To keep the research aspect of SEMTEX as objective as possible, I will talk about my opinions on the 2017 passers and what this means to me as an evaluator on Twitter. But remember: 96.1 percent of starter-level quarterbacks since 1983 have been Gold or Silver passers. Every Super Bowl-winning starting QB drafted since 1983 has been a Gold passer. There has never been an All-Pro Bronze QB in the SEMTEX era.
Here are the 2017 SEMTEX results:
Even if you think one of the 2017 Bronze passers is going to hit, the ones that have before haven’t even been worth a first-round pick. The Impact Score for the Bronze group comes right between the draft-capital value of the 32nd and 33rd pick, according to the MAVEM Draft Chart, so keep that in mind with bigger-name Bronze prospects like Deshaun Watson and Davis Webb.
SEMTEX is not an end-all, be-all system, but rather a new piece in the ever important quarterback-evaluation puzzle, highlighting which QBs have the highest and lowest chances of outperforming their draft slot, and becoming starters based on their enhanced production.
As we discussed, just because you are in the Gold bucket doesn’t mean you will be good NFL QB. But to be successful at the next level, you clearly need to be in the Gold group or in the Silver one with top level arm talent or mental processing skills to pair with it, or the deck is stacked against you. And when paired with other parts of the NFL draft process, such as evaluating a player’s translatable traits on tape, determining scheme fit, checking to see if prospects have baseline physical size and athleticism measurables as we put them through interviews and medical checks to eliminate undesirable Gold prospects, SEMTEX should become even more effective in application.
Even just applying Slaytics results to the Gold group to root out passers that don’t have baseline macro measurables, the corresponding starter percentage and success rate both jump up another 4 percent each.
As mentioned before, raw production on its own is not valuable in player evaluation. But, there is clearly something to utilizing Situationally Enhanced Metrics for predictive purposes. The whole point of this framework was to discover what aspects of “production” have been actually historically important, and to see just how effective those aspects are on a macro scale. It’s not about using production to create a Big Board, but rather eliminating prospects who don’t have the baseline production to be successful and highlighting ones with the best chances.
Being able to grasp and contextualize the relative importance of information available to you is obviously valuable in determining its usage, and that is what research like this does. In the future, I may analyze other positions as well, as even if they don’t work as well as this, knowing how important production is at each position is valuable intel.
I certainly didn’t expect anything close to this level of effectiveness from something production-based coming in, but the results over a 34-year period speak for themselves. It’s clear that enhanced production can be a powerful predictive tool at QB, and NFL teams curious about optimizing production, or looking to increase their odds of hitting at the quarterback position in the draft, should consider SEMTEX as a vehicle for doing so.