Draft Room: Does Any Combine Drill Actually Predict NFL Success?
Packernet Podcast: Daily Green Bay Packers Podcast
AC Sports
4.7 • 524 Ratings
🗓️ 21 February 2026
⏱️ 40 minutes
🧾️ Download transcript
Summary
What if almost nothing at the NFL Combine actually predicts success? Ryan went deep into the data — correlating height, weight, 40 time, vertical, bench, broad jump, shuttle, and three-cone results against NFL career value scores — and the results are humbling. Almost every metric across every position lands squarely in the "noise" category. But what emerged from the frustration is a powerful new way to think about prospect evaluation.
- Position-by-position correlation breakdown reveals almost zero signal in any individual combine drill, with the 40-yard dash showing some of the weakest predictive value of all
- Surprising inverse correlations: why slower 40 times, lower verticals, and weaker bench numbers sometimes trend with more successful players — and what that actually means
- The offensive tackle vertical jump mystery: a negative .314 correlation that challenges everything we assume about explosiveness
- Ryan introduces the "Craftsman vs. Weapon" framework — why how a player uses their physical tools matters far more than the tools themselves, and how to think about "buckets" when evaluating prospects at the Combine
Stop chasing the shiny 40 time and start asking the real question: can this player actually use what he's got? Subscribe and leave a review to keep the draft content coming.
#NFLDraft #NFLCombine #PackersDraft #DraftAnalytics #GreenBayPackers #NFLScouting
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Transcript
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| 0:00.0 | Ladies and gentlemen, welcome to the Draft Room. This is the NFL Draft |
| 0:20.2 | Podcast of the Packernet Podcast Network. |
| 0:24.0 | If you'd like to call into the show, you can feel free to do so. The phone number here is |
| 0:27.2 | 608-561-33243. So the plan for today is going to get a little bit derailed. |
| 0:40.6 | Again, with the combine coming up, I want to make sure we're all, what the heck is that little symbol? We're all, oh, as up on the combine as |
| 0:47.9 | as humanly possible, right? So I do this every time, and it gets very, very annoying because in my mind, I want exact, like, I'm going to solve it. |
| 1:01.9 | You know, I'm going to solve the equation as though there is a way to solve the equation. |
| 1:07.0 | I'm going to find the perfect formula. |
| 1:09.1 | I'm going to run the perfect code. And we going to run the perfect code and we're going to |
| 1:12.5 | figure this thing out as far as the, you know, exact formula so that when somebody runs through |
| 1:21.4 | all the drills at the combine, I can tell you how good they're going to be based on X, Y, and Z. |
| 1:27.3 | There's several problems with that. And as I sat here and wasted a lot of time, |
| 1:31.2 | I shouldn't say wasted, but as I sat here, just going through it, it's like an annual |
| 1:34.8 | thing I need to go through where I just need to re-remember the goal and the situation |
| 1:41.1 | that we're in. |
| 1:42.9 | So it's actually very easy to get correlation, right? |
| 1:46.3 | I mean, the hardest part is finding a good value metric, |
| 1:49.1 | in other words, how good an NFL player is. |
| 1:52.2 | But then just taking all the players, |
| 1:54.8 | giving them all a value metric, |
| 1:56.1 | and then running that against all the combine data, |
| 1:59.8 | you can get correlations relatively easily. |
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