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Young Players and How Minnesota's Youth Affects Winning

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While researching for an article I wrote elsewhere on the web, I decided to determine what I considered the true age of every WNBA team from 1997 to 2009.  My question was a simple one:  do older teams play better than younger ones, and if so, how strong is the connection?

One problem is that the ages of players changes over the season - time waits for no one.  For any given WNBA team, the age of player was given as "the player's age in years on July 1st".  I then weighted the ages by minutes played, so that the age of the team was biased in favor of which players played the most.

The oldest teams of the WNBA were no surprises.

Year Team Weighted Age WinPCT

2005 HOU 30.25 0.559
2009 LAS 30.02 0.529
2003 NYL 29.92 0.471
2002 NYL 29.81 0.563
2006 HOU 29.80 0.529
1999 HOU 29.68 0.813
2000 HOU 29.58 0.844
2001 NYL 29.28 0.656
2009 SAS 29.23 0.441
1999 NYL 29.21 0.563

Last year's Los Angeles Sparks had both Lisa Leslie and Tina Thompson on the roster, and each of those players had been in the league since 1997.  The 1999 and 2000 Houston Comets - world champions - had Cynthia Cooper on the squad, a player who never got her chance to play in the WNBA until her 30s.

My surprise came when I looked at the ten youngest teams in WNBA history.  I think you might be surprised, too....

Year Team Weighted Age WinPCT

2007 MIN 23.67 0.294
2009 MIN 23.74 0.412
2002 MIN 23.84 0.313
2006 MIN 23.97 0.294
2002 DET 24.12 0.281
2003 DET 24.17 0.735
2001 MIN 24.18 0.375
2000 MIN 24.29 0.469
2002 SEA 24.48 0.531
2008 NYL 24.50 0.559

The Lynx hold six spots in the top ten, and the #1 through #4 spots on the list.  Last year's Lynx squad was the second youngest ever to play in the WNBA.  They have six spots in the top ten.

Another fact about the Minnesota Lynx-Kittens - for the most part, the teams were pretty bad.  It might be more illuminating to list the total wins of every Lynx team over the franchise's history.  Here we go!  15, 15, 12, 10, 18, 18, 14, 10, 10, 16, 14...and 2, as of this writing.

Okay.  The Lynx suck.  Even Lynx fans will agree with you.  But is the youth of these Minnesota teams a feature in their losing, or is it a bug?  What kind of relationship does a team's youth have with its ability to win games?

We'll run a straight statistical correlation.  A zero would indicate that there's no relationship.  A one would indicate a lockstep, fixed relationship.  The correlation yields 0.372, a low to medium number.  Yes, there is a low-level relationship, but it's a stronger relationship than, say, a team's ability to shoot the 3-pointer.  At some noticable level, age influences winning.

Now let's remove the Lynx from the scene.  This might be a little hard to do, as with the Lynx absent this would affect the win-loss record of every team that could have normally picked up easy wins against the Kittens.  We'll ignore that problem and proceed.  The final correlation between youth and winning in a Lynxless world is 0.335, which isn't much different from our starting point.  More likely, the Lynx's youth is an integral part of why they can't win games. 

If that's the case, then it gives old-timey sportswriters the chance to expound on the calm, steady influence of time-tested leadership and write about intangibles and use a few metaphors.  "Father time hasn't beat back the march of...."

So if we suspect that older teams are better, why are they better? 

"Because they know more!  Duh!" 

They're using that intangible hocus-pocus, they know what to do in the last three minutes of a game, they bear the responsibility of the team on their backs and they don't eat the skin on their chicken. 

We're talking in anecdotes here, but if that's the case, then I'm reminded of the stories of those individuals in the men's game who were great coaches...but lousy players.  Bob Knight was a benchwarmer in his brief stint as a pro.  Rick Pitino was a gym rat that simply didn't have the physical tools.  There's no way to quantify game knowledge, but I suspect that knowing the game doesn't necessarily translate into playing the game well - and vice versa, since we all know great players that were horrible coaches. Sometimes, genetics screws you over and the closest you'll get to being on a WNBA team is leading it into battle with a clipboard.

Rather, it could be the case that age rewards the fortunate.  In the article on Age Curves and Katie Smith's hypothetical future value when the Lynx traded her to Detroit, Smith's career certainly wasn't 85 percent over.  Take a look at the 2009 Sparks, with both Lisa Leslie, Tina Thompson, and an over-30 Betty Lennox on the squad.

Why did Michael Cooper allow these old women to play at all?  Because they were all good players.  From the moment a player enters the WNBA, a winnowing-out process takes place.  Players who can't hang against their cohorts - even the ones who came into the league the same time as they did - are the first to go.  Then you bump into the three-year rookie contracts and the bump in pay that players expect in that fourth year, and some teams decide certain players aren't worth the extra money.  The lucky survivors hang on.  Some get injured and can't play any more.  What's left over is the cream of the crop - players who have consistent value every year and remain relatively injury free.

For seasons where a WNBA player is age 23, the average adjusted wins score of those players for the year is 10.76.  For a 30-year old player it's 19.52.  They don't let you play at age 30 in the WNBA unless you're good.  If a team has old players, those players are more likely to be good players, and teams that have a preponderance of good players are teams that win more frequently. 

So what happened to the Lynx?  How come they were never able to obtain good players, or at least let their players mature? All signs would seem to point to management not retaining the talent and letting them age with the team. We don't currently know exactly how much general manager Roger Griffith has to with player acquisition, but Griffith has been a major figure at the Lynx ground level for the decade or so the team has been in Minneapolis. I'll let the Lynx experts chime in on that one, but it becomes reasonable to believe that it certainly helps one's job security if you're the son-in-law of the owner.

Following is the complete list of WNBA teams by age from 1997 through 2009:

Year Team Weighted Age WinPCT

2007 MIN 23.67 0.294
2009 MIN 23.74 0.412
2002 MIN 23.84 0.313
2006 MIN 23.97 0.294
2002 DET 24.12 0.281
2003 DET 24.17 0.735
2001 MIN 24.18 0.375
2000 MIN 24.29 0.469
2002 SEA 24.48 0.531
2008 NYL 24.50 0.559
2004 PHO 24.52 0.500
2007 NYL 24.58 0.471
2000 LAS 24.63 0.875
2008 MIN 24.66 0.471
1999 LAS 24.75 0.625
2004 DET 24.77 0.500
2000 IND 24.82 0.281
1999 WAS 24.87 0.375
1997 UTA 24.94 0.250
2001 CLE 24.96 0.688
2003 CLE 25.00 0.500
1998 WAS 25.01 0.100
2006 CHI 25.04 0.147
2005 SEA 25.04 0.588
1998 SAC 25.05 0.267
2001 IND 25.16 0.313
1998 UTA 25.18 0.267
2009 NYL 25.20 0.382
2002 CLE 25.28 0.313
2008 ATL 25.31 0.118
2006 NYL 25.32 0.324
2000 POR 25.40 0.313
2003 PHO 25.41 0.235
2003 WAS 25.42 0.265
2004 WAS 25.46 0.500
1997 LAS 25.48 0.500
2008 CON 25.51 0.618
2002 POR 25.56 0.500
2005 DET 25.57 0.471
2007 CHI 25.60 0.412
2001 SEA 25.61 0.313
2001 ORL 25.62 0.406
2006 PHO 25.64 0.529
2009 CON 25.70 0.471
2000 DET 25.74 0.438
2006 SEA 25.76 0.529
2000 CLE 25.82 0.531
2005 MIN 25.84 0.412
2005 PHO 25.85 0.471
1999 ORL 25.86 0.469
2004 IND 25.87 0.441
2002 IND 25.95 0.500
2001 POR 25.99 0.344
2004 MIN 26.02 0.529
2006 SAS 26.02 0.382
2000 ORL 26.12 0.500
2001 LAS 26.14 0.875
2008 CHI 26.17 0.353
2009 CHI 26.18 0.471
1999 CLE 26.18 0.219
2009 WAS 26.18 0.471
2001 DET 26.22 0.313
1998 CLE 26.23 0.667
2009 ATL 26.23 0.529
1997 CLE 26.26 0.536
2002 ORL 26.28 0.500
2002 WAS 26.28 0.531
1998 CHA 26.31 0.600
2000 WAS 26.33 0.438
1999 SAC 26.33 0.594
2007 SEA 26.33 0.500
2008 SAC 26.36 0.529
2005 SAC 26.40 0.735
2006 CHA 26.42 0.324
2000 SEA 26.55 0.188
2009 PHO 26.55 0.676
2003 SEA 26.58 0.529
2000 MIA 26.58 0.406
2007 PHO 26.59 0.676
1998 LAS 26.62 0.400
2006 LAS 26.62 0.735
2005 SAS 26.73 0.206
2006 DET 26.73 0.676
2004 SEA 26.82 0.588
2004 CON 26.90 0.529
2005 LAS 26.90 0.500
2002 LAS 26.93 0.781
2003 IND 26.94 0.471
2008 PHO 26.96 0.471
2007 LAS 26.99 0.294
2000 UTA 27.01 0.563
1997 CHA 27.04 0.536
2006 SAC 27.08 0.618
2005 WAS 27.10 0.471
2000 SAC 27.15 0.656
1999 DET 27.17 0.469
2004 SAS 27.19 0.265
2006 CON 27.21 0.765
2005 CON 27.22 0.765
2004 LAS 27.23 0.735
1999 MIN 27.24 0.469
2003 MIN 27.30 0.529
2007 WAS 27.31 0.471
2002 PHO 27.32 0.344
2006 IND 27.32 0.618
2007 SAC 27.35 0.559
2001 WAS 27.38 0.313
2008 WAS 27.40 0.294
2007 SAS 27.43 0.588
2005 IND 27.44 0.618
2004 HOU 27.46 0.382
1997 NYL 27.46 0.607
2007 CON 27.47 0.529
2009 SEA 27.49 0.588
2000 CHA 27.49 0.250
1998 PHO 27.49 0.633
2007 HOU 27.51 0.382
2002 MIA 27.55 0.469
2009 SAC 27.67 0.353
2001 CHA 27.67 0.563
1997 SAC 27.72 0.357
2007 DET 27.72 0.706
2001 PHO 27.76 0.500
2001 MIA 27.82 0.625
2008 LAS 27.91 0.588
2003 CON 27.92 0.529
1999 UTA 27.95 0.469
1997 PHO 27.98 0.571
2003 LAS 27.99 0.706
2008 IND 28.00 0.500
2008 DET 28.00 0.647
2002 CHA 28.01 0.563
2008 SEA 28.02 0.647
1998 DET 28.04 0.567
2005 CHA 28.10 0.176
2001 HOU 28.13 0.594
2004 NYL 28.15 0.529
2006 WAS 28.16 0.529
2001 UTA 28.18 0.594
1999 CHA 28.18 0.469
2001 SAC 28.27 0.625
2000 PHO 28.30 0.625
1998 NYL 28.30 0.600
2000 NYL 28.35 0.625
2005 NYL 28.36 0.529
2003 SAS 28.39 0.353
2004 SAC 28.40 0.529
2008 HOU 28.46 0.500
2003 HOU 28.50 0.588
2007 IND 28.65 0.618
2008 SAS 28.67 0.706
2009 IND 28.69 0.647
2002 HOU 28.73 0.750
2003 CHA 28.73 0.529
2003 SAC 28.74 0.559
2002 SAC 28.74 0.438
2004 CHA 28.87 0.471
2009 DET 28.91 0.529
2002 UTA 28.99 0.625
1998 HOU 29.14 0.900
1997 HOU 29.17 0.643
1999 PHO 29.19 0.469
1999 NYL 29.21 0.563
2009 SAS 29.23 0.441
2001 NYL 29.28 0.656
2000 HOU 29.58 0.844
1999 HOU 29.68 0.813
2006 HOU 29.80 0.529
2002 NYL 29.81 0.563
2003 NYL 29.92 0.471
2009 LAS 30.02 0.529
2005 HOU 30.25 0.559