Career Points in an Atlanta Dream Uniform

A recent post was made at the Atlanta Dream message board stating that Iziane Castro Marques has become the first player to score 1,000 points in an Atlanta Dream uniform. So I decided to check on that.

Here is the list of career points leaders while wearing an Atlanta Dream uniform...and congratulations, Izi!


Iziane Castro Marques 1015
Angel McCoughtry 743
Erika Desouza 699
Sancho Lyttle 669
Betty Lennox 595
Ivory Latta 534
Chamique Holdsclaw 348
Jennifer Lacy 285
Tamera Young 270
Katie Mattera 220
Michelle Snow 185
Shalee Lehning 157
Coco Miller 150
Alison Bales 133
Kristin Haynie 94
Kasha Terry 92
Stacey Lovelace 91
Armintie Price 87
Camille Little 62
Kelly Miller 59
Kristen Mann 45
Yelena Leuchanka 44
Ann Strother 39
Nikki Teasley 39
Chioma Nnamaka 16
Brittainey Raven 11

The Best Basketball Players: "Pound Per Pound"

In an article somewhere I've read on line - I'd give it credit, but I honestly can't remember what it was - a WNBA defender spoke about the foolish dismissals of the WNBA where some fool makes the argument because "my favorite NBA team/college team/local high school team could be a WNBA team". The approach to this defense was one I formulated before, but the article beat me to putting it in print.

Namely, that this argument is never made in boxing. Could Vladimir Klitschko beat up Manny Pacquiao? Probably, since Klitschko is physically stronger than Pacquiao and none of Pacquiao's opponents have hit Pacquiao as hard as Klitschko could. In boxing fandom, there is much discussion as to who is the best "pound per pound" fighter - who is the best fighter taking into account the differing weight classes.

As it turns out, we have a nice "one value" metric to assign worth to a ball player - John Hollinger's Player Efficiency Rating, or PER. PER can be calculated for both NBA players and WNBA players. I therefore decided to count NBA PER as essentially equal to WNBA PER. This equalizes male and female basketball players.

For WNBA players, only players who have played more than 5000 career minutes are included. Sorry, Cynthia Cooper. You probably would have been on this list, but the WNBA started too late.

Top PER Values for NBA and WNBA Players
(min 5000 minutes WNBA, min 15000 minutes NBA)

1. Lauren Jackson (28.55)
2. Michael Jordan (27.91)
3. LeBron James (26.86)
4. Tamika Catchings (26.67)
5. David Robinson (26.18)
6. Wilt Chamberlain (26.13)
7. Dwyane Wade (25.67)
8. Yolanda Griffith (25.49)
9. Bob Pettit (25.37)
10. Tim Duncan (25.02)
11. Neil Johnston (24.72)
12. Diana Taurasi (24.67)
13. Charles Barkley (24.63)
14. Kareem Abdul-Jabbar (24.58)
15. Lisa Leslie (24.24)
(T) Sheryl Swoopes (24.24)
17. Magic Johnson (24.11)
18. Karl Malone (23.90)
19. Dirk Nowitzki (23.76)
20. Kevin Garnett (23.59)

So is Lauren Jackson better than Michael Jordan? That's up for you to decide. (As for me, go Lauren.)

Best Stats Anywhere

If you wanted to know how well the Dream is doing for some advanced stats like net plus/minus and points per possession, go to this helpful page provided by the Minnesota Lynx organization. You can learn some interesting facts. Did you know that the Dream lead the WNBA in "points in the paint" and "second chance points"?

Of course you did. But if you didn't, go visit the link above. The guy who runs the page is cool.

1/2009 - Dream 75, Silver Stars 70: Effective Izi

Okay. We now remove all the fun from the win by taking a surgeon's scapel to it. Hopefully you didn't forget that game on Saturday. You know, when we went to the Silver Stars home court and beat them?

Dean Oliver's Four Factors gets heavy play:

Field goal shooting. We don't use the normal field goal percentages around here. Us statheads use "effective field goal percentage", where every 3-point shot counts as 1 1/2 ordinary shorts. For those mathetmatically inclined:

Effective field goal percentage = (FG + (1/2)*3P)/FGA

The final numbers:

Dream: 45.5 percent
Silver Stars: 44.3 percent

Shooting really wasn't the key to the Dream winning. The edge is a slight one. Maybe in some other stat.

Turnovers: San Antonio 20, Dream 22. Sort of a wash, really. Neither team held on to the ball well.

Offensive rebounding: The Dream had 13 rebounds and the Silver Stars had seven. But what was the Dream's offensive rebounding percentage?

The formula would be OR/(OR + Opp DR), where OR = "offensive rebounds" and DR = "opponent's defensive rebounds".

Dream Offensive Rebound Percentage = 13/(13 + 23) = 36.1 percent
Silver Stars Offensive Rebound Percentage = 10/(10 + 28) =26.3 percent

The real key to the Dream's win was that we outrebounded San Antonio. San Antonio really struggled on the offensive boards. Put it this way: the entire San Antonio team only had three more offensive rebounds than Erika de Souza.

Free throw visits: Dream 25, San Antonio 16. Both teams shot horribly: the Dream hit 52 percent of their free throws...but the Silver Stars hit just 50 percent. Incidentally, the Dream's +5 margin in free throws was exactly the margin of victory.

(* * *)

We give some props to our noble opponent by looking at the San Antonio Silver Stars:

Becky Hammon: 20 points, 4 rebounds, 5 assists. Hammon certainly wasn't tired, but as Erika de Souza can tell you, Hammon certainly didn't wear herself out in Spain.
Sophia Young: 15 points, 2 rebounds. And she was tired. She might have had 25 points if she had some oomph.
Michelle Snow: 11 points, 3 rebounds, 3 steals, 5-for-7 shooting. The ex-Dream player made a good impression in San Antonio.
Megan Frazee: 5 points, 3 rebounds. Her +9 raw plus/minus was the best on the San Antonio team. Why didn't they play her more?

And now, we'll take a look at the Atlanta Dream performance, from toppermost to bottommost:

Iziane Castro Marques: 23 points, 3 assists, 4 steals. 9-for-18 shooting. I've written before about the "Izi Effect" where Iziane's best performances come when the Dream is losing. Not this time. Izi carried the Dream. Maybe Iziane's one of those players that looks perpetually forward to new starts. But you have to give her credit despite her +2 raw plus/minus - Iziane was by far the Dreamer of the Game.

Angel McCoughtry: 20 points, 4 rebounds, 4 steals. Nice numbers, but with some caveats. First, it took 25 shots to make those 20 points - 20 field goal attempts and five free throw attemps. Also: three personal fouls and six turnovers. Maybe McCoughtry was trying a little too hard. Even with those asterisks, it was a pretty good game that lots of WNBA players would have loved to have.

Sancho Lyttle: 16 points, 7 points. She had five personal fouls, however, which kept her on the bench for long stretches of the first half after she picked up two quick personal fouls in the opening minutes. Her 6-for-9 shooting was impressive; imagine what she could have done without the foul trouble.

Erika de Souza: 11 points, 15 rebounds. A double-double looks impressive on any stat line. Her shooting however was just 5-for-14, which is quite low for The Beast from Brazil - she can usually bank them in from point-blank range. Her +10 raw plus/minus was the highest of the team - the Dream just did better on the court when Erika de Souza was on it.

All of this despite the fact that de Souza was obviously tired. A double-double when exhausted. She is clearly The Beast in the best sense of the word.

Shalee Lehning: One of Lehning's goals for 2010 was to be a better shooter. Her goal wasn't in range for this game: she took three shots and missed them and took three free throws and missed them. We take away credits for stuff like that. (That and four personal fouls.) But she had six assists - the most of any player on either team - and she had five rebounds, including the offensive rebound than ended the game.

Armintie Price: Here is where we sink into mediocrity. It's to be expected: of the Dream's 75 points, the five players above scored 70. Price had some good shooting - she was 2-for-3 with 4 points - but she wasn't a firebrand on the court. At least...not this game....

Alison Bales: Bales was actually decent in the sense that she wasn't embarrassing or inept - what you'd expect of a marginal player after a one-year layoff. Bales had one point but had five rebounds and a +9 raw plus/minus. Bales might come along this season if Leuchanka doesn't take her job on Wednesday.

Coco Miller: She's the Miller twin who played with the Dream last year. Frisco del Rosario said that he expected a "double billion" sometime this year from the Miller twins. (A "billion" is a line of nothing but zeroes in the box score.) Coco Miller has one steal and avoided ignominity.

Brittainey Raven: Didn't play. Coach's decision.

Chamique Holdsclaw: Didn't play. Holdsclaw's decision.

Kelly Miller: She played six minutes. No points, and three turnovers, averaging a turnover every 190 seconds. Those aren't pro numbers. So Kelly Miller gets the Still Snoozin' award. That's okay...it looks like we can set the alarm for this Friday, at the latest.

More Potential College Prospects and the Senior Prospects Metric

Mighty, or midget, or both?

The author of the Chasing the Title blog - even though his real name isn't that much of a secret I don't feel I have permission to state it yet - has boldly gone where only a few of us out there are going, namely, trying to say "these are the players you should be watching this year".

It's tough, because it opens you up to ridicule. Trust me, I know.

As far as I know, there are only three people doing this kind of stats-based analysis: me, the Chasing the Title author, and bullsky who is the author of WNBA Draft Net. Our lists of players look pretty much the same; the only difference is in what order should players be placed?

However, there are time when our lists don't match. I see a player at the Chasing the Title blog who isn't even on my list at all! There were three such players named. That means that I go back to my little spreadsheet, put the stats in, and see how they compare.

Here are three players on the Chasing the Title blog that weren't in my spreadsheet. But they are now. Let's look at how my metrics rate them.

Jenna Green, center, UC Santa Barbara

Well, there's a simple reason Jenna Green didn't make it to my list: she's returning not from her first, but her second medical redshirt year. Which means that we'll be comparing her against a class of people who are actually two years younger than her. Green is two years closer to her peak value, which automatically drops her a lot in my spreadsheet's evaluation.

On the other hand, in her rates of blocks and steals, Green is actually quite good. Furthermore, in terms of efficiency, she does well in producing value per minutes played.

In terms of assists vs. turnovers, she suffers - but all players except guards suffer, so she's in good company. The strength of her conference - the Big West - causes her rating to take a hit because she performs against a lesser class of players.

In her "rebounds expected per 100 rebounds a game for both teams total", however, Green suffers. She doesn't rebound as efficiently as a lot of centers - some of those centers are from schools in conferences as relatively weak at the Big West. My spreadsheet looks at her rebound rate, concludes "this is truly sub-par rebounding for a center", and assigns her a big hit against.

In the end, Green doesn't even make the Top 100 of my spreadsheet - the two medical redshirt years hurt her even more than her rebounding. If you decide to treat her as players aged two years younger, however, she'd jump to the 50s on my list.

Laura Kurz, shooting forward, Villanova

I never liked the term "small forward". There's nothing small about most of those ladies. For Laura Kurz, we might make a relative exception.

Kurz is another person who is missing a year - she sat out a year after transferring to Duke. Kurtz, however, is young enough to compare favorably with her "cohort", so to speak.

In terms of blocking-stealing-rebounding, her rates per game are frankly not impressive enough to stand out overall. She has too many turnovers for her assists - she had 32 assists compared to 71 turnovers in 2007-08.

However, Kurz is small compared to other forwards at 6'1" tall - she'd be at best a Jennifer Lacy type of forward, with Lacy's D-class output. Could Laura Kurz rally grapple against a Ruth Riley-Ann Wauters combo guarding the basket, much less a Candace Parker-Lisa Leslie tandem?

It doesn't look good for Kurz, and I have her at #99 on my list.

Brianne O'Rourke, point guard, Penn State

In O'Rourke's case, some things hurt her and some things help her. She doesn't have very many blocked shots - even for a guard - but Kristi Toliver doesn't have blocked shots either, and Toliver is #3 on my list.

Furthermore, O'Rourke handles the ball well if you compare assists to turnovers. So where does she take her hits?

She actually takes a double hit because of one factor - Brianne O'Rourke is five feet six inches tall. Just like my spreadsheet doesn't trust anyone over 6'6" - the "Katie Feenstra clause" - it turns up its nose at particularly small players. The spreadsheet basically says, "okay, here's a penalty, now prove that you're good". Good players will overcome the penalty; poorer players won't.

Because of her height, it's harder to get rebounds - not impossible if you like to fight, but harder. In "rebounds expected per 100 rebounds a game for both teams total", O'Rourke falls below the acceptable minimum. When O'Rourke players for you, you don't have five players scrapping for rebounds, you might have - as Queenie might say - "four rebounders and one midget". Rebounding is a skill that O'Rourke can't bring to the table. It impairs the team and has to be made up for elsewhere.

This puts O'Rourke in the 50s in my spreadsheet. If she has a good senior year - and I mean a really good one - she might approach WNBA draft territory. But if her senior year is like her junior year, odds are she won't be drafted.

Making Use of Usage

Usage is defined as the percentage of a team's possessions that an individual player uses. Basically, it approximates the "space" a player takes up in the team's offence.

If a team only had five players that were exact clones of each other, each would have the exact same usage rate: 20 percent. The stat is estimated by:

usage = 40 x (field goal attempts + (0.44 x free throw attempts) + (0.33 x assists) + turnovers) x (team pace / league pace) / minutes played

Unfortunately, calculating usage requires two other stats - team pace and league pace. The problem with calculating college usage is determining what "league" pace is. I've decided that when I use usage in evaluating college players, I'll ignore the "team pace / league place" part - in short, by assuming that team pace/league pace = 1.00. This introduces an error in a statistic which is essentially an estimation, but as long as the rules are laid out ahead of time, we'll go forward.

According to Ken Pomeroy at Basketball Prospectus, it seems to be an iron law that usage doesn't change much over time. If a player is a role player in college, she'll be a role player in the WNBA.

Furthermore, there's another rule about usage, this one formulated by Dean Oliver. Players who have high usage rates - somewhat over 25 percent - are performing under their maximum efficiency. It makes sense, as they have to carry more of a team's offense. You're not seeing the player at their best.

On the other hand, players with low usage rates - 15 percent or less - are already performing at their peak. If their usage goes above at what they're used to doing, they'll perform less well. Low usage players are performing at better than their maximum efficiency.

The end result is that players with high usage should be rewarded, and players with low usage should be penalized. I went to my Senior Prospects Metric and decided to reward any player with a usage above 25 percent, and to penalize players with usage below 15.

Players with Usage Greater than 25 Percent

Angel McCoughtry, Louisville - 32.69 percent
Robyn Fairbanks, Utah Valley State - 31.35 percent
Krystal Ellis, Marquette - 29.01 percent
Sade Logan, Robert Morris - 28.27 percent
Kendra Appling, Tennessee State - 27.16 percent
Shavonte Zellous, Pittsburgh - 26.36 percent
Megan Frazee, Liberty - 26.28 percent
Kristi Little, Duquesne - 25.86 percent
Obiageli Okafor, Tennessee State - 25.79 percent
Shantia Grace, South Florida - 25.21 percent
Erin Kerner, Quinnipiac - 25.20 percent

That doesn't mean any of the above players are going to be great WNBA players. Which players had the same unadjusted-for-pace average of the 2008 Draft Class? Valeriya Berezhynska with 30.76 percent and Jolene Anderson of Wisconsin with 30.55 percent. (Candace Parker had a respectable 28.60 percent at Tennessee.)

Adding in usage to the SPM moves Angel McCoughtry up from #8 to #5 on my list. And here's my newest Top 25:

Some More College Players and the Senior Prospects Metric

So who's this "Mandy Morales" girl?

I've added the Preseason Top 25 players has sparked a lot of discussion.

I have my own draft list of over 100 players, but there were players on bullsky's list that weren't on my list. I looked at the one's missing on my list, and then ranked them using the Senior Prospects Metric.

So does the newest WNBA Draft website find some diamonds...or does it dig some coal?

Robyn Fairbanks, Utah Valley State

Strengths: Averaged 23.8 points a game for Utah Valley State. Good rebounder and shot blocker.
Weaknesses: Plays for a weak conference - as a matter of fact, Utah Valley State does not belong to a conference. Short for a center.

Projection: Will not be drafted. I have her as #48 in my list of players. However, she should definitely show up at a WNBA pre-draft camp. Someone should at least give her a chance, given the dearth of centers.

Lindsay Wysdom-Hilton, Purdue

Strengths: Blocked Shots. Steals. All of the great defensive stats that would translate to NBA success if she were male.
Weaknesses: ACL tear led her to miss all of 2007-08. She's one year ahead of the other players in development.

Projection: I'm a moron for missing her. I had to evaluate Purdue's strength in 2007 as equal to 2008, since I don't have the Sagarin ratings for 2006-07, and they're not on the internet. If we assume that Purdue stands relatively to other teams the same way in 2006-07 as 2007-08...she jumps to #2. A first round pick, and the highest ranked forward.

Candace Byngham, Louisville

Strengths: Biggest contribution in my metric is in steals. Also a good rebounder.
Weaknesses: Age - older players take a bigger hit. Furthermore, at 6-1, she's small for a forward.

Projection: I have her at #39, which puts her as a candidate for the third round of the WNBA draft.

Jhasmin Player, Baylor

Strengths: Few turnovers and high steals ratio. Something tells me she's a great ball handler.
Weaknesses: She only played 21 games last year with a torn ACL. Therefore, we're looking at a smaller sample size of games. Games earlier in the season are usually against non-conference foes, and the Big East was the baddest conference around last year.

Projection: #15. On the border of second round/first round. She really needs to stand out as a senior.

Aisha Mohammed, Virginia

Strengths: She's a great rebounder.
Weaknesses: First, she'll be 23 on draft day. She's suffered a knee injury. She has a lot of turnovers (even for a center) and she doesn't have many blocked shots at all for someone playing the five position.

Projection: #115. She's not going to be drafted unless some team is absolutely desperate for a relatively unskilled rebounder. We'll see her in international play if her knees hold out.

Marshae Dotson, Florida

Strengths: High steal ratio. Good rebounder despite her size.
Weaknesses: High number of turnovers. Really too short to be a forward in the WNBA.

Projection: #81. The statistics say that she'll be one of the last people invited to a WNBA camp, and one of the first ones cut.

Mandy Morales, Montana

Strengths: Excellent assist to turnover ratio. As in 129 assists and 69 turnovers. Furthermore, she was the leading scorer for her team.
Weaknesses: Only age and that some might look down on the Big Sky conference.

Projection: bullsky over at the 2009 WNBA Draft site really found a diamond in the rough. Her stats project her as a first rounder, and she goes to #10 on my list. Someone should keep their eye on Mandy Morales.

Recruiting vs. NCAA Tournament Success - The McDonald's All Americans

Time to answer the question: what do Ivory Latta, Kasha Terry, Alison Bales, Camille Little and Ann Strother all have in common?

Answer: all of them were McDonald's All-Americans.

Ann Strother: 2002
Ivory Latta: 2003
Camille Little: 2003
Alison Bales: 2003
Kasha Terry: 2003

Some background about the McDonald's All-American team. Since 1977, McDonald's - the guys who make the Big Mac - have been naming high school All-Star teams. Being like everyone else in organized basketball, they didn't even notice the girls until 2002, when the first girl's McDonald's All-American team was named.

Sports America makes a list of 1200 girls, which is pared down to 150 players. The 150 players are then reviewed by a selection committee that shrinks the roster down to its final size. An "East" and "West" team are chosen, but more for balance than for geographical correctness.

These McDonald's All-Americans are considered to be the cream of the crop that the country has to offer, and as far as I know, all are seniors. These kids are heavily recruited by college programs, and most of the kids already know where they're going by the time the next college season rolls around.

If you look at some of these lists, they look like a WNBA roster. The 2004 McD All-Americans were pretty impressive. This list had Candace Parker, Crystal Langhorne, Nikki Anosike, Sylvia Fowles, Essence Carson, Alexis Hornbuckle, Tasha Humphrey, Candace Wiggins, and a couple of others that are on rosters today.

Of course, this doesn't mean that every McDonald's All-American will be a WNBA All-Star. Look at the Atlanta Dream, which has five McDonald's All-Americans on the roster, but only one of WNBA All-Star quality.

Once I learned about the McDonald's All-Americans, I asked myself, "how much does having a McDonald's All-American on one's college roster have to do with tournament success?" If I were, say, Coach Joe Blow from Wassamatta U., and I could recruit two McDonald's All-Americans , what would be my chances of success in the NCAA Tournament if I could get that far?

I first drew up lists of all of the All-Americans from 2002 to the present 2008 class. I looked up their college records. Some McD All-Americans, like Lindsay Richards (2002), got two years before injuries ended their career (Richards played at Iowa in the 2002-03 and 2003-04 seasons.) Others, like Brooke Smith (2002) would transfer after one year. Richards played for Duke from 2002-03, then transferred to Stanford. NCAA rules require that students transferring sit out one year. (Smith concluded her career at Stanford in 2007.)

Other students were medical redshirts, due to blown out knees and the like. Others couldn't cut the mustard academically (Erica Brown in 2005) or questioned their commitment to basketball (Elena Delle Donne in 2008).

The first All-Americans that made it through four years were the 2002 class, and it wasn't until 2006 that a college team could have a McDonald's All-American on their roster for four years. This gave me three NCAA tournaments to review - the 2006, 2007 and 2008 tournaments.

I accounted for three cases:

a) teams that went to the tournament and had an All-American on the roster,
b) teams that went to the tournament and did not have an All-American on the roster - these teams were the majority of teams, from the mid-majors and automatic byes, and
c) teams that had an All-American on the roster, but did not go to the tournament. Texas Tech had Erin Grant (2002), Brooke Baughman (2003) and Darrice Griffin (2004) but still couldn't make the tournament in 2006.

I wanted to look at games played in the NCAA tournament as opposed to games won. Looking at games played made more sense to me, as games played seemed to apply to all Division I teams, whereas games won restricted the group (in my mind) only to teams that made the tournament. A team that lost in the first round has one game played, a team that didn't make the tournament has zero games played.

We then restrict to teams that have McDonald's All-Americans.

The next step is to perform what is called a linear regression. Linear regression answers the question: "if the relationship between All-Americans and games played is linear - if having x All-Americans means you get to play y games in the NCAA Tournament - then what is the relationship?"

In real life, the relationship is not strictly linear, but we can statistically draw a "best fitting line" that best approximates the data.

Here are the "best fitting lines" for the 2006, 2007 and 2008 tournaments.

Let "x" = # of McDonald's All-Americans on your team.
Let "y" = # of expected games played in the NCAA Tournament that year by your team.

2006: y = 0.630x - 0.237
2007: y = 0.705x - 0.004
2008: y = 1.116x - 0.910

Note that for each of the years, the slope of the line - the number next to x - increases year per year. For each successive year in the analysis, having a McDonald's All-American has more impact.

Why is this? My hypothesis is that the selection committee has gotten better over time. Remember that the 2006 tournament represents the very earliest McDonald's All-Americans whereas the 2008 tournament reflects a McDonald's All-American committee with more experience in picking players. 2008 represented the strongest correlation between roster and tournament success.

Here is the best fitting line representing three years of data:

all years: y = 0.798x - 0.337

If your team has zero All-Americans on it, you will play an "estimated" -0.337 games in the tournament. If you have two All-Americans, you will play an estimated 0.798 * 2 - 0.337 = 1.259 games. Two All-Americans on the roster might get you past the first round.

If this relationship is correct, or even close to correct, it explains why these girls are so highly recruited.
Note that

in 2006, you needed three McDonald's All-Americans to make the NCAA finals (Maryland)
in 2007, you needed five McDonald's All-Americans (Tennessee, Rutgers)
in 2008, you needed six McDonald's All-Americans (Tennessee, Stanford)

In all three years of the NCAA Tournament for which McDonald's All-Americans play a fact, only one team in each of those three years that made it to the Elite Eight had no All-Americans on it.

2006: Utah
2007: Mississippi
2008: Texas A&M

Neither Utah, Mississippi, or Texas A&M was able to make it to the final four. Three years isn't much of a sample, but recruiting success appears to be highly correlated with tournament success.

So which teams have the most McDonald's All-Americans on them now? Which teams are the ones to look out for in 2009?



As you can see, Tennessee and Pat Summitt have an amazing nine McD All-Americans on the roster:

Fuller, Cane, Baugh, Bjorklund, Gray, Johnson, Manning, Stricklen, Brewer

Up next is Rutgers with eight All-Americans:

Vaughn, Prince, Rushdan, Lee, Sykes, Dixon, Pope, Speed.

As a matter of fact, one could probably pass off the list above as a pre-season Top 25 list and the casual observer wouldn't give it a second glance. Except, of course, for the observers who live in Connecticut.

POSTSCRIPT: The third column of the graphic should indicate Tournament Games, not wins. Since I'm at work, I'll fix it when I get home.

2009 WNBA Prospects, Part II

I'm coming back to the Senior Prospects Metric (SPM) and I'm continuing to make small changes in it. I'll mention the changes I've made:

Height has now been built into the model. I've found the heights of all of the players and made the following assumpions:

Guard height. John Hollinger makes distinctions between short point guards and short shooting guards. Since it's hard to determine whether a guard is a point guard or a shooting guard just by statistics (he furthermore makes a distinction between "short" and "somewhat short" guards), I've simply penalized any guard who is 5'8" or less. These "short guards" get a penalty which is 3/4th of the penalites that follow. The reasoning Hollinger uses is that if a short guard is really good, the other parts of the metric will overcome the height penalty.

Forward/center height. If a forward center is shorter than 6'3", they will receive a penalty.

The 6'6" ers. We could call this the "Katie Feenstra" rule. Hollinger noticed that NBA prospects who were taller than 7 feet were generally a sorry lot. These big men had distorted statistics because their opponents were generally shorter than the players they'd face in the WNBA.

I've penalized any player that is taller than 6'6". Sylvia Fowles barely makes the cutoff at 6'6".

Guards who can't shoot from the perimeter. According to Hollinger, a guard should be able to make at least 25 3-pointers in a season, which is about 0.78-0.85 threes a game, depending on the length of the season. If a guard can't make that many threes, they get a penalty.

Bad rebounders. In order to make this one work, I had to drag in a formula from John Hollinger called "Rebound Rate". I am not going to drag out the formula, which depends on the player's minutes played, her rebounds, and her college team's rebounds and opponent rebounds. I'll just explain how it works.

Assume that during an average game against College Team's Average Opponent, both teams have 100 total rebounds (that's a lotta rebounds!) Rebound rate answers the question "how many rebounds would player X get out of those 100 rebounds?"

Of course, the Hollinger Rebound Rate he uses in the draft prospects article...isn't the same as the Rebound Rate formula that he uses everyone else. I had to depend on a converstion from Frisco del Rosario, for which I thank him.

The penalties assessed are for:
* guards with a rebound rate of less than 5.0
* guards between 5'11" and 6'1" with rebound rates of less than 7.5
* guards 6'2" or taller with rebound rates of less than 8
* forwards with rebound rates of less than 12
* centers with rebound rates of less than 13

With no further ado, here are the 2008-09 prospects reevaluated.

2008-09 - The Best Senior Prospects

I've now concluded my analysis of the current Division I women's basketball prospects. All of these women will be seniors during the 2008-09 season. For blog readers which may be math-phobic, you might want to skip down to the very end where the players are actually named.

Why do an analysis?

Good question. The point is basically to try to determine which players deserve a closer look.

Whenever someone who likes statistics creates a ranked list, contention is the outcome. "How dare you claim that Player X is #16 when it's plain that X is better than Player Y who is #6?"

The goal is to look both with the eyes and with the stats. Your eyes can actually fool you as much as statistics can. In order to really know which players are the best, you would have to watch each of the named players for the entire college season. This is impossible for all but maybe a handful of reporters, and even they can only watch so many players in the day. Statistics do two things:

a) they isolate players that have distinguished themselves in some way in the boxscores and,
b) they point to a player's flaws as well as a player's strengths.

The Starting Point

I began with Hollinger’s idea that blocks, steals, rebounds, and three point shooting were important in a prospect. I determined that we should look at NCAA Division I players who were juniors in the 2007-08 season. Only players who were in the Top 100 players in any of the four categories indicated above should be considered. This left me with 108 players to look at, and I was able to locate statistics for 105 of those players. (Florida A & M and St. Mary’s (California), I’m pointing the finger at you.)

Ashley Paris, sister of Courtney Paris, was mentioned in a previous comment, so I added her to my list. As my attention is drawn to other players, I'll add them to my analysis.

Blocks, Forwards, Rebounds

One expects forwards and centers to be able to get rebounds, with guards at a disadvantage. All players should be able to get steals, with guards (being more agile and quick) having the best shot. Three point shooting would be primarily a guard skill.

I decided that the scale for blocks, steals, and rebounds would be linear. It would be based on number of blocks per game, steals per game, and rebounds per game. A good player should be good in all of these defensive skills at the college level. Therefore, these three factors were multiplied together. Ed Weiland has a stat called RSB40, which he uses as a multiplicative factor so I feel that I'm on the right track.

This decision hurts guards – because we don’t expect them to rebound - but the guards get a chance to be rewarded later.

Furthermore, the factor for steals was doubled. Hollinger weighted steals more heavily than any other factor in his analysis, and the numbers that come out at the end match up with “common sense” when I make the same decision.

The problem is that at some point in the analysis, you have to decide what number of blocks, steals, or rebounds per game corresponds to a factor = 1.0. Looking over the top 100 finishers in these categories, I made the following decisions:

1.5 blocks per game = factor of 1.0
2.2 steals per game = factor of 2.0 (remember, the factor for steals is doubled)
8.1 rebounds per game = factor of 1.0.

If you want different results, set different factors. I'm going to stand on these values, which would be pretty impressive if they were per-game.

Three-point Shooting

We ranked players by percentage, not by number of shots made. 0.343 percentage = 1.00 factor. Players were required to make at least an average of two three-pointers a game to sort out those people with high three-point shooting but low numbers of baskets – if they didn’t meet the average qualification, they got a zero factor.

Age

The age of players is definitely important, because older players are closer to their peaks. The youngest player among the candidates had a 11/18/1987 birthday. I began penalizing players who had birthdates before 11/18/1986. A person born a quarter of a year before that date would have 0.25 removed from the final score; a person born on 11/18/85 would have 1.0 removed from the final score. A player closer to their eventual peak should be devalued.

For some players, I was not able to find their ages. Those players were not penalized in the system. There was one player who was born in “January 1987”, I assigned her a birthdate of 1/15/87. She didn't suffer any age penalty according to my current rules.

Wins Efficiency

Certainly, we should reward players who can score, but by how much? There are so many metrics like PER and Efficiency. I don’t agree with “Efficiency” because I believe it overvalues crappy shooting. I therefore used the “Wins Score” metric, but divided it by Games Played – Wins Score is not divided by Games Played – to create a more Efficiency-like metric called “Wins Efficiency”. I divided the final Wins Efficiency results by 10 to award points. A player with a score of 10 in “Wins Efficiency” gets 1.00 point.

WPPR

This is a variation on Hollinger’s Pure Point Rating. The problem with Pure Point Rating is that if you apply the formula to WNBA players, they have terrible values. The reason is because in the NBA, the average team’s amount of turnovers is 2/3 of the amount of its assists. In the WNBA, players turn the ball over more and for an average team, turnovers and assists are equal. I simply removed the 2/3 multiplicative factor from Hollinger’s formula. In the NBA, assist/turnover ratio is misleading as to a player’s true value as a guard; in the WNBA assist/turnover ratio is more accurate.

My variation – WPPR – rewards players who have more assists than turnovers. A good guard will have a high WPPR and all players are rewarded 1/5 of their WPPR if the value is positive. In general, this decision rewards guards and punishes forwards and centers (who have more turnovers than assists), but the best forwards and centers at the college level can avoid turnovers. Still, they’ll have a negative number. If a forward or center has a negative WPPR, 1/10th of the WPPR is removed from the final score.

However, a guard who has a negative WPPR in the women’s game is someone whom one should be wary of. If a guard has a negative WPPR, 1/5th of the WPPR is removed from the final score.

50-50 players

Fifty-fifty players are players who have 50 blocks and 50 steals in a season in the men’s college games turn out to be excellent college players, according to Hollinger. Players are given a special 1.00 factor bonus for meeting this benchmark. Only two players qualify for this benchmark in the 2007-08 season: Demetress Adams of South Carolina and Jessica Bobbitt of Belmont. This is an additive factor, so no one is penalized for not reaching the mark. (Except for maybe Chante Black of Duke, who missed the 50-50 mark by one steal. I decided not to give her the point; your mileage may very.)

Conference Strength

Players were rewarded for playing against good teams and punished for playing against bad teams. The final score is multiplied by a factor equivalent to the strength of their conference. Conference strengths are determined by Jeff Sagarin’s ratings for women’s NCAA basketball. The central mean method was used, with the Big Twelve’s 86.55 rating converted to a 1.00 factor, and partial ratings converted linearly.

Final Factor

Equals:

blocked factor*steals factors (which is x2) * rebounds factor
plus three point factor
plus age factor (negative for older players)
plus Wins Efficiency factor
plus PPR factor
plus 50-50 factor….

all multiplied by conference strength factor.

Known Flaws

Hollinger points to several "red flags" that might disqualify a player. One of the flaws is the flaw of a player not receiving a certain number of rebounds per height. Hollinger states that "a player in the X range of height should receive at least Y rebounds per game". I wasn't able to do create these height categories because I don't have enough information about the range of heights in the NBA (and WNBA) to determine the appropriate cutoff points.

Furthermore, schools play at many different "paces". The word "pace" has a specific meaning in the APBRmetric community. I was not able to obtain this information and was not willing to calculate it for, oh, about 300 schools. Maybe someday, there will be a master women's college database. Until then, the speed at which schools play, the number of possessions per team, etc. is not taken into account.

(* * *)

So who are the leaders after all this number crunching? Lets look at the top twenty overall players:

Top Twenty Overall Players



We have Courtney Paris of Oklahoma as number one, and that's a good start. I'd expect Angel McCoughtry to be number two, but she ends up as #8 on the metric. However, Kristi Toliver at #2 should be no surprise.

I wonder if my formula gives too much credit to guards. Then again, I have approximately 20 centers, 30 forwards and fifty guards on my list so I shouldn't be surprised that guards are overrepresented. I would say the only surprises are Kristi Cirone of Illinois State and Jenna Schone of Miami of Ohio, both from small schools.

Top Ten Centers



I'm very surprised that the quality of centers drops of quickly after Courtney Paris. I don't know if centers get short shrift for having low WPPR or for the fact that most of the centers in women's college basketball don't seem to produce a lot of Wins Efficiency.

Top Twenty Forwards



Forwards also drop off quickly, although not as quickly as centers do. There are four good forwards to be had early in the draft. Most of the good centers come from the big schools.

Top Twenty Guards



Guards are the quality position in the metric. Even down at the twentieth position, there are decent guards. Furthermore, the small schools (Tiera DeLaHoussay at Western Michigan, Shantia Grace at South Florida) provide a large number of great guards. If you want to sneak up on someone in the draft, you can probably get a quality guard from an overlooked school.

I also wondered if guards are the prime position for players to make their presence known in women's basketball. The talent level at the women's college game is thinner than in the men's game, and it's more likely that tall (but not truly athletic) women have been pushed into the post positions in high school.

(* * *)

I'll try to keep this list updated, and to have the senior stats analyzed at the end of the 2009 season. Oddly enough, Hollinger says that good NBA players have a decrease in their statistics between their junior and senior years. So if one of your favorite juniors has a bad year...well, don't lose hope. And if one of your favorite juniors isn't ranked high on my list...well, 2008-09 has the power to change everything.

Extremistan

It was Q over at Rethinking Basketball who introduced me to the work of The Arbitarian, who is one of a small but dedicated network of NBA (and by extension, WNBA) stat grinders.

He introduced something called the "playing style spectrum". The formulas are at the link above. They are simple formulas -- nothing more than simple division -- but the explanation is a bit long.

What's the idea? The idea is to assign three numbers to every player....

Scorer index: Determines how much a player specializes in points and field goal attempts
Perimeter index: Determines how much a player specializes in assists and steals
Interior index: Determines how much a player specializes in blocked shots and rebounds

I then applied the score to all players with more than 10 minutes per game playing time in the WNBA. Let's take a look at the players on the Dream. An important note is that a high number for a player does not mean that they are the "best in the WNBA", but rather that a high portion of their individual game rests in one of the three areas above.

Betty Lennox (0.91, 0.45, 0.2)

It's what we think. A high degree of Lennox's value comes from scoring, but the middle number is good - she can also handle the ball.

Ivory Latta (0.78, 0.84, 0.03)

Latta is not just a shooter, but a point guard who can work the perimeter and handle the ball. Her interior game, however, is nonexistent...but we don't expect Ivory to get rebounds.

Tamera Young (0.59, 0.4, 0.59)

Young is the type of player who can do several things well in the time she gets.

Iziane Castro Marques (0.99, 0.46, 0.09)

Izi's game is more heavily related to scoring even than Betty Lennox's is. Like Betty, she's also good at handling the ball and lousy at the boards.

Jennifer Lacy (0.79, 0.21, 0.50)

For someone who is a forward-center, Jennifer seems to concentrate on scoring points more. My guess is that either a) Jennifer has been forced to rely more on shooting due to the need to come back from losses, or b) the presence of other shot blockers has allowed Lacy to be more agressive with scoring. Then again, her numbers might have always been like this.

Katie Feenstra (0.22, 0.01, 0.98)

Not much of a scorer, and as that 0.01 indicates, a lousy ball handler with only 10 assists and 3 steals all year. Her game is a big woman's game. But does that 0.98 mean that her game depends more on blocked shots and rebounds than anyone else on the Atlanta Dream?

Kasha Terry (0.31, 0.16, 0.88)

A bit more of a scorer than Kit is.

Alison Bales (0.05, 0.11, 0.99)

Holy moley. Bales personal game comes almost entirely from her ability to block shots and get rebounds.

Erika DeSouza (0.13, 0.04, 0.97)

Again, another pure shot blocker and rebounder.

(* * *)

So what does this mean? It means we have a lot of players on the Dream that have "extreme" games. Lennox and Castro Marques are extreme scorers. You give them the ball, and they're going to take a shot with it, offense be damned. They like to create their own offenses. How good they are at doing that is a matter of debate, given Castro Marques's streakiness and Lennox's tendency to turn over the ball. If you have a pure scorer, you want someone who can hit what she's aiming at and not turn over the ball.

Let's look at Cappie Pondexter's triple of (0.96, 0.6, 0.06). She's sort of like Betty Lennox and Izi Castro Marques. Cappie is also a "shoot first" kind of player. However, she hits 41 percent of her shots, compared to the 35 percent that Izi hits. She's also only turned the ball over 62 times, compared to Betty Lennox's 100.

Let's also look at Feenstra, Terry, Bales and DeSouza. They rebound. They block shots. But for the most part, that's all they do, particularly Alison Bales. Granted, Bales does it very well - in Wins Score, Bales has the highest value of any player on the Dream, even Ivory Latta or Betty Lennox! However, aside from Terry, Bales, Feenstra and DeSouza are all one-dimensional. On the offensive end, they can set screens or get the offensive rebound, but other teams know that Bales or Feenstra won't be given the ball to score (heck, if Izi or Lennox is on the floor, it's a much better idea to double team the lead shooters). Compare their triples with Lisa Leslie's (0.33, 0.26, 0.82). Leslie's game depends a lot on getting those rebounds and shot blocking, but not to the extent of the big women on the dream. Defenses still have to worry that Leslie will score with the ball.

So why is this post called "Extremistan"? If you look at other teams than the Dream, players don't seem to be clustered up at one end or the other of the spectrum as much as the players on the Dream. The Dream is a bit more predictable in their individual games than players from other teams. That makes it easy to build defenses around what the Dream can do offensively, and vice versa.

Shooting from Point-Blank Range

Whenever there's not a game on, Swanny at Swanny's Stats gives us the scoop on some odd stats.

In Shooting Percentage from 6-10 Feet, Iziane Castro Marques is in the top 10 of WNBA shooters, shooting 50 percent from close range (10-20). However, Tamera Young is the bottom 10 at 18 percent (4-22).

In Shooting Percentage from 1-5 Feet -- which is about as close as you can get -- we don't have anyone in the top 10 of WNBA shooters. However, Ivory Latta is in the bottom 10 at 45.8 percent (33-72).

Indeed, Atlanta is the worst team in the WNBA in point-blank shooting, shooting only 51 percent from 1-5 feet. It's a good thing that basketball courts aren't 10 feet long. Maybe Ivory needs to put a basketball hoop in her pantry, close the door, and practice a few shots.

Kit the Killer

Swanny has his "Transgressions" statistics up at Swanny's Stats, where we learn some interesting things regarding who fouls and who doesn't for the Dream.

Katie Feenstra is second in the league in offensive fouls committed with 19, beat out only by Nakia Sanford of the Mystics with 21. I suspect, however, that Feenstra "commits" most of these fouls due to her size, as refs assume "the big woman done it". I also suspect that once you get a reputation for committing offensive fouls, your reputation precedes itself. "It must have been Kit, she fouls all the time."

On the other hand, Izi Castro Marques has not committed an offensive foul this year. She's played 372 minutes, putting her in fourth place in the WNBA for 2008. The leaders are Swin Cash and Sheryl Swoopes of Seattle, which gives you a clue as to why Seattle is doing so well. Not only that, Izi's also in fourth place in Most Minutes Played Without Drawing an Offensive Foul.

Jennifer Lacy and Betty Lennox are in the top 10 in Most Offensive Fouls Drawn. (Plenette Pierson of Detroit and Nakia Sanford of Washington are tied for the lead.) Lacy has drawn 13 offensive fouls, good for fifth. Betty Lennox, at 11, is tied for eighth with three other players.

What about travelling? Katie Feenstra and Betty Lennox are tied for second, wtih 10 each, along with Charde Houston of the Lynx.

As for three-second lane violations, Kasha Terry has committed five this year and Katie Feenstra has committed four. I don't know what to say about this particular stat, but if I could figure out what to say about it, it wouldn't be good.

Dream Rejections

More interesting stats from Swanny:

Most FG Attempts Blocked, 2008 Season

1. Swin Cash, Storm and Katie Douglas, Fever: 23
5. Betty Lennox, Dream: 20
18. Ivory Latta, Dream: 18



Lowest Percentage of FG Attempts Blocked, 2008 Season
(min 50 attempts)

1. Cathy Joens, Sky: 0 percent (0-74)
8. Camille Little, Dream/Storm: 1.4 percent (1-70)



Most FG Attempts Blocked in One Game, 2008 Season

Nicole Powell, Monarchs at Silver Stars, July 3 -- 5 blocked
...
Ivory Latta, Comets at Dream, July 3 -- 4 blocked

Assisted and Unassisted Field Goals

Some interesting stats by Swanny. Go for the complete list at the link.

Swanny has three list where Atlanta has players on the top 10 or 20. The first is Highest Percentage of Assisted Field Goals. We have two players on that list. Stacey Lovelace is fifth with 85.7 percent of her field goals coming on assists (30-35). Katie Feenstra is eighth on the list with 82.8 percent (24-29). (The leader? Noelle Quinn of the Lynx, with 88.9 percent assisted.)

The second list is Highest Percentage of Unassisted Field Goals. Ivory Latta is ninth on that list with 65.6 percent (40-61). (The leader? Ticha Penicheiro of the Monarchs with 88.1 percent unassisted.)

The third list might be the most interesting...Top Assist Pairs. Tied for tenth with two other pairs is the pair Betty Lennox FROM Ivory Latta. Ivory, when she isn't making her own shots, has assisted Betty 19 times this year. The top of the list is Lauren Jackson FROM Sue Bird, an amazing 44 times.