We are less than two weeks(!) away from the NFL Draft and the mocks are flowing. But what does it all mean? How can you possibly know what player goes to what team or what drafting philosophy a team employs? For that reason, I created BANE (Best Available Need Evaluation).
So far I have taken deep dives into the 2014, 2015, and 2016 draft classes. I’ve scoured multiple sources for any insight I could gain on what constituted a top consensus need for each team. I’ve looked at player ages, contract lengths, depth charts, stats, and the list goes on and on. Essentially, what started as a glimmer of intellectual curiosity, has ballooned into a massive undertaking. There is enough underlying raw data to fill my own grave, which is where I thought I would end up before I finished, and really, I’ve only just begun.
Here’s how the BANE formula works:
- Each draft pick is assigned a value, which decreases with each subsequent pick. So, for instance, a round one 4th overall selection is going to weigh more than a round one 10th overall selection.
- Each round is weighted further to reflect a scale more in line with a draft value chart that teams use for trades, but my formula is not as stringent on later rounds.
- The rounds used for this are RD1-RD4, as spending a 6th round pick on a need is not necessarily addressing that need. I have data for rounds 5-7, but their weighted value counted for so little that when I compared both versions of a 2016 next to each other, the needle barely moved.
- Consensus needs are what I could gather from a number of sources and my own independent research. If you feel I have misconstrued a need, feel free to reach out and I’ll try to explain my reasoning. Don’t though, that’d be cool too.
- DL and OL designations can be either for all positions along the line or a specific position. I tag these in my underlying data to ensure that I’m not assigning a “hit” for a Center when Tackle was the real hole.
- To the best of my ability, I have tried to ascertain the position the player was drafted to play, not the position listed next to their name at the time they were drafted. A good example of this is the Steelers’ Safety Sean Davis, who was listed as a Cornerback when drafted. He would count as a Safety in my findings.
- Each team amasses a total value for available draft capital and “hits” are added to the drafted value. This is how the final percentage is determined.
You can find my findings and analysis from 2015 and 2016 via the following links:
Now that I’ve added 2014 to the database, here are the meat and potatoes:
Yes, I know, you probably want a more basic view, so let’s take those three years give an overall breakdown. Note: An asterisk (*) denotes a team had at least the same General Manager or Head Coach for the entirety of the study.
The first thing that popped out to me is the trend of 1st round value spent on a consensus need. 2014 saw 24 hits, 2015 and 2016 each saw 25 hits. This leads me to believe that you can expect 7-8 teams to take a player that lands beyond the realm of consensus need. Of the qualifying teams (remember the asterisk), so far the data suggests that those teams are more likely to include the Cardinals, Packers, Bills, Colts and Rams. But I will dig into that on the next installment.
The top 4 qualifying teams (DEN, MIN, SEA, HOU) all came in above league average for the each of the years researched. They also picked a “need” 11 out of 11 times in RD1 11 out of 11 times. Let’s take a deeper dive into the how and why of the top four teams:
DENVER BRONCOS (86.67%)
In 2014 their needs were CB, WR, OL*, LB. These were addressed by drafting OSU CB Bradley Roby (1.31), IND WR Cody Latimer (2.24), MICH OT Michael Schofield (3.31). Even if you go beyond the RD1-RD4 range, they added LB twice to hit a BANE Grand Slam and added a center in RD6.
When Gary Kubiak took over in 2015, the OL need repeated due to Kubiak’s zone running attack. This was addressed in RD2 when they took CSU OT Ty Sambrailo (2.27), whose athleticism fit a zone scheme. With DeMarcus Ware turning 33 years old, the Broncos took MU EDGE Shane Ray (1.23). They followed up by addressing another hole in their offense with OSU TE Jeff Heuerman. The asterisk on their OL need was due to a specific need within, namely at OT, and UF G Max Garcia (4.34) was not considered a top need and therefore kept them from repeating their 100% hit rate from the year before.
The 2016 offseason saw Peyton Manning retire and Brock Osweiler landing a big contract with the Houston Texans, and the glaring hole on the roster is, without question, Quarterback. The Broncos continued their trend of RD1 hits by taking MEM QB Paxton Lynch (1.26), and followed up by taking GT DT Adam Gotsis (2.32) to lessen the blow of losing Malik Jackson in free agency. Safety was considered as a possible need, but not a top one, therefore BC Justin Simmons (3.98) was not considered a hit, and with an OL need (Tackle/Guard) they just missed on another hit when they took MU OG Connor McGovern (5.5) outside of the RD1-RD4 range.
When mocking the Denver Broncos, chances are high that they will address glaring holes early, often and late. Nearly every expert has mocked Utah OT Garett Bolles to the Broncos with the 20th overall pick, and given their drafting history, there’s overwhelming evidence to suggest that OT will be on their radar early.
MINNESOTA VIKINGS (86.57%)
With an extra RD1 pick in the three years observed, quantity of early selections did not deter the Vikings from hitting their needs 4 out of 4 times. In ’14 they hit with UCLA EDGE Anthony Barr (1.9) and LOU QB Teddy Bridgewater (1.32). In ’15 MSU CB Trae Waynes (1.11), UCLA ILB Eric Kendricks (2.13), LSU EDGE Danielle Hunter (3.24) and PITT OT TJ Clemmings (4.11) all hit, resulting in a 100% BANE score.
In ’16, they scored yet another 100% (the only team to have multiple max value used twice) by hitting on Ole Miss WR Laquon Treadwell (1.23), CLEM CB Mackensie Alexander (2.23), and WMU OT Willie Beavers (4.23). CB was a debatable need, but Terrence Newman was turning 38 years old and Captain Munnerlyn was on the last year of his contract and expected (rightfully) to be gone by the next offseason.
On the heels of consecutive 100% BANE scores and an offensive line with several upgrades needed, you can expect the Vikings to attack the position with their 2nd round pick. They also have a decision to make regarding inconsistent DT Sharrif Floyd, who is on his $6.75 fifth-year rookie option. He only played one game last year and how the Vikings address their defensive line depth in the draft this year could be a sign of how they deal with Floyd next offseason.
SEATTLE SEAHAWKS (83.62%)
The Seahawks have a limited sample size regarding first round value spent, only possessing one RD1 in the last three years, but that lone pick hit in ’16 when they selected TAMU OT Germain Ifedi (1.32) after losing Russell Okung in free agency.
Looking back, ’15 saw them hit 100% by landing needs on all four of their picks. Adding inexpensive depth at DL was considered a consensus need in part due to DT Brandon Mebane’s upcoming departure, this was addressed with UM DL Frank Clark (2.31).
Coming into the draft, they had a repeating need at WR partially due to ’14 RD2 pick WR Paul Richardson posting some pedestrian numbers in his rookie debut (29-271-1). Having no WR catch for more than 825 yards the previous season they went for a difference maker and found one in KSU WR Tyler Lockett (3.5). Lockett doubles as a return man which was not considered a consensus need but with the previous return man WR Bryan Walters leaving for Jacksonville that offseason, Lockett’s selection only helps to identify him as a hit.
The Seahawks struggles along the offensive line has been well documented, but it’s not for a lack of trying. In ’15 they added SDSU OG Terry Poole (4.31) and WVU OG Mark Glowinski (4.35). In total they have had a need at OL all three years and have drafted five linemen to try and address their deficiency.
Looking beyond the RD1-4 range, they continued to hit, adding Towson CB Tye Smith and two more defensive linemen.
When forecasting what the Seahawks will do during the draft, it’s important to note that of their 10 total consensus needs over the last year, they have spent 11 picks and a considerable amount of draft capital on those positions.
HOUSTON TEXANS (83.40%)
It would be easier to point out the Texans drafting outside of consensus need than to note all the hits, as they rarely deviate until the 3rd round. Those picked outside of need from RD1-4 include ’14 selection UI TE CJ Fiedorowicz and ’15 selection SJSU RB Tyler Ervin.
The Texans have attacked WR holes frequently, drafting 3 in the past two years, so I would expect them to address their defensive backfield next with CB A.J. Bouye and S Quinton Demps leaving for greener (bad pun) pastures. The team has brought in USC CB Adoree’ Jackson and NCST S Josh Jones in for official visits.
They also have a hole at right tackle after losing Derek Newton to injury last year when he tore both patellar tendons. Chris Clark stepped in for him and struggled mightily. It’s worth noting that when I studied the league wide correlation of official visits and interviews leading to drafted prospects in the 2014 draft, the Texans scored 4th highest. So far they have touched base with OTs Julie’n Davenport, Dan Skipper, Taylor Moton, Ryan Ramczyk, Cam Robinson, Garett Bolles, Brad Seaton, Avery Gennesy, Sam Tevi, Dimitric Camiel, and Dieugot Joseph.
It’s my personal belief that the Texans are higher on QB Tom Savage than what the public thinks, so barring a wildcard pick at Quarterback, expect the Texans to invest a significant portion of their draft capital on their defensive backfield and offensive line.
WHAT TO EXPECT…
In future installments, the next of which will be finished before the draft, you can expect breakdowns of low percentage BANE teams along with write-ups similar to the top teams I talked about in this installment. I’ll also be sharing some insight on repeating needs for teams and whether they repeated due to “hits” or lack there of. I’ll also attempt to identify certain position trends for teams and see if this new information jives with their investment charts.
But for now, you’ve got the basic data to help guide you on your next mock. If you have any questions or suggestions, hit me up on Twitter (@MichaelJKist), I’d love to hear from you… maybe.