Post by Speedman on Mar 4, 2024 15:15:47 GMT -5
In terms of the mental aspect and the personality, players like Williams and Rattler concern me. The idea of Williams having to answer to the NY media after multiple losses doesn't seem like a good fit.
I'm also a bit concerned with Daniels frame and style of play. With his skill set, I can see him stepping on the field day-1 for any team and immediately making them playoff contenders. With his frame and propensity to take big hits, I can just as easily see him missing the majority of the season with injury.
That said, saying this class is on par with the 2015 class seems like a stretch. Honestly, it's kind of absurd. I had to go back and look, but here are the QBs drafted in 2015.....
- Jameis Winston
- Marcus Mariota
- Garrett Grayson
- Sean Mannion
- Bryce Petty
- Brett Hundley
- Trevor Siemian
- Taylor Heinicke
Beyond a few career backups, 2015 was horrible. I don't recognize half of the names on that list. Without doing research, I'd imagine it's one of the worst QB classes in the 2000's.
With your algorithm, is it 100% based on stats, metrics, etc., or is film review also taken into consideration?
Historically pick 17 has produced 24 players. Percentages are rounded.
1 QB 4%
0 RBs
2 WRs 9%
0 TEs
3 OTs 13%
3 OGs 13%
0 Centers.
2 DTs 9%
4 ILBs 17%
3 Edge/ OLB 13%
3 CBs 13%
2 Safeties 9%
0 Punters
I Kicker 4%
0 Long Snappers
24 players drafted. Rounded It comes to 104%.
My algorithm is based on 3 main logical arguments. With some subcategories. All with a weight attached to them.
I am doing this as a Write.
A) The history of the pick:
I just showed the history of the pick (last year a corner was taken with 17). 13% is one corner taken every 8 drafts. Most likely a corner will not be taken this year.
It calculates every position's probability based upon when the position was last picked. It also looks at the 2 picks on either side of it. (bell curve / wave function effect)
Example OLB/ Edge is 22% on pick 16 and 26% on pick 18. It also averages the history those picks on when that position was last picked as well.
Then calculates that into the probability of Pick 17 also.
B) Need as it applied to pick:
This year pick 17 belong to The Jags. (most likely not accurate because FA has not taken place yet) But
The Jags main needs are interior O-line, Interior D-line Edge Corner depth WR depth.
A corner can be counted out just because of need and a corner was taken in last year's draft with pick 17. Most likely a Center also. Rarely taken in the 1st.
That leaves OG, DT, Edge.
An Og was taken in 2022 with 17.
2019 Dex was taken with 17
By this I would predict Edge
C) Is the player and the position in the wheelhouse and consensus:
Is there a player ranked high enough at 17 that fills a need? Consensus is what are the pendants saying about those players draft status.
I have 2 Edge Rushers in my wheelhouse at 17
Jared Verse, I have ranked at 16
Laiatu Latu, I have ranked at 19
What the pundits are saying:
www.nflmockdraftdatabase.com/players/2024/laiatu-latu/page/1.html
Laiatu Latu Average mock draft pick 16.
www.nflmockdraftdatabase.com/players/2024/jared-verse/page/1.html
Jared Verse Average mock draft pick 15
There are a few more lesser metrics I use for tie breakers.
Without running my algorithm, I would predict the Jags select Laiatu Latu with pick 17. It fits most of the criteria. This is pre-FA. The needs may change after it is finished.
This is the basics on how my draft predictability functions.
I hope someday to be 60% on position taken.
40% on player taken.
That beats every Mock draft ever published.