Conference Differentials, Part 11/02/25

NCAA -- 11 to Go?...
16 weeks into the season and the conference still has eight teams in the Top 25. Consider that in all 10 different Big East teams have been ranked over the course of the season, with at least three ranked every week so far. Eleven teams may be a stretch, but conditions are in place for the conference to break it's previous "most teams in the NCAA" record, eight, from 2006...
1. 15 of the conference's 16 teams entered conference play with winning records & strong RPIs.
2. 11 teams have established winning conference records (not an absolute predictor of an NCAA bid, but a necessary prerequisite) through week 16.
3. The bottom five teams have absorbed a lion's share of the losses handed out this season, while (Pittsburgh aside) the other 10 winning teams have traded punches and taken hits, mostly (but not exclusively) from each other. Only a few of those 11 teams (counting Pitt in this group) have ugly losses, and even those are not to the lowest two teams in the conference, DePaul and South Florida. 10 of the 11 teams are ranked #35 or higher in the RPI of 2/24, with Marquette number 11 on the list, ranked #52 (as of 2/24). But entirely in keeping with the tenor of the season, the Warriors hammered Connecticut 74-67, in Hartford, to bring their record to 8-7, virtually guaranteeing themselves a 0.500 record (or better) going into the Big East Conference Tournament next month. UConn is also 8-7 and also looking at a 0.500 record (or better) to finish out conference play.

	Record			Eff.	Pythag.
Team	W	L	Pct.	Diff.	Win %
Pittsburgh	13	2	0.867	0.146	0.833
Villanova	9	6	0.600	0.065	0.670
Marquette	8	7	0.533	0.057	0.647
Louisville	10	5	0.667	0.056	0.655
Notre Dame	11	4	0.733	0.052	0.634
Syracuse	10	6	0.625	0.050	0.636
Cincinnati	9	6	0.600	0.034	0.597
West Virginia	8	7	0.533	0.030	0.583
Georgetown	10	6	0.625	0.018	0.551
St. John's	10	5	0.667	0.010	0.529
Connecticut	8	7	0.533	-0.003	0.493
Seton Hall	5	10	0.333	-0.048	0.360
Providence	3	12	0.200	-0.076	0.305
Rutgers	4	11	0.267	-0.079	0.295
South Florida	2	13	0.133	-0.120	0.206
DePaul	1	14	0.067	-0.197	0.103
Average					0.506

Sorted by net efficiency and including results through Thursday night's games, the "great divide" between the top 11 and bottom five is distinct. Five teams -- Villanova, Marquette, Louisville, Notre Dame and Syracuse share a tier, separated by a 0.015 difference in efficiency net. The next tier contains Cincinnati and West Virginia, with Georgetown and a surging St. John's close behind. Connecticut maybe underwater this week, but given the volatility in the conference race, could easily be back on the plus side of the net efficiency next week. Pitt and DePaul, outliers from virtually week 1 of conference play, have been joined by South Florida, as the Bulls settle into a niche at the bottom, just above the Demons. The 0.045 separation between UConn and Seton Hall is almost as large as the one that separates Pitt from Nova, and Rutgers from USF.

About Marquette & Villanova
Those two schools have had their struggles in conference play, yet have net efficiencies and Pythagorean Winning Percentages fairly inconsistent with their conference records. Pythagoras "says" each should have an additional win. The paradox is resolved when considering the winning and losing margins for 20+ games (apiece) the two have logged since January. The Golden Eagles' average winning margin is 11, while their average losing margin is -6.9. They have two wins by more than 15 points, and only one loss by more than 10. The Wildcats' 9 wins have been by an average of 10 points, while their six losses have been by an average of -4.8. Only a single loss (Providence) has been by more than 10 points. And yet the Wildcats may well be one of the eight teams who opens the Big East Tournament on Tuesday. Such is the Big East this season.

So How Many?...
I have to fight the urge towards over optimism, but certainly nine at this point is realistic...if conservative. Eleven teams have pretty much done what the NCAA has asked -- they have scheduled out of conference games away from home, limited the number of cupcakes (RPI ranks > 200, for example) and won against top 100/50 competition. It will be crucial, this season even more than most, for the Big East teams at the lower end of the S-curve to win their first round BET games and finish Championship week with a record no worse than 1-1. Watch how the bubble and at-large lock teams in the lower ranked conferences fare during their conference tournaments. Upset conference champions tend to limit BCS conference bubble teams. If favored teams prevail in the #6 - #10 ranked conferences during tournament week, then 10 or 11 is very possible.

Big East 2007-08 -- Inside/Outside

Can the inside/outside formula be effective for identifying a team's playing style and offense? And which is more effective at expressing that style? I applied both Pomeroy's & Pelton's variations to the teams of the Big East conference...

					Rating		Rank
Team	Min	FGA	3FGA	FTA	KPom	KPelt	KPom	KPelt
Connecticut	6650	1880	465	905	23.40	6.62	1	1
Syracuse	7025	2071	558	870	15.07	4.44	2	2
South Florida	6225	1705	504	734	13.49	3.69	3	3
St. John's	6025	1625	472	569	5.97	1.61	4	4
Marquette	7050	2082	697	794	4.66	1.38	5	5
Pittsburgh	7450	2185	671	768	4.44	1.30	6	6
Villanova	7000	2013	703	783	3.97	1.14	7	7
Rutgers	6250	1721	538	597	3.43	0.94	8	8
Seton Hall	6525	2006	677	736	2.94	0.90	9	9
West Virginia	7500	2169	743	782	1.80	0.52	10	10
Notre Dame	6625	2015	677	687	0.50	0.15	11	11
Louisville	7225	2011	778	734	-2.19	-0.61	12	12
Providence	6275	1802	631	582	-2.72	-0.78	13	13
Cincinnati	6450	1783	635	585	-2.80	-0.78	14	13
DePaul	6025	1827	645	562	-4.54	-1.38	15	15
Georgetown	6850	1744	701	593	-6.19	-1.58	16	16

The formulas produce identical rankings, though the actual values vary in magnitude. Hardly surprising. The rankings look "about right" -- that is, Connecticut, a team with a reputation for inside play produces the highest "inside" value, and it clearly relies more on inside play (and does it rather better than the other "inside-oriented" Big East teams) than other Big East teams. And that consistent with most analysis of Connecticut's style of play. And Georgetown as the "most outside" team in the conference (but not too outside) also seems consistent with the consensus of Georgetown's play and style.

I was surprised less by where Villanova came in from the calculations. I believe, from tracking the Wildcat's front court players over the past 4 seasons, that the staff has made more of an effort to get the ball to players in the paint for "better" scoring opportunities. I will post the results for the seasons 2004-05 through 2007-08 shortly.

Surprise, surprise...
If pressed I would have identified Notre Dame, or possibly Seton Hall as the "next most" outside team(s) in the Big East. Neither was anywhere near Georgetown. The Fighting Irish were "nearly neutral", if one where to assume that a rating of 0.0 suggests the team favors neither inside nor outside play. That outside shooting does not predominate in the Irish attack is a tribute to the roles played by Luke Harangody and Rob Kurz. Looking at 2008-09, will Zach Hillesland and/or Ryan Ayers provide the strong inside play characterized by Kurz? As for Seton Hall, mad bombers perhaps by reputation, Jamar Nutter and Jeremy Hazell did not dominate over Harvey, Gauss, Laing and Garcia. I knew that Syracuse's outside game would take a hit when Andy Rautins tore his ACL in August of 2007, followed by Devo's injury only two weeks into the season, but the computed score provides yet more proof that the Orange offense was too one dimensional for Big East play.

Notes & Observations...
1. Kentrell Gransberry has graduated and most likely taken most of South Florida's inside game with him. The Bull's Dominique Jones, Chris Howard and Jesus Verdejo return, but they are all back court/wing players. Gus Gilchrist's waiver application may be the most significant predictor for success this coming season.
2. Cincinnati's score was more puzzling than surprising. The Bearcats had, with a contingent of John Williamson, Adam Hrycanuik, Anthony McClain and Kenny Belton, an undeniable inside presence last season. So how did they end up with a -2.8 (Pomeroy) rating? Scoring guard Deonta Vaughn, who took (according to Ken Pomeroy's Cincinnati Scouting Report) nearly 28% of the team's shots when he was on the court, had an FTARate of about 31%, suggesting he did not get to the line "enough".
3. Optimism about Louisville's prospects may be well founded. The Cardinals rated at -2.19 (Pomeroy) last season lost only inside players -- David Padgett, Telo Palacios and Derrick Caracter. With a rookie front court next season, that outside tendency may become even more pronounced this season.
4. Those who remember the influence of Troutman, Taft, Aaron Gray and Levon Kendall may believe 4.44 (Pomeroy) may understate Pittsburgh's inside game. They forget that Jaime Dixon has very deliberately brought outside shooters like Keith Benjamin, Ron Ramon and Antonio Graves into the program and gave them the opportunity to shoot the ball.

2007-08 Inside According to Pomeroy & Pelton

Yesterday I listed the Big East's "most outside" players based on 2007-08 statistics (all games). I wanted to also look at the players from last season who showed the strongest tendency to play on the inside. Again I used the 2007-08 statistics for all games, and filtered for those players who logged at least 35% of the playing time at their position. I show the calculated results for both Ken Pomeroy and Kevin Pelton, but again I order the list according to Pelton's results.

Name	College	Min	Min%	FGA	3FGA	FTA	KPom	Pelton
Kentrell Gransberry	USF	953	76.5	354	1	220	61.9	23.0
Jeff Adrien	UConn	1115	83.8	345	4	229	65.2	20.2
Luke Harangody	NDU	959	72.4	518	9	198	36.5	19.7
Derrick Caracter	Ville	593	52.7	201	1	108	53.2	18.0
Hasheem Thabeet	UConn	1025	77.1	189	0	169	89.4	16.5
David Padgett	Ville	611	54.3	168	0	100	59.5	16.4
Paul Harris	Cuse	1264	90.0	343	34	237	59.2	16.1
Roy Hibbert	GTU	894	65.3	294	3	144	48.0	15.8
DeJuan Blair	Pitt	963	64.6	313	0	149	47.6	15.5
Arinze Onuaku	Cuse	1070	76.2	288	0	164	56.9	15.3
John Williamson	Nati	848	65.7	294	13	132	40.5	14.0
Joe Mazzulla	WVU	684	45.6	144	20	114	65.3	13.7
Joe Alexander	WVU	1137	75.8	474	41	194	32.3	13.5
Antonio Pena	Nova	678	48.4	183	6	96	49.2	13.3
Eugene Harvey	Hall	1176	90.1	331	47	192	43.8	12.3
John Garcia	Hall	642	49.2	144	0	74	51.4	11.5
Mac Koshwal	DPU	940	78.0	260	6	112	40.8	11.3
Dwight Burke	MU	412	42.2	53	0	46	86.8	11.2
Dante Cunningham	Nova	1050	75.0	261	0	116	44.4	11.0
Justin Burrell	Johns	946	78.5	294	1	98	33.0	10.3

As before, players higlighted in yellow were seniors or out of eligibility at the end of the 2007-08 season. Green highlighted players have transferred while blue highlighted players went to the NBA draft. While the list suggests that 14 of the 20 will return to Big East play this season, the paint players are more than "a bit" more stable than the "outsiders". After all, Caracter's departure was not entirely voluntary, and Alexander was a junior last season, not a freshman. Only Justin Burrell, Mac Koshwal and Antonio Pena are freshmen. And Pena is a redshirt freshman. As I reviewed the list I realized virtually all of the players were the same centers and power forwards I have written and talked about over the past several seasons (or in the case of Pena and Burrell, the past seasson and preseason). Except for Nunu Harvey and Joe Mazzulla, who as guards seem very out of place. Both took about 14% of their FGAs from the 3 point line, not quite typical for backcourt players, but Harvey, with an FTARate of 58.0 and Mazzulla, with an FTARate of 79.2(!) showed the front court player knack for converting field goal attempts into free throw opportunities. Both have FTARates more typical of aggressive front court players, a characteristic reminiscient of Kyle Lowry (Villanova) and Carl Krauser (Pittsburgh).

Distinction Without Difference?
When identifying outside players Pomeroy and Pelton seemed to arrive at about the same place by slightlymagnitude of the differences. Pelton's 3^rd ranked player (Notre Dame's Luke Harangody) is Pomeroy's 22^nd ranked player. Pelton's 8^th (Georgetown's Roy Hibbert) and 9^th (Pittsburgh's DeJuan Blair) ranked players are Pomeroy's 16^th and 17^th ranked players respectively. And Pomeroy's 3^rd (Marquette's Dwight Burke) is Pelton's 18^th. Oh, and Pomeroy's 1^st ranked player, Byron Joynes of Rutgers, is not listed in this post, because he is ranked 26^th by Pelton's method.

Notes & Observations...
1. For the second year running Syracuse's Paul Harris is on both Pelton's (#7) and Pomeroy's (#8) list. Like Harvey and Mazzulla he shows a better aptitude for inside rather than outside play, though technically he is described as a wing/back court player. Harris took about 9% of his FGAs as 3s.
2. With 20 players listed, only 2 schools, Rutgers and Providence, are absent players. The outside top 20 lacked only USF on the list.
3. Villanova has two players, Dante Cunningham and Antonio Pena on this list, another indication that the Wildcats offense has developed an inside presence. Drummond, with only 19 or so Min% of playing time at the center position, did not make field for consideration.

2007-08 Outside According to Pelton & Pomeroy

I wrote several posts in August of 2007 that identified Big East players as "inside" or "outside" players based on the difference between the number of their free throw attempts and their 3 point attempts, divided by (based on whether you value Kevin Pelton's or Ken Pomeroy's approach) their minutes played or the total of their field goal attempts. I looked at both inside and outside players in turn using the formulas developed by Ken Pomeroy, a stats guru who writes exclusively about college (D1) basketball and Kevin Pelton, a statistician who writes about pro (primarily the NBA) and international basketball. Ironically both analysts began writing (non collaboratively) for a startup website, The Basketball Prospectus last October.

This time I decided to look at outside, then inside players, juxtaposing Pomeroy's (values under the KPom column) and Pelton's (under the Pelton column below) calculation for easier comparison. The Big East's 20 highest rated "Outside" players, according to Pelton's formula (the more negative the number the greater the tendency to play wing and shoot 3s, the higher the rank), are listed below. I ranked only players who logged 35% or more of the playing available in their position.

Name	College	Min	Min%	FGA	3FGA	FTA	KPom	Pelton
Dan Fitzgerald	MU	428	43.9	102	87	13	-72.5	-17.3
Jeremy Hazell	SHU	874	67.0	331	234	93	-42.6	-16.1
Larry Wright	Johns	547	45.4	205	132	44	-42.9	-16.1
Jeff Xavier	PC	981	78.2	327	209	56	-46.8	-15.6
David Cubillan	MU	598	61.3	158	116	23	-58.9	-15.6
Kyle McAlarney	NDU	1178	88.9	383	245	68	-46.2	-15.0
Corey Stokes	VU	642	45.9	202	135	42	-46.0	-14.5
Alex Ruoff	WVU	1179	78.6	353	239	92	-41.6	-12.5
Brian McKenzie	PC	878	70.0	273	138	37	-37.0	-11.5
Andre McGee	Ville	732	65.1	184	132	49	-45.1	-11.3
Jamar Nutter	SHU	945	72.4	292	177	70	-36.6	-11.3
Deonta Vaughn	Nati	1069	82.9	408	244	128	-28.4	-10.9
Jon Wallace	GTU	985	71.9	251	159	58	-40.2	-10.3
Donte Greene	SU	1253	89.2	521	261	133	-24.6	-10.2
Dwain Williams	PC	656	52.3	190	118	51	-35.3	-10.2
Jesse Sapp	GTU	911	66.5	256	151	58	-36.3	-10.2
Ronald Ramon	Pitt	1174	78.8	260	180	62	-45.4	-10.1
Ryan Ayers	NDU	803	60.6	179	116	40	-42.5	-9.5
Jeron Griffin	RU	780	62.4	248	122	49	-29.4	-9.4
Dar Tucker	DPU	685	56.8	329	156	92	-19.5	-9.3

Seniors and players who have run through their eligibility are highlighted in yellow, transfers in olive green and Donte Greene (freshman to NBA draft) in blue. Thirteen of the 20 players are slated (as of early September) to return to play in 2008-09. Andy Rautins, a Syracuse wing guard ranked 1^st using both formulas in the 2006-07 season and sidelined by an ACL injury last season, will return to the Orange for 2008-09. Rautins should provide an outside dimension Coach Boeheim's team lacked last season. Those familiar with my posts in 2007 August, or who have followed Big East basketball over the past two seasons will no doubt recognize Dan Fitzgerald (Marquette), David Cubillian (Marquette), Brian McKenzie (Providence), Jamar Nutter (Seton Hall), Deonta Vaughn (Cincinnati) and Ron Ramon (Pittsburgh), all repeated appearances on either or both of Pelton's and Pomeroy's Top 10 Outside list from 2006-07 to appear on the 2007-08 list.

Observations & Notes...
1. Larry Wright, who ranked 2^nd on this list is the second Johnnies "Outside" player to transfer in the past two off seasons. Avery Patterson who ranked second on Pelton's list from the 2006-07 season transferred during the summer of 2007.
2. Pomeroy and Pelton calculations tend to find the same Outside players. Pelton's 7 highest ranked Big East players are also ranked among Pomeroy's first 10. Pelton and Pomeroy "agree" on eight of their first 10.
3. Kyle McAlarney of Notre Dame ranked at #6 (#4 by Pomeroy) is no surprise; Ryan Ayers, a small forward for the Irish ranked at #18 (#10 by Pomeroy) is. I always thought Ayers' shot selection was a bit more balanced.
4. Brian McKenzie (Providence) ranked in their top 10 by both Pelton and Pomeroy, Deonta Vaughn (Cincinnati) and David Cubillian (Marquette) have been ranked in two successive seasons. They will be juniors next season.
5. Villanova's own Corey Stokes was ranked #7 by Pelton and #5 by Pomeroy.

Statistics: Frequency vs Possessions

After I posted Ray's piece I took a look at the SEC Hoops: The Good. The Bad. The Dirty. Blog to see what those guys were up to. They organized data for the entire South East Conference -- teams and players -- and begun to publish a series of "minutes per..." statistics for individual SEC players. For convenience I will call these frequency stats, they suggest "how frequently" a particular player will perform some action (an FGA, an FTA, a foul, a steal, etc.) to distinguish them from per capita (per game) stats -- how frequently will a particular player/team perform a particular act/task over the course of a game, and possession-based stats. Ironically, all are refinements, an end product of some process that begins with the same grist -- the raw data produced by individuals and teams when they play the game. The differences however extend beyond simply the computations and organization, to what they might suggest about a player (or his team) and ultimately to how they can be employed for analysis of personal and team performance.

Consider the compilations of Minutes per Field Goal Attempt Ray produced in his latest Guest Post for the 2008 Villanova squad. The players making up the regular rotation were listed from most frequent shooter (rising sophomore Corey Fisher) to least frequent shooter (rising junior Reggie Redding). I know (using no more than a calculator...or a good estimate) that if he played an entire game Corey Stokes would have taken about 13 FGAs while Reggie Redding would have taken about 8. By comparing Corey Fisher to Scottie Reynolds, I would know that Fish would most likely take the shot (by a small margin...), but that putting both on the floor together would generate a whopping 30.5 FGAs over the course of a 40 minute game. Consider that Villanova averaged (ahhh -- a per capita stat...) 57.5 FGAs per game, the two would have accounted for 53% of the Wildcat's FGAs. What can that tell us about a line up that put both Fish and Reynolds on the floor simultaneously? I have reproduced Ray's table below, but added a third column of the Shot%, a possession-based stat that calculates the probability that a particular player will take the shot.

Player	MpFGA	Shot%
Corey Fisher	2.46	27.5
Malcolm Grant	2.74	22.4
Scottie Reynolds	2.81	24.3
Corey Stokes	2.94	21.9
Casiem Drummond	3.39	20.5
Antonio Pena	3.68	18.8
Dwayne Anderson	4.40	16.0
Shane Clark	4.47	17.6
Dante Cunningham	4.77	17.3
Reggie Redding	5.13	13.3

Shot% and MpFGA do appear to "track", but there is not an exact correlation. If I add Fisher's and Reynold's Shot% I get 51.8, very close to the 40 minute, per capita calculation I did earlier. I can tell by looking at Shot% that a four guard lineup with Drummond in the middle would have been very problematic for the team (the sum of the Shot% for Fisher, Grant, Reynolds, Stokes and Drummond is 116.6 -- the team would have needed two basketballs to maintain everyone's shot rate. The relationship between MpFGA and Shot% is less obvious when I compared the Big East's Top 10 Scorers:

Rnk	Player	School	MpFGA	Shot%
1.	L. Harangody	Notre Dame	1.79	35.6
2.	S. Young	Pittsburgh	2.28	29.0
3.	D. Jones	South Florida	2.63	25.5
4.	B. Laing	Seton Hall	2.72	25.4
5.	D. Vaughn	Cincinnati	2.58	27.6
6.	J. Flynn	Syracuse	2.80	22.7
7.	K. Gransberry	South Florida	2.76	27.3
8.	D. Green	Syracuse	2.36	28.2
9.	D. Burns	DePaul	2.33	29.5
10.	A.J. Price	UConn	2.68	24.4

"Luke Harangody takes a lot of shots" was my first thought when I saw Ray's numbers, putting his MpFGA up against his Shot%, and I have a very good idea of how significant Harangody's role is with respect to Notre Dame's offense. His 35.6% by the way, earned Harangody a #6 ranking overall in D1 according to Pomeroy's Notre Dame Scouting Report. And "Luke Harangody takes a lot of shots relative to his teammates" was my first thought when I saw Harangody's Shot%. Each statistic (MpFGA and Shot%) suggest something about an individual player's tendency to hoist shots (attempt field goals), but MpFGA measures that tendency against time, while Shot% measures it against the other players on the court (at the time the player is shooting...). Which explains why any correlation between an individual's MpFGA and Shot% breaks down with respect to the players in the Top Ten list. How can Jonny Flynn and Kentrall Gransberry, shooting at about the same frequency (2.20 vs 2.76) have a nearly 5% "gap" in their respective Shot% (22.7 vs 27.3)? The answer is the number of possessions (and by implication, shots) the team each plays on typically gets in a game. South Florida had about 67 possessions per game (according to Pomeroy's South Florida Scout Page), while Syracuse (per Pomeroy) had nearly 73.

That each of the Top Ten Scorers should be very efficient offensively is a given (he would not have been allowed to function in the role without demonstrating efficient scoring...), and the table below (same as the one above, just added the player's eFG% & ORtg to the other numbers...):

Rnk	Player	School	MpFGA	Shot%	eFG%	ORtg
1.	L. Harangody	Notre Dame	1.79	35.6	57.1	114.9
2.	S. Young	Pittsburgh	2.28	29.0	54.7	110.1
3.	D. Jones	South Florida	2.63	25.5	53.9	112.2
4.	B. Laing	Seton Hall	2.72	25.4	49.4	106.6
5.	D. Vaughn	Cincinnati	2.58	27.6	55.5	109.5
6.	J. Flynn	Syracuse	2.80	22.7	52.6	112.9
7.	K. Gransberry	South Florida	2.76	27.3	52.8	102.6
8.	D. Green	Syracuse	2.36	28.2	50.5	105.4
9.	D. Burns	DePaul	2.33	29.5	48.6	107.6
10.	A.J. Price	UConn	2.68	24.4	50.8	114.4

Notice that while all of the players listed were indeed efficient shooters (eFG%s nearly 50.0 or better) but all also efficiently generated points for their respective teams (ORtgs > 100). It is no coincidence that all but one of the players who had ORtgs > 110 played on teams that played in a post season tournament (NIT/NCAA). When we look at those same numbers for last season's Wildcat squad what can we learn?

Player	MpFGA	Shot%	eFG%	ORtg
Corey Fisher	2.46	27.5	43.3	94.1
Malcolm Grant	2.74	22.4	53.4	113.2
Scottie Reynolds	2.81	24.3	51.1	105.6
Corey Stokes	2.94	21.9	47.5	101.8
Casiem Drummond	3.39	20.5	52.4	104.4
Antonio Pena	3.68	18.8	46.5	95.4
Dwayne Anderson	4.40	16.0	57.6	114.9
Shane Clark	4.47	17.6	48.3	111.1
Dante Cunningham	4.77	17.3	54.4	104.1
Reggie Redding	5.13	13.3	42.5	99.7

The keys to progress next season may well come down to improvements by the (then sophomores) Fisher, Stokes and Pena. Fisher will need better judgement on when to shoot (and cut back a bit...) and work on setting up teammates. Stokes and Pena will have to become better scorers. Each, along with Drummond, may not get as many opportunities to shoot, but they will have to score more efficiently when they have the ball.

Guest Post: Ray Floriani on Minutes per Field Goal Attempt

Fellow stats lover Ray Floriani, a writer for Hoopville, the Big East Report and Basketball Times, ran across this statistic in an SEC blog. He was kind enough to run the numbers for the Villanova team and compare them to some of the Big East scoring leaders. And share his thoughts with us.

By Ray Floriani
Hoopville
Big East Report
Basketball Times

SOUTH ORANGE, NJ Saw an item on an SEC blog that listed the conference leaders in field goals attempted. This figure did not take sheer FGAs but calculated a figure, minutes per field goal attempt, dividing minutes by FGA. The leader in the SEC this past season was Marcus Thornton of LSU at 2.1 (mins per FGA). Devan Downey (2.3) and Austin Steed (2.4) both of South Carolina, followed Thornton. Which tells us the Gamecocks may not have enjoyed a banner year, still, they had a few players who weren’t bashful when it came to launching shots.

Decided to do a distribution on Villanova based on 2008 Big East (regular season only). In addition the top ten conference scorers are listed by (scoring) order with their minutes per field goal attempt.

Villanova Minutes per FGA 2007-08

Player	MpFGA
Corey Fisher	2.46
Malcolm Grant	2.74
Scottie Reynolds	2.81
Corey Stokes	2.94
Antonio Pena	3.68
Dwayne Anderson	4.40
Shane Clark	4.47
Dante Cunningham	4.77
Reggie Redding	5.13

Big East Conference Minutes per FGA of Top Ten scorers 2008

Rnk	Player	School	MpFGA
1.	L. Harangody	Notre Dame	1.79
2.	S. Young	Pittsburgh	2.28
3.	D. Jones	South Florida	2.63
4.	B. Laing	Seton Hall	2.72
5.	D. Vaughn	Cincinnati	2.58
6.	J. Flynn	Syracuse	2.80
7.	K. Gransberry	South Florida	2.76
8.	D. Green	Syracuse	2.36
9.	D. Burns	DePaul	2.33
10.	A.J. Price	UConn	2.68

Notes:  No surprise that guards basically dominated the top of ‘Nova’s list. The stat does give some insight regarding field goal attempt distribution. In the ‘raw’ stats, Scottie Reynolds led the Wildcats with 199 FGA while Corey Fisher was second at 164. Applying the figures per minute you can see Fisher was the one who was more active when it came to shooting.

Luke Harangody would get what the SEC folks at ‘The Good. The Bad. The Dirty’, the ‘Ball-hog’ award. Not really, as the SEC blog points out not everyone at the top of the list is to be considered selfish and possessive of the basketball. In Harangody’s case, he’’s the farthest thing from it. The Notre Dame sensation clearly led the best of the Big East in scoring and did it while taking a shot just under every two minutes. Call that smart coaching by Mike Brey. You have a dominant low post presence you feed him.

Kentrell Gransberry of South Florida was in the top ten and my observation regarding Harangody applies to him also. South Florida (with Dominque Jones) had two players with lofty minutes per field goal ratings. Again, there weren’t a great deal of options for the Bulls.

Syracuse also had two players with high rates (a shot less than every three minutes). One has to believe the wealth would have been spread more if Eric Devendorf hadn’t gone down with a season ending injury.

The shot disparity seems small. But over a forty minute span it is significant. For instance a shot every two minutes (given a player goes the full contest) gives 20 FGA. Another player getting a look every four minutes with similar playing time attempts 10 shots. A significant difference.

Pace: The Beilein-McCullum Effect

I decided to track pace for all Division 1 programs for the 2007-08 season, much as I had done for the 2006-07 season. The source, as last it was for the 2006-07 season, was Ken Pomeroy's website, a terrific source for statistical data for all D1 teams. At the beginning of each of the past 2 or so seasons, Ken Pomeroy has written something like "...it looks like the pace may be higher this season...", this season it actually happened. The raw pace at the end of the 2006-07 season was 66.85, while this season the average pace for D1 was 67.09, a very modest increase of 0.24 possessions per game. I suppose if you consider there are nearly 5,000 games played in the season, that translates into about 1,250 additional possessions this past season. I plotted Pomeroy's efficiencies over the entire season to see the "shape" of the curve. I noted in a post last August that the 2006-07 chart showed a "hump" (a rise in the average possessions) during the middle of December, the product of seasonal invitational tournaments possibly. I looked for the hump this season and while not a prominent as last season (see the blue line on the chart below), it nevertheless appears again in late December. This time it appears to be due more to a "lessening in the rate of decline" of the average possessions, rather than an actual reversal in the trend of decline. Not as pronounced, it nevertheless disappears during the early conference play, right on schedule. From late December (early January?) the decline, though gentle, is clearly present and persistent through the end of the season. The end of season average raw pace for 2007-08, 67.09, reverses a three or four season trend, but does not quite match the pace from the 2005-06 season, 67.61. In truth I think the changes are largely at the edges, and most likely do not represent a long term trend...a 1 to 2 possession, year-over-year change would be a trend. The three year numbers suggest the college is settled in at (overall) a game in which both teams play for about 67 or so possessions over 40 minutes.

The mid-December hump aside, another interesting pattern is the gentle decline that settles in as conference play begins. This is another year-over-year fixture. The large pattern may be in place, but the devil is in the details. The causes, late season player fatigue, a familiarity with playing styles that leads to more deliberate approaches to game planning and strategy, etc. -- I have nothing more than anecdotal evidence and conjecture to offer at this point. If the reasons are not clear, the trend is persistent. There was a very small rise in pace at the very end of the 2007-08 season (March 23 to April 7), surprising given that at most only 20% of the D1 teams were still playing at that point (between single round eliminations in the NCAAs & NITs, and maybe the 4 or so teams playing out the CBI series?), a number I thought would be too small to move the average even the very small bump of 2/1000 of a possession.

When I compared the average pace for Big East conference teams with the average for all D1 teams, I got a surprise (at first). Comparing those averages for the past three season:

Average Pace
	2006	2007	2008
All D1	67.61	66.85	67.02
Big East	66.61	66.17	67.84

The 2007-08 season was the first (in a long while) since the Big East teams played for more possessions than D1 as a whole. When I considered the coaching changes during the last off season, the reason for the "faster" pace was obvious...though Georgetown's Princeton Offense is absolutely the most deliberate system used in the Big East, both John Beilein and Robert McCullum implemented systems that were notoriously deliberate. A comparison of the Mountaineers' and Bull's season-ending pace for the past three seasons shows the difference:

Raw Pace
	2006	2007	2008
South Florida	64.81	66.39	66.80
West Virginia	64.09	63.64	66.14
Arkansas	69.34	67.61	-----
Kansas State	-----	67.56	-----

Note the jump from the 2007 to the 2008 seasons, especially for West Virginia. I also included the pace for Arkansas (Stan Heath's last stop) and Kansas State (Bob Huggin's previous stop) for comparison. Both teams were above the D1 average for those respective seasons. While each team was below the D1 average, they were above (well above in West Virginia's case...) their previous season's average. Those Arkansas and K State pace stats suggest both the 'Eers and Bulls will "play faster" as Huggins and Heath fully install their systems with their own players.

Offensive and Defensive Ratings -- An Arial View

I wondered how the sixteen Big East teams compared with each other with respect to efficiencies -- offense and defense -- so I pulled down the schedule data from Ken Pomeroy's Basketball Prospectus Web Site to see if there was anything interesting to plot. I looked at just the conference games. The conference-wide offensive and defensive effiencies averaged out to 102.7 -- which I frankly thought might be high. That both offense and defense averaged to the same number however was "proof" that it was correct. Taking the "average" as 0,0 I subtracted the average from each team's offensive efficiency and then subtracted each team's defensive efficiency from the conference-wide average. That gave me points, relative to the conference-wide average, to plot for each team. Using this technique I was able to plot those teams with "above average" defenses above the X-Axis, and those with "above average" offenses to the right of the Y-Axis. Those teams with "above average" offensive and defensive efficiencies were grouped into the upper right hand quandrant.

The chart (above) confirms "knowns" rather than reveal "unknowns". Five of the teams grouped in the upper right quandrant, Georgetown, Louisville, Connecticut, Marquette and West Virginia, finished the regular season with five of the six best records in the conference. The chart confirms that Georgetown and Louisville, by consensus the two strongest teams in the conference, were, as confirmed by the scatter chart, clearly separated from the rest of the conference. Good things had been predicted for Syracuse (the sixth team in that quadrant), though the Orange finished the regular season riding the bubble, and after losing their first round game in the Big East Tournament to Villanova, finished the season with an NIT run. Having Notre Dame positioned below the 0,0 point on the Y-Axis might seem to undermine the chart's credibility, but consider that the "below average" efficiency identified here is defense. Notre Dame in the Mike Brey era is noted for both it's potent offense (best in the conference in 2006-07, but nearly as notorious for it's lack of defense. This season shows yet again that Notre Dame's offense is strong enough to mask the team's suspect defense. While strong offense (coupled with "just enough" defense) may be good enough to get by in the Big East, it may also explain the series of early NCAA exits the Irish have taken in the past 2 post seasons.

The mirror opposite quandrant (lower left) also seems to confirm what a consensus suspected. Three of the four teams in this quadrant finished among the bottom five. Rutgers and South Florida did not make the conference tournament. Providence barely had time to unpack before being sent home with a first round loss.

The data used for each team is below. For each team I have included a link to that team's "Game Plan" page over at Ken Pomeroy's web site. Notice that Villanova's ratings, offensive and defensive were nearly identical.

Team	ORtg	DRtg	X Axis	Y Axis
Cincinnati (8-10)	98.1	103.1	-4.6	-0.4
Connecticut (13-5)	110.8	102.0	8.1	0.7
DePaul (6-12)	104.6	111.3	1.9	-8.6
Georgetown (15-3)	104.5	93.1	1.8	9.6
Louisville (14-4)	105.9	91.4	3.2	11.3
Marquette (11-7)	106.1	98.8	3.4	4.0
Notre Dame (14-4)	110.1	103.6	7.4	-0.9
Pittsburgh (10-8)	109.2	104.7	6.5	-1.9
Providence (6-12)	102.7	108.6	-0.1	-5.9
Rutgers (3-15)	88.4	105.4	-14.3	-2.7
Seton Hall (7-11)	103.3	109.0	0.6	-6.3
St. John's (5-13)	90.1	102.2	-12.6	0.5
South Florida (3-15)	98.4	108.6	-4.3	-5.9
Syracuse (9-9)	103.7	102.0	0.9	0.7
Villanova (9-9)	100.3	100.2	-2.4	2.5
West Virginia (11-7)	107.4	99.6	4.7	3.1
Averages	102.7	102.7
Standard Deviations	6.45	5.46

A few observations...

1. While Villanova's defense was the focus of a good deal of criticism within the Nova Nation, the table demonstrates it was the team's stronger feature during the Big East season. A few defensive efforts like the games at Georgetown and St. John's and the homestands against Connecticut and Pittsburgh come to mind. The Wildcat's "nearly even" ratings (100.3 vs 100.2) provide a hint of the team's 0.500 record in conference play. The defense, while better than average for the conference was not on par with the performance of recent teams.
2. For the Big East this season, offense seemed to matter most. Note that St. John's, while playing slightly above average on defense, was significantly off on offfense. And their record (5-13) reflected that very big step back from last season.
3. Cincinnati, Syracuse and Villanova were the three teams whose points fell closest to the intersection of the X and Y Axis. Those three also finished with records within +/- 1 of 0.500.