More NFL Draft Silliness…

While we wait for the 2011 season to be canceled, more words and tables about the 2000-2010 NFL Drafts and why the Steelers are so unbelievably awesome…

Just a few more odds and ends from my previous SL Time Machine post. Below is a table of each team’s CarAV by draft round from 2000-2010. Remember: as we approach 2010 the data become noisier and less reliable.

(Click on the table to make it bigger, readable. FYI: R_1 = round 1; rank_1 = team rank based on CarAV in first round; AVG = CarAV average for Rounds 1-7; AVG1_4 = CarAV average for Rounds 4-7; WIN_PCT = team winning percentage for 2000-2010. Finally, here’s the link to the data.)

A couple things…

The Ravens are the best team in the league at finding first-round talents throughout a draft. A quick glance at their CarAV-adjusted first-round hauls since 2000:

2000
Jamal Lewis (originally drafted 1.5, CarAV re-draft: 1.5)
Adalius Thomas (6.186, 1.12)

2001
Todd Heap (1.31, 1.27)

2002
Ed Reed (1.24, 1.2)
Anthony Weaver (2.52, 1.30)

2003
Terrell Suggs (1.10, 1.7)
Kyle Boller (1.19, 3.86)

2005
Mark Clayton (2.43, 1.22)

2006
Haloti Ngata (1.12, 1.2)

2007
Ben Grubbs (1.29, 1.22)

2008
Ray Rice (2.55, 1.3)
Joe Flacco (1.18, 1.5)

Not only does Ozzie Newsome do a swell job of identifying legitimate first-rounders, he’s also very good at unearthing top-32 talent after Round 1. (In looking at 11 drafts, Kyle Boller is the worst first-rounder, and he ends up being a third-round talent.) But the Ravens are among the league’s worst at getting value out their second-, third- and sixth-rounders, which sounds a lot like the criticism folks love to heap on Kevin Colbert.

Turns out, the Steelers are second behind the Ravens in finding first-round talent throughout the draft, and rank ninth, tenth and third in Rounds 2-4. Pittsburgh is 24th and 22nd in the fifth and sixth rounds, and 11th in the seventh.

Averaging Rounds 1-7, the Steelers rank fifth overall. In Rounds 1-4 they rank fourth, and 19th in Rounds 5-7.

Ultimately, the draft isn’t the be-all end-all. There’s also free agency, and perhaps most important (and most often overlooked): coaching. Historically, the Steelers are among the best in league in the former and the latter and rarely dabble in free agency, at least when it comes to breaking the bank for a proven player.

Feel free to add any other noteworthy nuggets from the table. In the meantime, pray that this lockout ends soon and enjoy the magic only Terry Bradshaw can bring to the silver screen (via PSAMP):

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  • EasyLikeSundayMorning

    This is awesome and I look forward to diving it in depth tonight. If AVG is of all 7 rounds, aren’t we ranked 5th after SD, NYG, NYJ and IND?

    • http://www.steelerslounge.com/ ryan

      Yep, you’re right. I’m an idiot. I originally averaged the CarAV ranks for each of the seven rounds instead of ranking the average CarAV. Now fixed.

      • EasyLikeSundayMorning

        No prob. By the way, the text says that says we’re 11th. Don’t beat yourself up over little things… This is great stuff.

  • EasyLikeSundayMorning

    This is awesome and I look forward to diving it in depth tonight. If AVG is of all 7 rounds, aren’t we ranked 5th after SD, NYG, NYJ and IND?

  • Anonymous

     Is the spreadsheet used to calculate this available on google docs like the last one? I want to give each team an “expected CarAV” based on where in each round they have been drafting and then divide the actual by the expected to see performance vs expectations.

    • http://www.steelerslounge.com/ ryan

      Guh. Forgot to do that too. Here ya go (and I’ll include the link in the post, too).

      • Anonymous

        Okay not done yet, but here’s what I have so far. The expected total value of all draft selections from 2000 through 2008 per team:
        “ARI” 1268.589894
        “ATL” 1219.658277
        “BAL” 1039.228579
        “BUF” 1126.481557
        “CAR” 1250.613664
        “CHI” 1171.318186
        “CIN” 1185.469139
        “CLE” 1271.631846
        “DAL” 1111.125691
        “DEN” 1039.593032
        “DET” 1214.869645
        “GNB” 1154.033542
        “HOU” 976.402928
        “IND” 1077.462169
        “JAX” 1181.725239
        “KAN” 1103.485925
        “MIA” 1011.49626
        “MIN” 1167.861439
        “NOR” 1094.619561
        “NWE” 979.375234
        “NYG” 934.510359
        “NYJ” 1018.251859
        “OAK” 1196.715704
        “PHI” 1175.361851
        “PIT” 1056.778825
        “SDG” 1203.676821
        “SEA” 1210.843972
        “SFO” 1347.701672
        “STL” 1202.3246
        “TAM” 1042.14018
        “TEN” 1313.3214
        “WAS” 1064.457509
        I picked 2008 because I didn’t think the more recent years would be useful. But now I realize I don’t have the AVG val available just through those years. Anyway, that avg / this value per team gives you a performance ratio for that team for value obtained with the picks they actually used (of course a team can get better total value or worse total value by trading picks, but this just tells you how well a team uses the picks at which it actually selects).

        • Anonymous

          Okay. I made the assumption that teams would have similar performances across the years. So I went ahead and just used the outcomes from 2000-2010 with the expected outcomes from 2000-2008. The number has no absolute meaning anyway. It’s just comparative. So here are the values for performance over expectations:

          NYG 0.0160639783895743
          NOR 0.0151261063486285
          NYJ 0.0151198015994754
          JAX 0.0147224588595537
          GNB 0.0141335094398652
          IND 0.0140377202311854
          BAL 0.0139216024762351
          SDG 0.0138736719275804
          SEA 0.0138040203361726
          CHI 0.0135744498719838
          PIT 0.0134967663633123
          ARI 0.0130494812885783
          TEN 0.0128651864312481
          DAL 0.0125964452151938
          NWE 0.012544497330542
          CAR 0.0121855737059366
          HOU 0.0119230246688563
          CLE 0.0118026348432319
          ATL 0.0117708101925619
          WAS 0.0116400737983129
          BUF 0.0114194926213273
          PHI 0.0112744650133616
          SFO 0.0107795025642949
          MIN 0.010635022728843
          CIN 0.0103017237584973
          DEN 0.0101356109772592
          MIA 0.00959017878832456
          OAK 0.00958234585576116
          STL 0.00883681155246318
          DET 0.00856673813377852
          KAN 0.00837571062193915
          TAM 0.0077910417551222

  • EasyLikeSundayMorning

    So, Colbert has been great in r1 and 4, good in 2, 3 and 7, poor in 5 and 6. I’ll take it…

    Eyeballing the data, I’d guess it would be very strong correlation between drafting strength is with winning percentage. Some teams, though, have either underperformed relative to their drafting strength (eg, the Jets) or overperformed (eg, the Broncos).

  • Anonymous

    Really hard to draw conclusions from some of this round-specific data.  Colbert was good in round seven?  That’s all on #99, no? Does this one pick prove anything you can generalize about.  I don’t think so. 

    Fact is, he has done way better with undrafted free agents than from rounds 5-7 combined. Does this mean he is great at UFAs or that he did badly for missing them in the draft and then got lucky because everyone else missed them as well. (Exception here is Willie Parker, because it seems no one else knew about him, so they could leave him undrafted knowing he’d be available.)

  • EasyLikeSundayMorning

    Ryan, this data seems like it has a lot of value and could be used in a variety of different ways.

    For example, this data could be used to create a new, better version of the famous Jimmy Johnson draft value chart. It could then also be used to evaluate trades to see how much teams underpaid or overpaid relative to the expected value of the slots swapped. Trades could be evaluated when they happened (eg, much did the Browns get in the trade with the Falcons, and Julio Jones needs to be as good as X (Randy Moss or whatever the comparable CarAV value is for that draft slot) to make the trade worthwhile). And it could be used to evaluate trades from the past (Troy and Ricardo needed to perform X and Y and they actually performed at A and B).

    Also, as much as I love the SL focus on the Steelers, if framed the right way (title, content, SEO keyword tags, etc.), it could be excellent linkbait, driving traffic from fans of and writers for all teams who are interested in how well their teams drafted and made draft trades.