16 .875 W Buford 31/59 .525 35/81 .432 46/59 .780 D Thomas 59/99 .596 40/92 .435 48/48 1.000 A Craft 8/58 .138 2/32 .062 14/21 .667 L Smith 18/39 .462 1/18 .056 27/29 .931 A Williams 12/16 .750 0/3 .000 0/0 .000 S Thompson 19/22 .864 6/11 .545 1/1 1.000 E Ravenel 24/31 .774 10/15 .667 0/0 .000
You’ll see in the data that almost every non-point guard is assisted on over 90% of their made three-pointers. (Notice Deshaun Thomas hasn’t had a single unassisted three-pointer this season.) This makes William Buford’s 78% assist rate on threes unusual. Also, Buford has made 81 long 2’s compared to 59 short 2’s. He’s the Buckeyes mid-range guy. So cut Buford some slack when talking about his shooting struggles, because he was never going to make a high percentage of 2’s given his role. And making “only” 36% of his threes this season isn’t bad at all considering how many shots he takes off the dribble.
Kansas
Name 2Pt(Short) 2Pt(Long) 3-Pointers T Robinson 100/163 .613 35/73 .479 7/7 1.000 T Taylor 29/85 .341 5/71 .070 38/56 .679 J Withey 63/79 .797 18/28 .643 0/0 .000 E Johnson 22/48 .458 5/20 .250 58/63 .921 T Releford 33/61 .541 8/28 .286 23/24 .958 K Young 22/33 .667 8/10 .800 3/3 1.000 C Teahan 2/10 .200 3/7 .429 45/46 .978
Tyshawn Taylor has been assisted on “only” 68% of his made threes. That’s actually the second-lowest figure (to Aaron Craft - who takes far fewer threes) of any regular still playing. Basically, he’s the most likely player to make a three off the dribble which is unusual considering that 34% of his short 2’s are assisted – a high figure for a point guard. Down low, put-backs are not Jeff Withey’s specialty. He is assisted on short 2’s like few other post players.
Louisville
Name 2Pt(Short) 2Pt(Long) 3-Pointers C Behanan 63/107 .589 9/29 .310 6/6 1.000 G Dieng 64/88 .727 20/52 .385 1/1 1.000 P Siva 14/75 .187 3/26 .115 14/16 .875 K Kuric 38/53 .717 12/34 .353 70/75 .933 C Smith 23/39 .590 1/14 .071 56/66 .848 R Smith 26/63 .413 6/41 .146 37/41 .902 J Swopshire 14/26 .538 7/14 .500 5/5 1.000
We have to use some caution when comparing shot selection across teams because one scorekeepers’s 2-pt jumper is another’s lay-up. Within-team comparisons are fair game, though, and this is something I wouldn’t have known before looking at the data – Gorgui Dieng, Louisville’s 6-10 rim protector, is much more likely to take a mid-range shot than Chane Behanan. Attempts aren’t shown here, but Dieng has attempted over twice as many long twos as Behanan this season. Dieng has played more minutes, but not enough to explain that large of a difference, which is made more unusual considering Behanan has taken 34 3’s to Dieng’s two. Statistically, Dieng is not a particularly gifted offensive rebounder, but part of that is because he’s not near the hoop as much as the smaller Behanan.
Kentucky
Name 2Pt(Short) 2Pt(Long) 3-Pointers T Jones 52/118 .441 4/36 .111 15/16 .938 A Davis 91/148 .615 22/51 .431 3/3 1.000 M Kidd-Gilchrist 43/93 .462 14/46 .304 12/12 1.000 M Teague 10/82 .122 2/30 .067 21/24 .875 D Lamb 20/48 .417 10/43 .233 71/73 .973 D Miller 9/34 .265 7/49 .143 47/54 .870 K Wiltjer 7/15 .467 9/20 .450 34/34 1.000 E Vargas 3/6 .500 3/6 .500 0/0 .000
It’s not surprising to see that Marquis Teague and Darius Miller are both rarely assisted on mid-range shots. As the Wildcats’ primary ballhandlers, they’re the ones giving out assists rather than receiving them. But oddly, Terrence Jones also has point guard like assisted-on numbers from mid-range. Not coincidentally, he’s also a particularly poor mid-range shooter, making just 28% of his shots this season. By the way, I’ve been struck by the tough two’s Miller has made in the tournament, and season-long data bears out that he’s one of the best mid-range shooters left. He’s made 49% of his long 2’s, far and away the best on the team and second only to Deshaun Thomas (51%) among Final Four participants that have taken at least 80 mid-range shots this season. Note here that making half of your mid-range shots is a very difficult goal to achieve.
The untrained eye: Mercer vs. Utah State
03.28.12
Mercer beat Utah State 70-67 in a 66-possession game Wednesday night. I was there. This is what I saw. (Really, this is heavier on the random thoughts than game recap.)
Travel and Altitude Redux
There’s nothing like travel and altitude to enhance one’s road struggles. So serious credit goes to Mercer for overcoming a 2000-mile trip from Macon, Georgia (elevation 400’) to Logan, Utah (elevation 4500’) in addition to the lively crowd. Mercer built an early lead and had to deal with the customary home-team run after halftime. Late in the second half, Utah State scored on eight consecutive possessions to turn a 48-41 deficit into a 55-49 lead. There were no weary legs here, though, as Mercer responded by scoring on the game’s last ten possessions – going 4-of-4 from the field and 10-of-11 from the free throw line - to pull off the victory.
Atlantic Sun = CAA (almost)
The CIT title game provided a reminder that the A-Sun was really good this year. From 2006 to 2008 the league was ranked 29th, 29th, and 28th, respectively, out of 31 conferences. Mercer’s win last night pushed the league into 14th this season, looking down on the Horizon and MAC, and within arms length of the CAA. Belmont heads to the Ohio Valley next season, so this may be the heyday for the A-Sun. While we’re here, let’s give it up for USC Upstate. I had them at 286 in the preseason and they finished 131, going 21-13 including narrow defeats on the road against South Carolina and Dayton, and the memorable home win against Belmont where they reversed a 16-point halftime deficit in front of a near-sellout crowd of 781. I have my eye on you, Eddie Payne.
That’s a lot of home games
Utah State played its 22nd game at the Dee Glen Smith Spectrum last night. Since 2000, only Memphis in ‘04-‘05 played more games (23) in one building. The Tigers had the benefit of playing their conference tournament at home that season and played four games in it before losing in infamous fashion in the title game. That sent them to the NIT where they were rewarded with three more home games. Footnote 1: Oregon played 24 home games last season, but those were split across two arenas. Footnote 2: The Aggies’ five home losses were as many as in the previous seven seasons combined.
Score another one for pre-season ratings
03.25.12
If you’re into the twitter scene like I am, you’ve noticed Gary Parrish tweeting after each round where the remaining teams were ranked in his pre-season top 25 (and one). That got me to thinking about the old issue of the pre-season poll versus the final poll. It’s been another good year for pre-season polls. The AP version had the Final Four teams ranked 2, 3, 9, and 13. (Is this really that good? I don’t know.) As you might suspect, after a full season’s worth of data, the voters were arguably worse, ranking the eventual Final Four teams at 1, 6, 7, and 17 in the pre-tournament poll.
I’m not here to bash the AP voters for their late-season work. I’ve done that before and I hate repeating myself. I’m really here to support pre-season ratings. Because even in my system which should know better, the Final Four teams were more highly rated before the season than in the ratings posted on Selection Sunday.
The remaining four teams were ranked 1, 2, 8, and 11 before any games were played. It’s better but not appreciably different than the AP poll, which I actually have great respect for in the pre-season. (However, Crazy Uncle takes a bow for having Kentucky and Ohio State one and two, respectively, in the pre-season. According to pollspeak.com, no AP voter had these as their top two in either order. It’s unfathomable to me that not a single voter had Kentucky as their number one. Attention future voters: A little diversity of opinion isn’t a bad thing. Channel your inner Scott Mansch before next season. The poll will be better off for it.)
My pre-tournament ratings had the teams ranked 1, 2, 4, and 20. I’m not sure if that’s better than the pre-season or not, but obviously it was worse for Louisville who dropped from 8th to 20th over the course of the season. And looking at the Elite Eight, Florida was 12th in the pre-season and 19th entering the tournament. Getting beyond the tedious manual bookkeeping, I thought it would be interesting to see how the pre-season ratings stacked up with the pre-tournament ratings when filling out a bracket. Let’s compare!
Correct picks for each round
Pre-season Pre-tourney R32 21/32 22/32 R16 9/16 9/16 E8 7/8 5/8 F4 3/4 3/4 Title UK over OSU UK over OSU*
The pre-season ratings win! This is partly due to good fortune in the way the bracket was set-up. In the West region, the highest-rated teams in the pre-season were Louisville (8th) and Florida (12th). The top two seeds in that region were surprising Michigan State (24th) and Missouri (14th). This would have forced you to pick a Louisville and Florida regional final which seemed unlikely on March 12th but would have worked out for you. (It’s worth mentioning here that Michigan State continued the curse of the pre-season-unranked one-seeds.) In addition to those two, the pre-season ratings would have had Syracuse over Wisconsin, while the pre-tourney ratings correctly had Baylor instead of Duke in the Elite 8.
The only Final Four team missed by the pre-season ratings was Kansas. The Jayhawks may still have beat the Tar Heels with a healthy Kendall Marshall, but if that was your only Final Four miss, you’d have to feel good about your prognosticating given the Tar Heels’ unforeseeable lineup change.
I have to think that this is a rare occurrence. I hope it’s rare, anyway. It’s deflating to think a person could have tucked away an ordered list of teams in November, not watched a single game, filled out a bracket in March based on that list, and be on the verge of winning their pool on the eve of the Final Four. However, consider that if UConn had been the 9-seed in the West instead of the South, the pre-season ratings would have had them in the Final Four instead of Louisville. And if we looked at the average prediction error of actual tournament games using the two systems, I suspect we’d find that the final ratings did better. However, it’s probably not that unusual for the pre-season ratings to be competitive.
Let me make this clear: Do not use pre-season ratings to fill out your bracket in the future. That is not the point of this analysis. The point really is that 30-35 games are not enough to get a true measure of a team. The second-most common complaint about my system is that the pre-season ratings have too much influence for too long. All influence is removed on the third weekend in January, which seems to be far too late for most people’s tastes, but I’ve suspected that it would make the ratings better if I left the influence in even longer. (This suspicion has been supported by Nate Silver, whose bracket-forecast model includes the pre-season poll as a predictor.)
The only reason I haven’t done this is because I haven’t systematically investigated it. However, given what we’ve seen this March, this deserves a closer look. If the pre-season ratings make the system better in February and March, it would be irresponsible not to include them in the ratings mix to some degree for the entire season.
*The asterisk on the title game prediction from the pre-tourney ratings is because Ohio State actually leap-frogged Kentucky before Thursday’s round of 64 games based on NIT results. If you waited to do your bracket on Wednesday or Thursday, you would have had Ohio State as the champ based on the ratings.