Last Year’s Sacks don’t predict Next Year’s Sacks

But Hurries do

It’s been a few years since the analytics community taught us sacks shouldn’t be the “end all, be all” metric for pass rushers. Yet  many still fall for the trap. Even NFL teams, and their GMs, those who are paid (alot and solely) to select good players for their team, continue to “pay for sacks”. This stupidity offers us an opportunity to take advantage and profit.

Diving into this topic more in depth, in “Pass Rushing Slugging Percentage” we explained that the “last step in a chain/sequence” is never as consistent/predictive as the first/initial step(s). Imagine you were predicting home runs, and think through the “chain of events” a hitter must accomplish to complete the feat:

  • Make contact with the ball (not whiff/k)
  • Swing with enough power (usually measured by exit velo)
  • Have the correct trajectory (measure of the swing angle) 
  • Hope that the ballpark he’s hitting in, has small enough dimensions for the ball to get over

In other words, with an “extreme” or “absolute” stat, there are typically many steps that need to be completed beforehand. And given the very nature of variance in sports, the first steps are almost always going to be more consistent than the raw “absolute number”. The same goes for sacks.’ 

We’ve been preaching how much pressures should be used as a much better “success indicator” for a pass rusher, is a story for another day. Today, we are simply going to look at how we can profit on its predictive ability based on this very clear phenomenon. 

Take a look at the last 4 seasons, and how Year (n)’s sacks relate to Year (n-1)’s pass rushing numbers.

*Note data was limited to players with 24 pressures within one season.

As you can see total sacks, or really any form of sacks only predict about 20% of next season’s sack numbers for an individual pass rusher. However, Pressures, or better yet, pressure rate is more than twice as correlated. Not only are pressures a better performance metric, they are a hidden gem in regards to predicting how sack totals may rise or fall in the following season. 

Looking at how much a pass rusher turns his pressures into sacks is called the conversion rate. Historically, we’ve found the average pass rusher “converts” about 16% of pressures into sacks. With that said, over the last four years, looking at the upper and lower quartiles (those that converted >24%, and <8% conversion rates the season prior) we see some stark predictive value in which way sack totals move in the ensuing season.

Pass Rushers that exceeded 150% expected sack conversion (Sacks / Pressures), and what their net sack rate and totals were the following season (>24% Pressures converted into Sacks in n-1 year):

PlayerSKSK %pSSN SKpPRESSpPRESS%pconvpssn sk %Net Sk% Nxt SsnNet Sk Nxt Ssn
Julius Peppers52%11278%41%3%-2%-6
Erik Walden42%113010%37%4%-2%-7
Danielle Hunter71%134311%29%3%-2%-6
Jordan Jenkins21%8289%29%3%-2%-6
Vic Beasley Jr52%165513%28%4%-2%-11
Von Miller82%155312%27%3%-1%-7
Denico Autry41%93310%27%3%-2%-6
Mario Addison113%103512%27%3%-1%2
Jamal Adams1010%72430%27%8%2%3
Bruce Irvin93%72410%27%3%0%2
Matt Ioannidis92%82811%27%3%-1%1
Jason Pierre-Paul92%13479%27%2%0%-4
Nick Perry72%114212%26%3%-1%-4
Chandler Jones193%135010%26%3%1%6
Julius Peppers113%8298%26%2%1%4
Lorenzo Alexander32%134916%26%4%-2%-10
T.J. Watt153%145513%25%3%0%1
Ifeadi Odenigbo41%72811%25%3%-2%-4
Justin Houston82%114410%25%3%0%-3
DeForest Buckner82%124810%25%2%-1%-5
Jonathan Allen62%8327%25%2%0%-2
Jordan Jenkins83%72810%25%3%0%1
Sam Hubbard92%6247%25%2%0%3
Cameron Heyward82%124811%25%3%-1%-4
Chris Jones92%166313%25%3%-1%-7
Frank Clark92%104110%24%3%-1%-1
Benson Mayowa62%72913%24%3%-1%-1

In other words, those that vastly out “convert” pressures into sacks in the previous year average about 3 less sacks the next year.

On the flip side, the “unlucky” pass rushers that converted 50% of the expected sack conversion, saw the following changes to their sack total the next year (<8% conversion rate in n-1 year).

PlayerSkSk %pSSN SKpPRESSpPRESS%pconvpssn sk %Net Sk% Nxt SsnNet Sk Nxt Ssn
J.J. Watt50.90%45017%8%1%0%1
Allen Bailey61.14%2257%8%1%1%4
DeMarcus Lawrence6.51.86%56315%8%1%1%2
Leonard Floyd10.52.29%33810%8%1%2%8
Samson Ebukam4.51.93%33814%8%1%1%2
Brandon Graham8.51.75%45110%8%1%1%5
Maliek Collins30.95%2.5348%7%1%0%1
Vinny Curry30.88%2.53412%7%1%0%1
Tarell Basham3.51.00%22810%7%1%0%2
Ndamukong Suh61.15%2.5366%7%0%1%4
DeForest Buckner122.38%3459%7%1%2%9
Ezekiel Ansah124.05%23110%6%1%3%10
Tom Johnson20.45%2319%6%1%0%0
Adrian Clayborn41.33%2.54316%6%1%0%2
Sheldon Richardson10.27%1.5266%6%0%0%-1
Sheldon Rankins81.92%2357%6%0%2%6
Leonard Williams51.00%24610%4%0%1%3
Romeo Okwara102.51%1.53711%4%0%2%9
Sheldon Richardson4.51.11%1277%4%0%1%4
Kerry Hyder8.52.05%13011%3%0%2%8
Leonard Williams11.52.40%0.54310%1%0%2%11

The underperforming sack converters typically add 4 raw sacks the next year. To summarize, that’s a 7 sack swing between those that outperformed their conversion rates, and those that underperformed. 

Knowing this, here is a list of those >24% / <8% converters from the 2020 NFL season, and what we can expect for 2021 sack futures:

PlayerPass RushesSolo SacksAst. SacksComb. SacksUnblocked SacksHurriesHitsKnockdownsPressuresconvExpected 21
Devin White1069095131472733%6
Haason Reddick38812112.52242264627%9.5
Dre’Mont Jones337616.5013842427%3.5
Denico Autry395717.5122823025%4.5
Trey Hendrickson33013113.512330115425%10.5
Myles Garrett467112120252274924%9
Za’Darius Smith51512112.503125115224%9.5
Jordan Jenkins268122019123268%6
Shaq Lawson3214040273915538%8
William Gholston3523030203017408%7
Cameron Heyward4793240333813547%8
John Franklin-Myers3323030282311427%7
Clelin Ferrell258202018148297%6
Al-Quadin Muhammad361202022154307%6
Robert Quinn324202019166316%6
Sam Hubbard345202023219316%6
Tyus Bowser2282020222212336%6
Marcus Davenport227111.5121157276%5.5
Jonathan Allen4491220162711375%6
K’Lavon Chaisson312101019128264%5
Arden Key2740000162111270%4

If any player in the green section’s sack total number is under, hit the over strong. Vice versa for those in red. As soon as individual sack futures are listed, we’re going to hammer them using logic.

3 thoughts on “Last Year’s Sacks don’t predict Next Year’s Sacks

  1. Pingback: FPS Posts

Leave a Reply