The Youngest and Oldest Teams in the NBA

Typically when someone on TV talks about a team being young or old, they just take the average age of everyone the
roster. Which of course is a worthless number. If your youngs never play, your team is older than your average. If
the old guys never play, its younger than its average.

To find out where all the teams stood, i went through and took the age of each player on dec 31st and multiplied
by the number of minutes they have played and calculated the weighted average age for each team.

These charts are going to look confusing unless you are into numbers, but the numbers are interesting. The teams
are ordered from youngest weighted average age to oldest. All teams show the most used lineup in minutes, except for
the MAVs. I just picked a lineup but excluded numbers. Hey, this is competitive info …..

ATL “team 23.49 weighted age

ATL 1.00 131.08 minutes 57
appearances

Harrington Johnson
Lue Pachulia J.
Smith 24.20 years

CHI “team 24.48 weighted age

CHI -7.02 109.54 minutes 38 appearances

Chandler Duhon
Hinrich Nocioni
Sweetney 24.17 years

POR “team 24.96 weighted age

POR -13.40 172.98 minutes 58 appearances

Miles Monia
Przybilla Randolph Telfair
23.64 years

(I used this lineup since it played so much more than the next most used)

CHA “team 25.33 weighted age

CHA 3.93 157.97 minutes 60 appearances

Brezec Knight
Okafor Rush
Wallace 25.65 years

LAL “team 25.72 weighted age

LAL 10.63 216.09 minutes 74 appearances

Bryant Cook
Mihm Odom
Parker 25.93 years

MIL “team 25.91 weighted age

MIL -4.09 213.05 minutes 76 appearances

Bogut Ford
Magloire Redd
Simmons 24.68 years

BOS “team 25.98 weighted age

BOS 1.63 279.20 minutes 112 appearances

Blount Davis
LaFrentz Pierce
West 27.32 years

NOH “team 26.20 weighted age

NOH 0.25 263.95 minutes 80 appearances

Brown Mason
Paul Smith
West 26.15 years

UTA “team 26.25 weighted age

UTA 0.84 81.75 minutes 29 appearances

Giricek Kirilenko
McLeod Okur
Ostertag 27.79 years

TOR “team 26.30 weighted age

TOR -16.07 91.45 minutes 26 appearances

Araujo Bosh
Calderon James
Peterson 26.06 years

TOR 16.22 90.61 minutes 46 appearances

Bosh Calderon
James Peterson
Villanueva 25.25 years

(I showed both since the minutes were almost exactly the same)

NYK “team 26.42 weighted age

NYK -19.93 35.75 minutes 17 appearances

Ariza Davis
Frye Marbury
Richardson 26.97 years

(*Knicks most used by minutes lineup had Matt Barnes, so I excluded it)

GSW “team 26.60 weighted age

GSW 0.01 389.30 minutes 111 appearances

Davis Dunleavy
Foyle Murphy
Richardson 26.69 years

ORL “team 26.68 weighted age

ORL -8.81 100.41 minutes 33 appearances

Battie Francis
Hill Howard
Stevenson 27.36 years

(i used the lineup with Grant Hill since he is back)

SEA “team 26.73 weighted age

SEA 6.79 175.39 minutes 67 appearances

Allen Collison
Evans Lewis
Ridnour 26.51 years

WAS “team 26.99 weighted age

WAS 3.03 162.62 minutes 49 appearances

Arenas Hayes
Haywood Jamison
Jeffries 25.62 years

PHI “team 27.24 weighted age

PHI 5.57 286.85 minutes 109 appearances

Dalembert Iguodala Iverson
Korver Webber 26.95 years

DAL “team 27.54 weighted age

DAL 15.17 xxxx minutes xx appearances

Daniels Diop
Harris Howard
Nowitzki 24.99 years

LAC “team 27.74 weighted age

LAC 3.10 248.86 minutes 96 appearances

Brand Cassell
Kaman Mobley
Ross 28.32 years

CLE “team 27.78 weighted age

CLE 2.11 341.82 minutes 116 appearances

Gooden Hughes
Ilgauskas James
Snow 27.09 years

IND “team 27.79 weighted age

IND 9.77 169.28 minutes 70 appearances

Artest Croshere
Jackson O’Neal
Tinsley 27.92 years

MIN “team 28.02 weighted age

MIN 9.01 408.75 minutes 111 appearances

Garnett Hassell
Jaric Olowokandi Szczerbiak 28.65
years

DEN “team 28.04 weighted age

DEN 4.65 94.58 minutes 39 appearances

Anthony Camby
Lenard Martin
Miller 28.76 years

SAC “team 28.15 weighted age

SAC 9.98 508.58 minutes 177 appearances

Abdur-Rahim Bibby
Miller Stojakovic
Wells 28.85 years

MEM “team 28.61 weighted age

MEM 4.15 309.19 minutes 89 appearances

Battier Gasol E.
Jones Stoudamire Wright
29.90 years

DET “team 28.62 weighted age

DET 18.63 616.12 minutes 202 appearances

Billups Hamilton
Prince B. Wallace R. Wallace 29.12
years

PHO “team 28.79 weighted age

PHO 12.61 254.01 minutes 85 appearances

Bell Diaw
Marion Nash
Thomas 29.16 years

NJN “team 29.20 weighted age

NJN 12.43 315.84 minutes 98 appearances

Carter Collins
Jefferson Kidd
Krstic 27.35 years

MIA “team 29.39 weighted age

MIA 21.16 172.28 minutes 61 appearances

Haslem Mourning
Posey Wade
Williams 28.90 years

HOU “team 29.85 weighted age

HOU -2.97 97.47 minutes 21 appearances

Bowen Howard
McGrady Wesley
Yao 30.01 years

SAS “team 30.50 weighted age

SAS 0.37 192.76 minutes 69 appearances

Bowen Duncan
Finley Nesterovic
Parker 30.05 years

SAS 21.98 191.76 minutes 53 appearances

Bowen Duncan
Ginobili Nesterovic Parker
29.17 years

(I included both since the minutes were almost dead even)

And while Im at it, here is some more fun info

1 Atlanta 160 lineups used

2 Boston 205 lineups used

3 Charlotte 304 lineups used

4 Chicago 218 lineups used

5 Cleveland 120 lineups used

6 Dallas 187 lineups used

7 Denver 214 lineups used

8 Detroit 86 lineups used

9 Golden State 176 lineups used

10 Houston 179 lineups used

11 Indiana 182 lineups used

12 LA Clippers 208 lineups used

13 LA Lakers 193 lineups used

14 Memphis 189 lineups used

15 Miami 162 lineups used

16 Milwaukee 164 lineups used

17 Minnesota 164 lineups used

18 New Jersey 176 lineups used

19 New Orleans 132 lineups used

20 New York 281 lineups used

21 Orlando 203 lineups used

22 Philadelphia 170 lineups used

23 Phoenix 133 lineups used

24 Portland 253 lineups used

25 Sacramento 122 lineups used

26 San Antonio 203 lineups used

27 Seattle 181 lineups used

28 Toronto 119 lineups used

29 Utah 230 lineups used

30 Washington 153 lineups used

38 thoughts on “The Youngest and Oldest Teams in the NBA

  1. Oh – very nice, I be back.
    Best regards for all.

    Comment by Agroturystyka -

  2. I see – very good !

    Best regards for all.
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    Comment by Agroturystyka -

  3. good

    Comment by imdbcn -

  4. yes very nice work!

    Comment by Ogłoszenia anonse -

  5. Very nice. you have drive and passion, so maybe it is you.

    Comment by praca za granicą oferty pracy -

  6. Of course, if Bird and Walsh are smart, they will trade him to a crappy team for next year’s 1st rounder and others to make the deal work which would make the Pacer average less.

    Comment by runescape money -

  7. That is, if something was done in a team, that went off all the charts statistics-wise, and that combination proved magical and led to a championship team, I bet that other teams would possibly try to emulate that trend numberically also, but that would not necessarily lead to their success also.

    Comment by wow powerleveling -

  8. very interested theme; I will back, thanks!

    Comment by tworzenie stron -

  9. Very nice. Yeah, there’s no way you have time to compile these stats. LOL. But you have drive and passion, so maybe it is you.

    Maybe you’ll figure out a secret mathematical formula to basketball that’ll make you win. Like the secret baseball formula that everyone’s talking about.

    Comment by business -

  10. Do you really write everything here? I doubt it considering that you have so much money, no way, I bet my chatmates from webdatedotcom were right

    Comment by thynoe123 -

  11. Thanks for the statistics about team ages, Mark. As someone who is getting into sports operation research, this is really cool information.

    Comment by cnfalv -

  12. very goooooood!!!

    Comment by story -

  13. very goooooood!!!

    Comment by story -

  14. very goooooood!!!

    Comment by story -

  15. ºÜgoooooood!!!

    Comment by story -

  16. Some interesting stats, how would you assess the sport of baseball lineups?

    Comment by whales -

  17. I just added Smartest Guys and War Within to my Netflix queue! I can’t wait! But I too am surprised that Mr. Direct-to-Consumer is suggesting Amazon instead of some downloadable method… ~M

    Comment by IT中国 -

  18. back in the day who was the oldest person who started played N.B.A?

    Comment by james -

  19. Thanks for the statistics about team ages, Mark. As someone who is getting into sports operation research, this is really cool information.

    also, to val in post 10,

    Do you really think personal maturity matters on a basketball court? See Portland Jailblazers. It would be interesting if Mark had some statistics on the Jailblazers teams and their plus/minus numbers. I guess you could make the argument that “Since everyone on the team had a low personal maturity level, they also had a correlating high personality compatibility.”

    As for the rest of your thoughts, I am not quite sure you understand what Mark and Sagarin and that other guy are looking to measure with these numbers or why Mark has invested so much faith into these numbers. From what I have read, the Mavs use this info mostly to pinpoint players on hot streaks or cold streaks who the Mavs can exploit in one on one matchups. IOW, rather than the traditional “We Must Stop This One Guy”, the Mavs try and break down matchup for matchup on the team and see where they can take advantage of a player playing poorly and also where they will have to double team/get in foul trouble/mess with the head of a player who is on a hot streak,

    Comment by John "Z-Bo" Zabroski -

  20. to val in post 10.

    “gelling, synergy, group-think, team-sensibility, positive energy, synchronicity, great communication skills, complementarity of skills, will to achieve, professional and personal maturity and flexibility, faith and belief, persistence, patience, personality compatibility, social contribution, giftedness, developmental potential, luck, interpersonal sensitivity, potential skills, or maybe just plain abuncance of serendipity, and also guts in risk taking to make decisions when the number trends don’t support it.”

    we will call that the MJ formula, guranteed to win rings, unless abe pollin signs the cheques.

    Comment by chris in australia -

  21. That is very interesting. You should tell the NBA or TNT to use that statistic instead of the “useless” statistic you spoke of. Good thinking. Visit Solution Bound!!

    http://www.solutionbound.com

    Comment by Lewis -

  22. When a relatively young team has a single player in his late 30s playing serious minutes and a young talented kid in the wings, this team’s average age (weighted or otherwise) can be very misleading. When doing statistical analysis, good statisticians make calls on what data to weigh and what data to throw away based on various principles and standards of the industry. It doesn’t always add up to you or me but often proves a more accurate prediction.

    Comment by David-Plano -

  23. Well… there might be a correlation between age and success, but it would not be linear.

    Cleveland’s average age is 28 and without Lebron 21… There average age would be much higher and their success would be much lower.

    Comment by penxv -

  24. Mark,
    – These numbers aren’t as useful for a statistical analysis as the other set that you posted (Back to Backs in the NBA). There are obvious and separate advantages to have youth and to have experience. Any statistical analysis done with these numbers would be inherently muddled.

    – I wanted to do something with these numbers, but I just didn’t see how it could be useful.

    – If you went back into your stats to find out the number of wins and losses that teams had on the second game of a back-to-back versus fresh teams… You could get a statistically accurate read on the effect of playing back-to-backs.

    It could be broken down even further by doing separate home and away analysis.

    Comment by penxv -

  25. Have you run a regression – winning as a function of line-up consistency? Is there a correlation or pattern?

    Comment by nate -

  26. Mark — you may want to include 8 players in your analysis. Many of the NBA’s youngest players (esp rookies) get the majority of their minutes as 6th men.

    Comment by chris -

  27. It seems that, with the exception of a few outliers, average age corresponds very well to success. (If Dallas were to have posted their lineup of Terry, Stackhouse, Howard, Nowitzki, Dampier which was used so often last year my guess is that their average age would be right up with the highest.) It is not rocket science as to why this stat is as such. When teams are bad they draft high and play these draft picks. Atlanta, Toronto, and NO have all been forced to play their first round picks from the last few years a significant amount of time. Also, if a player is good then he stays in the league and plays a lot. If he is bad then he does neither. So, if you are a good team then you are not looking to replace your god players as they get older with younger guys with anything close to the frequency that bad teams do.

    Comment by Brian G -

  28. Then there is the importance of good timing, as contexts can change….and a great decision one year can not work in another situation. No time to comment further, Val.

    Comment by Val -

  29. Interesting for sure. However, while stats are relative in that they are a representation of reality they never exactly can predict or match reality – leaving room for other things such as gut feel, experience, talent in personnel selection, teaching and training giftedness in development of human resources etc as further wildcards to throw an X factor into it possibly. That is, if something was done in a team, that went off all the charts statistics-wise, and that combination proved magical and led to a championship team, I bet that other teams would possibly try to emulate that trend numberically also, but that would not necessarily lead to their success also. The numbers really are not the important part of it, and numbers would not necessarily show key intangibles like gelling, synergy, group-think, team-sensibility, positive energy, synchronicity, great communication skills, complementarity of skills, will to achieve, professional and personal maturity and flexibility, faith and belief, persistence, patience, personality compatibility, social contribution, giftedness, developmental potential, luck, interpersonal sensitivity, potential skills, or maybe just plain abuncance of serendipity, and also guts in risk taking to make decisions when the number trends don’t support it. but the decision seems right otherwise, and when tried somehow works better than imagined. I doubt that any statistical analysis can ever reflect how individual elite athletes mesh or not as a group for example. Although relevant, helpful, insightful, and interesting, statistical analyses is still no match for great/inspired personnel selection/development imho, as long as people remain people. Val

    Comment by Val -

  30. Hey Mike (post 1),

    Wouldn’t you think the time is the result, not the effect? Kind of the chicken and the egg thing. Clearly, the time can second.

    Comment by David -

  31. Aside from age, what about experience? And, not experience based on # of seasons played, but # of minutes played? Kobe Bryant is a young guy, but he has played a ton of minutes.

    Comment by tim gibbons -

  32. Correlation coefficient between age and winning %: 0.4096

    Getting the most wins from their age:

    1) DET
    2) DAL (large jump to #3)
    3) SAS
    4) MIL
    5) CLE

    Worst:

    1) TOR
    2) NYK
    3) ATL
    4) HOU
    5) CHA

    If you’re looking for a new team to cheer for the next 5 years, DAL, MIL, and CLE (barring the loss of #23) look like good potentials.

    Comment by Sam O -

  33. Mike,
    I don’t believe that Mark is compiling these stats. I live in Dallas and read the job postings on the Mavericks website. A couple of weeks ago or so I saw that he was hiring a statistician. Probably has more than one on the staff.

    Comment by Todd -

  34. Marc, can you post win/loss records by average age? Curious to see how the age factors into w&l.

    I could look it up myself but I am lazy and you seem to have the number anyways.

    Comment by Scott Pinkston -

  35. Don’t count Artest against the great Pacer team. Of course, if Bird and Walsh are smart, they will trade him to a crappy team for next year’s 1st rounder and others to make the deal work which would make the Pacer average less. That would show Ronny, send him to the Raptors for some picks. They can have Jax too as someone needs to tell him he is not a shooter, but yet he plays shooting guard. Go figure.

    Comment by JR Ewing -

  36. No big surprise that Detroit’s used the fewest lineups. Not only do they avoid injury problems, but it looks like Larry Brown’s short rotation is holding over in the Flip Saunders era.

    I wonder what that means for whether they’ll be able to keep up the pace they’re playing.

    Comment by Jason -

  37. Interesting and helpful info
    Could you post the data as an excel file that can be downloaded which would be helpful for everyone to manipulate the data

    Comment by dan devasto -

  38. Mark,
    Sometimes I wonder how you became a billionaire when you have so much time on your hands…
    😉

    Some interesting stats, how would you assess the sport of baseball lineups?

    Comment by MIke -

Comments are closed.