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Clustering Teams by PPP and Pace

http://apbr.org/metrics/viewtopic.php?t=8749

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Clustering Teams by PPP and Pace

Posted: Fri Nov 21, 2014 1:26 am
by BigLeagueInsights
I ran a k-means cluster (k=5) of all NBA teams using points per possession differential (ppp minus opponent ppp) and pace.

While the results are somewhat interesting, especially with Golden State getting their own cluster, I feel that pace dominates too much.

Anyone have any suggestions for other variables to use for clustering?

Here's what came out (apologies for the formatting, my bbcode skills are lacking):

Code: Select all

╔═══════════════╦═══════════╦═══════════╦════════════╗
║     Team      ║  Cluster  ║ PPP Diff. ║ Avg. Poss. ║
╠═══════════════╬═══════════╬═══════════╬════════════╣
║ Indiana       ║ cluster_0 ║ -0.009    ║ 92.1       ║
║ Miami         ║ cluster_0 ║ 0.018     ║ 91.7       ║
║ New York      ║ cluster_0 ║ -0.060    ║ 91.5       ║
║ Oklahoma City ║ cluster_0 ║ -0.058    ║ 92.7       ║
║ Utah          ║ cluster_0 ║ -0.037    ║ 91.6       ║
║ Golden State  ║ cluster_1 ║ 0.099     ║ 101.7      ║
║ Boston        ║ cluster_2 ║ -0.010    ║ 99.7       ║
║ Denver        ║ cluster_2 ║ -0.037    ║ 97.6       ║
║ Minnesota     ║ cluster_2 ║ -0.075    ║ 98.2       ║
║ Philadelphia  ║ cluster_2 ║ -0.160    ║ 98.9       ║
║ Phoenix       ║ cluster_2 ║ -0.005    ║ 99.8       ║
║ Sacramento    ║ cluster_2 ║ 0.004     ║ 98.5       ║
║ Dallas        ║ cluster_3 ║ 0.111     ║ 95.0       ║
║ Detroit       ║ cluster_3 ║ -0.048    ║ 93.2       ║
║ Memphis       ║ cluster_3 ║ 0.062     ║ 93.5       ║
║ San Antonio   ║ cluster_3 ║ 0.029     ║ 94.8       ║
║ Toronto       ║ cluster_3 ║ 0.100     ║ 95.0       ║
║ Atlanta       ║ cluster_4 ║ -0.008    ║ 95.8       ║
║ Brooklyn      ║ cluster_4 ║ 0.005     ║ 96.2       ║
║ Charlotte     ║ cluster_4 ║ -0.062    ║ 95.6       ║
║ Chicago       ║ cluster_4 ║ 0.048     ║ 96.2       ║
║ Cleveland     ║ cluster_4 ║ 0.022     ║ 95.7       ║
║ Houston       ║ cluster_4 ║ 0.051     ║ 95.3       ║
║ L.A. Clippers ║ cluster_4 ║ 0.019     ║ 96.6       ║
║ L.A. Lakers   ║ cluster_4 ║ -0.079    ║ 96.8       ║
║ Milwaukee     ║ cluster_4 ║ 0.000     ║ 97.1       ║
║ New Orleans   ║ cluster_4 ║ 0.056     ║ 95.6       ║
║ Orlando       ║ cluster_4 ║ -0.034    ║ 96.2       ║
║ Portland      ║ cluster_4 ║ 0.084     ║ 95.3       ║
║ Washington    ║ cluster_4 ║ 0.017     ║ 96.1       ║
╚═══════════════╩═══════════╩═══════════╩════════════╝

Re: Clustering Teams by PPP and Pace

Posted: Fri Nov 21, 2014 2:31 am
by Crow
Perhaps own and opp. PPP (as you had considered earlier) with or without pace. With pace might face some of same issues but maybe not or not as much as a three data point set?

Re: Clustering Teams by PPP and Pace

Posted: Fri Nov 21, 2014 1:42 pm
by DSMok1
First get the right number of decimals shown, then convert form Excel to unicode art here: http://www.sensefulsolutions.com/2010/1 ... table.html


I'd be interested in seeing clustering based on shot distance distribution (and/or shot type distribution), pace, and offensive rebounding percentage, effectively measuring offensive style.

Re: Clustering Teams by PPP and Pace

Posted: Fri Nov 21, 2014 7:43 pm
by BigLeagueInsights
As requested. With pace included, Golden State gets its own cluster. Without pace, the Sixers are in a world of pain and get their own cluster.

Without pace, Cluster 4 looks like "contenders," while cluster 2 stands out as teams with offensive firepower. Houston and San Antonio are strangely grouped with weak teams in cluster 1.

With pace

Code: Select all

╔═══════════════╦═══════════╦══════╦══════╦════════╗
║     Team      ║  Cluster  ║ ppp  ║ oppp ║  poss  ║
╠═══════════════╬═══════════╬══════╬══════╬════════╣
║ Indiana       ║ cluster_0 ║ 0.99 ║ 1.00 ║ 92.08  ║
║ Miami         ║ cluster_0 ║ 1.06 ║ 1.04 ║ 91.73  ║
║ New York      ║ cluster_0 ║ 1.05 ║ 1.11 ║ 91.54  ║
║ Oklahoma City ║ cluster_0 ║ 0.97 ║ 1.03 ║ 92.69  ║
║ Utah          ║ cluster_0 ║ 1.07 ║ 1.10 ║ 91.58  ║
║ Golden State  ║ cluster_1 ║ 1.07 ║ 0.97 ║ 101.70 ║
║ Boston        ║ cluster_2 ║ 1.07 ║ 1.08 ║ 99.70  ║
║ Denver        ║ cluster_2 ║ 1.04 ║ 1.08 ║ 97.64  ║
║ Minnesota     ║ cluster_2 ║ 1.04 ║ 1.11 ║ 98.20  ║
║ Philadelphia  ║ cluster_2 ║ 0.90 ║ 1.06 ║ 98.91  ║
║ Phoenix       ║ cluster_2 ║ 1.04 ║ 1.05 ║ 99.75  ║
║ Sacramento    ║ cluster_2 ║ 1.04 ║ 1.04 ║ 98.45  ║
║ Dallas        ║ cluster_3 ║ 1.15 ║ 1.04 ║ 95.00  ║
║ Detroit       ║ cluster_3 ║ 0.99 ║ 1.04 ║ 93.17  ║
║ Memphis       ║ cluster_3 ║ 1.05 ║ 0.99 ║ 93.50  ║
║ San Antonio   ║ cluster_3 ║ 1.00 ║ 0.97 ║ 94.82  ║
║ Toronto       ║ cluster_3 ║ 1.11 ║ 1.01 ║ 95.00  ║
║ Atlanta       ║ cluster_4 ║ 1.07 ║ 1.08 ║ 95.80  ║
║ Brooklyn      ║ cluster_4 ║ 1.06 ║ 1.05 ║ 96.18  ║
║ Charlotte     ║ cluster_4 ║ 0.98 ║ 1.04 ║ 95.58  ║
║ Chicago       ║ cluster_4 ║ 1.07 ║ 1.02 ║ 96.18  ║
║ Cleveland     ║ cluster_4 ║ 1.10 ║ 1.08 ║ 95.70  ║
║ Houston       ║ cluster_4 ║ 1.02 ║ 0.97 ║ 95.33  ║
║ L.A. Clippers ║ cluster_4 ║ 1.06 ║ 1.05 ║ 96.60  ║
║ L.A. Lakers   ║ cluster_4 ║ 1.06 ║ 1.14 ║ 96.75  ║
║ Milwaukee     ║ cluster_4 ║ 0.99 ║ 0.99 ║ 97.08  ║
║ New Orleans   ║ cluster_4 ║ 1.09 ║ 1.04 ║ 95.60  ║
║ Orlando       ║ cluster_4 ║ 1.00 ║ 1.04 ║ 96.23  ║
║ Portland      ║ cluster_4 ║ 1.10 ║ 1.01 ║ 95.27  ║
║ Washington    ║ cluster_4 ║ 1.03 ║ 1.01 ║ 96.10  ║
╚═══════════════╩═══════════╩══════╩══════╩════════╝
Without pace:

Code: Select all

╔═══════════════╦═══════════╦══════╦══════╗
║     Team      ║  Cluster  ║ ppp  ║ oppp ║
╠═══════════════╬═══════════╬══════╬══════╣
║ Philadelphia  ║ cluster_0 ║ 0.90 ║ 1.06 ║
║ Charlotte     ║ cluster_1 ║ 0.98 ║ 1.04 ║
║ Detroit       ║ cluster_1 ║ 0.99 ║ 1.04 ║
║ Houston       ║ cluster_1 ║ 1.02 ║ 0.97 ║
║ Indiana       ║ cluster_1 ║ 0.99 ║ 1.00 ║
║ Milwaukee     ║ cluster_1 ║ 0.99 ║ 0.99 ║
║ Oklahoma City ║ cluster_1 ║ 0.97 ║ 1.03 ║
║ Orlando       ║ cluster_1 ║ 1.00 ║ 1.04 ║
║ San Antonio   ║ cluster_1 ║ 1.00 ║ 0.97 ║
║ Cleveland     ║ cluster_2 ║ 1.10 ║ 1.08 ║
║ Dallas        ║ cluster_2 ║ 1.15 ║ 1.04 ║
║ New Orleans   ║ cluster_2 ║ 1.09 ║ 1.04 ║
║ Portland      ║ cluster_2 ║ 1.10 ║ 1.01 ║
║ Toronto       ║ cluster_2 ║ 1.11 ║ 1.01 ║
║ Atlanta       ║ cluster_3 ║ 1.07 ║ 1.08 ║
║ Boston        ║ cluster_3 ║ 1.07 ║ 1.08 ║
║ Denver        ║ cluster_3 ║ 1.04 ║ 1.08 ║
║ L.A. Lakers   ║ cluster_3 ║ 1.06 ║ 1.14 ║
║ Minnesota     ║ cluster_3 ║ 1.04 ║ 1.11 ║
║ New York      ║ cluster_3 ║ 1.05 ║ 1.11 ║
║ Utah          ║ cluster_3 ║ 1.07 ║ 1.10 ║
║ Brooklyn      ║ cluster_4 ║ 1.06 ║ 1.05 ║
║ Chicago       ║ cluster_4 ║ 1.07 ║ 1.02 ║
║ Golden State  ║ cluster_4 ║ 1.07 ║ 0.97 ║
║ L.A. Clippers ║ cluster_4 ║ 1.06 ║ 1.05 ║
║ Memphis       ║ cluster_4 ║ 1.05 ║ 0.99 ║
║ Miami         ║ cluster_4 ║ 1.06 ║ 1.04 ║
║ Phoenix       ║ cluster_4 ║ 1.04 ║ 1.05 ║
║ Sacramento    ║ cluster_4 ║ 1.04 ║ 1.04 ║
║ Washington    ║ cluster_4 ║ 1.03 ║ 1.01 ║
╚═══════════════╩═══════════╩══════╩══════╝
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