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March 30, 2012
UK vs. the NBA
Another Look

by Neil Paine

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This week, former Maryland coach Gary Williams raised the question of whether the 2012 Kentucky Wildcats men's basketball team could beat the Washington Wizards right now. This is not a new idea (ESPN's Colin Cowherd noted early-90s comparisons between the Larry Johnson-era UNLV Final Four teams and bad NBA squads), but it's a consistently compelling one because it allows us to create fantasy matchups that can only happen in our imaginations.

A college team that could beat an NBA team.. On its face, the mere suggestion seems patently ridiculous. As Cowherd and Stan Van Gundy immediately pointed out, any pro-Kentucky argument focusing on their sheer number of NBA prospects needs to be tempered by the painfully obvious fact that every team in the NBA is, by definition, 100% comprised of NBA players. Simply having loads of potential NBAers isn't enough.

However, Kentucky wouldn't be bringing ordinary NBA prospects to this hypothetical matchup. Wildcats big man Anthony Davis is the number one overall pick in DraftExpress' 2012 Mock Draft, while teammate Michael Kidd-Gilchrist is ranked third. Meanwhile, forward Terrence Jones checks in at the #11 slot, and guard Doron Lamb lurks just outside the first round at #33. Based on their talent level, how much production could UK's players realistically expect to put up if they were dropped into the NBA this season?

To answer that question, let's look at recent rookies (2002-12). For every rookie who played at least 250 minutes per 82 scheduled team games, I calculated Alternate Win Score (adjusted for position and team, in the manner of Dan Rosenbaum & David Lewin in this paper), and used linear regression to retrodict it using a variety of factors (including age, draft position, and high school recruiting ranking). In the end, only one variable proved significant--their draft percentile rank, cubed:

Rookie_AWS ~ 3.345374 + 1.291682*Draft_percentrank^3
Of course, this would predict their rookie AWS at the NBA level (i.e., what we would expect next season); we also need to use an age adjustment to back up and find their expected skill level this year (I chose the aging adjustment from the Simple Projection System). Divide the number above by (1 + ((28 – 2013_age) * 0.004)), and you have an expectation for the AWS a player would produce in the NBA right now.

Plugging in the numbers from DraftExpress' latest mock draft, here were the numbers for Kentucky (using their playing-time distributions from both the NCAA Tournament to date and their big-time non-conference opening game vs. Kansas in November):

NCAA Tournament MP AWS Opening Night MP AWS
Marquis Teague 134 3.24 Terrence Jones 35 3.97
Anthony Davis 133 4.49 Michael Kidd-Gilchrist 35 4.35
Terrence Jones 130 3.97 Doron Lamb 34 3.37
Darius Miller 128 3.28 Anthony Davis 33 4.49
Michael Kidd-Gilchrist 128 4.35 Marquis Teague 33 3.24
Doron Lamb 119 3.37 Darius Miller 20 3.28
Kyle Wiltjer 24 3.24 Eloy Vargas 7 3.29
Eloy Vargas 4 3.29 Kyle Wiltjer 3 3.24
Team Total 3.77 Team Total 3.80

For the sake of context, the NBA average AWS is 5.26, so all of Kentucky's players would be below-average NBAers if forced to play this season. However, they don't have to beat an average team in our little thought experiment, just the NBA's worst.J

That means we need the odds of UK beating the Wizards (and let's throw in the Bobcats and Nets for good measure). For any game, you can calculate the probability of the home team beating the road team using the minute-weighted averages of their seasonal AWS scores:

p(hW) ~ 1 / (1 + e^(-0.486927 - 1.14971 * Diff))

Where “diff” is the home team's AWS minus the visiting team's AWS. Using that formula and their distribution of minutes played, we can calculate Charlotte's odds of beating Kentucky at home and away:

Charlotte
Last 4 Games MP Season AWS
Gerald Henderson 137 4.39
Corey Maggette 105 2.98
Derrick Brown 98 5.67
Bismack Biyombo 97 3.36
Kemba Walker 96 5.03
D.J. Augustin 92 4.95
D.J. White 83 3.92
Byron Mullens 81 3.30
Reggie Williams 72 4.64
Tyrus Thomas 66 1.17
Eduardo Najera 19 3.87
Matt Carroll 7 1.67
Cory Higgins 6 -1.03
3.98
Odds vs UK (tourney) at home: 67.4%
Odds vs UK (opening) at home: 66.7%
Odds vs UK (tourney) on road: 43.9%
Odds vs UK (opening) on road: 43.1%
Opening Night MP Season AWS
Gerald Henderson 39 4.39
Corey Maggette 39 2.98
D.J. Augustin 31 4.95
Boris Diaw 30 3.03
D.J. White 22 3.92
Kemba Walker 21 5.03
Byron Mullens 20 3.30
DeSagana Diop 16 1.90
Matt Carroll 9 1.67
Derrick Brown 8 5.67
Bismack Biyombo 6 3.36
3.73
Odds vs UK (tourney) at home: 60.9%
Odds vs UK (opening) at home: 60.2%
Odds vs UK (tourney) on road: 37.0%
Odds vs UK (opening) on road: 36.3%

Assuming Rupp Arena would have an NBA-esque home-court advantage vs. Charlotte, the Wildcats would actually be favored at home against Charlotte, whether facing the Bobcats' horrendous opening-night lineup or the improved group they've sent out recently. (This, of course, assumes that UK's distribution of minutes would proportionally remain the same during a longer NBA game, admittedly no given.)

At any rate, here are the same numbers for the Wizards and Nets:

Washington Wizards

Last 4 Games MP AWS
John Wall 148 5.44
Jordan Crawford 140 4.52
Chris Singleton 126 2.85
Kevin Seraphin 97 4.30
Trevor Booker 95 5.39
Nene Hilario 93 4.88
Jan Vesely 81 2.58
Roger Mason 71 5.07
Shelvin Mack 46 4.19
Edwin Ubiles 36 2.88
Brian Cook 19 -4.08
Maurice Evans 10 1.35
4.14
Odds vs UK (tourney) at home: 71.4%
Odds vs UK (opening) at home: 70.7%
Odds vs UK (tourney) on road: 48.5%
Odds vs UK (opening) on road: 47.7%
Opening Night MP AWS
John Wall 41 5.44
Andray Blatche 39 1.95
Jordan Crawford 28 4.52
JaVale McGee 28 6.73
Rashard Lewis 25 2.89
Chris Singleton 22 2.85
Ronny Turiaf 20 6.38
Nick Young 18 4.05
Trevor Booker 9 5.39
Shelvin Mack 7 4.19
Roger Mason 5 5.07
4.35
Odds vs UK (tourney) at home: 76.0%
Odds vs UK (opening) at home: 75.5%
Odds vs UK (tourney) on road: 54.5%
Odds vs UK (opening) on road: 53.8%

New Jersey Nets

Last 4 Games MP AWS
Deron Williams 150 6.52
Gerald Wallace 148 5.70
Kris Humphries 127 5.99
MarShon Brooks 110 4.41
Gerald Green 103 5.46
Shelden Williams 83 4.50
Jordan Williams 72 4.83
Anthony Morrow 45 5.15
DeShawn Stevenson 37 1.58
Johan Petro 32 1.56
Jordan Farmar 27 6.09
Sundiata Gaines 22 5.86
Jerry Smith 2 3.04
5.21
Odds vs UK (tourney) at home: 89.5%
Odds vs UK (opening) at home: 89.2%
Odds vs UK (tourney) on road: 76.3%
Odds vs UK (opening) on road: 75.7%
Opening Night MP AWS
Damion James 40 1.20
Deron Williams 36 6.52
Kris Humphries 36 5.99
Johan Petro 29 1.56
Anthony Morrow 25 5.15
Mehmet Okur 20 1.40
Sundiata Gaines 18 5.86
Shawne Williams 12 0.57
Shelden Williams 9 4.50
MarShon Brooks 8 4.41
Jordan Farmar 6 6.09
DeShawn Stevenson 0 1.58
3.86
Odds vs UK (tourney) at home: 64.3%
Odds vs UK (opening) at home: 63.6%
Odds vs UK (tourney) on road: 40.4%
Odds vs UK (opening) on road: 39.7%

Although they would be nearly on equal footing with the Bobcats (particularly Charlotte's brutal opening-night lineup), UK would struggle more against Washington, and be heavy underdogs against the Nets' current Gerald Wallace-infused lineup. Moreover, the Bobcats, Wizards, and Nets are by far the league's three worst teams according to SRS. From there, things get much tougher; against a league-average team the Wildcats would expect to win just 23.5 percent of the time, a number that becomes 8.2 percent against the league-best Chicago Bulls. According to AWS, in a 60-game home-and-home schedule vs. NBA teams, the Wildcats could expect to go 11-49 (again, assuming their playing-time distribution would stay proportional during 48-minute games).

Of course, this also means Williams was right. According to this model, at least, Kentucky would stand a chance against the NBA's worst squads. They wouldn't be favored unless facing someone like the Bobcats at home, but they theoretically could beat an NBA team if their talent is as ready for the pros as advertised.

Neil Paine is an author of Basketball Prospectus. You can contact Neil by clicking here or click here to see Neil's other articles.

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