Super Bowl LVI Preview: An Analytical Guide to Sunday's Big Game

There are always plenty of storylines to study up on before a Super Bowl contest -- narratives, past matchups, franchise trends -- and I sure love digging into those in the lead-up to the game, but I think my favorite part of Super Bowl prep is the extra time and attention we can place on the game.

That week off to research? It's glorious.

According to FanDuel's Online Sportsbook, the Los Angeles Rams are 4.0-point favorites over the Cincinnati Bengals in Super Bowl LVI.

The over/under is 48.5 points.

Throughout this piece, I'll often be referencing numberFire's Net Expected Points (NEP) metric. You can read about NEP in our glossary, but if you're entirely new to an expected points model, don't worry. Just think of it like this.

While gaining 4 yards on 3rd-and-2 isn't a huge play from a yardage standpoint, it is a positive offensive play that will increase a team's chance to score points on that drive. A 10-yard gain on 3rd-and-15 isn't really increasing scoring chances, and the yardage is misleading.

Every incremental increase and decrease on each play is tallied up for teams and players in our database. That's NEP, and it's how we define and rank teams and players at numberFire.

I'll also reference NextGenStats' and nflfastR's Expected Points Added (EPA) models, as well.

Game Snapshot

Here's how each team ranks in opponent-adjusted offensive and defensive efficiency across the main categories, via numberFire's NEP model.

NEP Ranks
Los Angeles 6 2 28 4 10 7
Cincinnati 15 12 21 12 14 13

Some things that jump out and make a nerd like me happy: both teams are top-12 in adjusted passing offense while boasting rushing offenses that are outside the top 20 in the NFL. The run games aren't what got them to the big game.

Meanwhile, both sides are solid defensively with top-12 overall units.

But I want to go a tad deeper than this.

Here are some of the most interesting tidbits I can find that might affect this game.

Joe Burrow Against Pressure...But Also Matthew Stafford

A huge question mark leading into Super Bowl LVI is going to be Joe Burrow's time in the pocket.

We all know that he was sacked nine times against the Tennessee Titans in the divisional round but then took just a single sack against the Kansas City Chiefs in the AFC Championship.

What might we expect this week?

On the full season -- including playoffs -- the Rams rank just 21st in pressure rate generated, according to NextGenStats. That's not too worrisome.

Notably, they've had a 26.9% pressure rate since Week 10 with Von Miller joining the team. Before that, their rate was 27.9%. Hmm.

Did their blitz rate change? It did.

Since Miller joined the team, the Rams' blitz rate has been 27.6%, down a tick from 29.4%, so that could explain the partial drop-off in pressures while attaining better downfield coverage.

Either way, yes, we can still be concerned that the Rams can generate pressure on a weak offensive line, so how does Burrow fare against pressure?

Here are Burrow's splits in some key metrics against teams of various pressure ranks.

Time Sack
Top 5 34.3 63.6% 260.0 1.5 0.5 8.8 0.10 0.06 2.74 10.5%
11 to 20 29.9 64.3% 243.3 2.1 1.1 7.6 0.01 0.04 2.64 7.5%
21 or Worse 35.4 65.2% 338.8 2.1 0.8 8.1 0.14 0.08 2.70 9.3%

Overall, it's pretty stable.

Yes, the yardage ticks way up against weaker pressure teams, but he has solid raw EPA and EPA over expectation (via NextGenStats' model) splits even against top-five pressure teams. His time to throw was actually highest against top-five pressure teams.

The sack rate is its own conversation, so he'll need to do well not to take sacks that could be avoided.

According to ProFootballFocus, 26.0% of pressured dropbacks on Burrow have led to sacks, the third-highest rate among 27 qualified passers this season. Last season, his pressure-to-sack rate was 21.9%. It's a tendency he'll have to shed this weekend.

Speaking of pressure, though, the Bengals might need to pressure Matthew Stafford because, well, check out how similar Stafford and Burrow have been when pressured and when throwing from a clean pocket.

Not Pressured Pressured
Matthew Stafford 0.40 (1st) -0.46 (16th)
Joe Burrow 0.33 (4th) -0.51 (19th)
NFL Average 0.18 -0.52

The Bengals' offensive line will be a big talking point, but the conversation should go the other way, as well.

Cincinnati ranks seventh in pressure rate this season. Stafford has been sacked on 17.5% of his pressured drop backs, basically the league-average rate.

Pressure generation rates could be substantial from both defenses, as a result.

It'll be up to Burrow to avoid sacks as well as Stafford -- and for the Bengals to get to Stafford and disrupt his great clean-pocket splits.

Downfield Throws

With the downfield prowess of Ja'Marr Chase, it might feel as though the Bengals have been the more prolific team in terms of deep passes.

That's not the case.

Stafford has averaged 6.3 downfield attempts (passes traveling at least 16 yards downfield), ranking him 10th in the NFL. Burrow averaged 5.4 per game (18th).

If viewed by average depth of target, Stafford (8.1) bests Burrow (7.5) there, too.

The more aggressive downfield team has been the Rams.

This split will seem small (and the league average is only 8.0%), but on early downs in game situations during which the offense had between a 20% and 80% win probability (via nflfastR's model -- to remove garbage-time heaves and clock-milking rushes), the Rams have dialed up a downfield pass play on 10.6% of offensive plays.

The Bengals were actually dead average at 8.0%.

The next question is efficiency.

This season (including playoffs), Burrow generated 1,610 yards, 16 touchdowns, and 8 interceptions on downfield passes. That was good for 0.92 Passing NEP per drop back. That rate ranked him second among 30 quarterbacks with at least 50 downfield passes this season.

Stafford on downfield throws: 1,879 yards, 9 touchdowns, 10 interceptions, and 0.77 Passing NEP per drop back. That ranked him fourth.

But hasn't Stafford's downfield passing been worse in the playoffs?

Yes and no.

Stafford is actually maintaining 1.46 Passing NEP per attempt on downfield throws (16) this postseason, though Jaquiski Tartt could've changed that easily. Point being: the downfield woes are exaggerated, according to the data.

Notably, in the postseason, Burrow is 6 of 12 for 156 yards, 0 touchdowns, and 1 interception on deep passes.

That's not really what the narrative would have us think, so it's an interesting bit of information.

But, sure, overall the Bengals have the more lethal downfield threats with Chase and Tee Higgins, right? Not quite.

Cooper Kupp and Van Jefferson have been downfield studs in terms of Target NEP per target, which shows all NEP gained and lost when these players were targeted.

Here are their downfield stats and ranks among pass-catchers with at least 20 downfield targets this season.

Team Catches Targets Yards TD Target NEP/
(of 54)
Cooper Kupp LA 25 42 794 4 1.13 7
Ja'Marr Chase CIN 21 44 682 8 1.00 11
Van Jefferson LA 13 31 464 2 0.81 19
Tee Higgins CIN 14 29 420 2 0.75 23

Boy, Cooper Kupp is good.

And in case you're wondering, Odell Beckham has caught 6 of 17 downfield targets for 174 yards and a touchdown with the Rams.

So, limiting pressure could lead to lining up the downfield pass, and both quarterbacks excel in that area despite the possible consensus that Burrow has a big edge in this area.

The Slot Machine

We can always look for X-factors in the Super Bowl. Players who play above expectation and cause matchup nightmares for the opponent.

One position that usually comes to mind for me to examine is the slot receiver.

That's a little different this year with Kupp in the mix.

For the Bengals, they'll be running Tyler Boyd primarily from the slot.

This season (including playoffs), Kupp (as expected) leads all players in slot yards with 1,549.

Boyd ranks fourth with 826; excluding tight ends, Boyd is second.

Notably, Boyd's average route depth from the slot was 11.0 yards, via NextGenStats. That ranks him fifth among pass-catchers with at least 50 slot targets.

He's not a mere slot receiver within this offense.

According to ProFootballFocus, the Bengals have allowed 7.33 yards per target to the slot this season (just a tick above the NFL average of 7.21). The Rams ranked 8th-best in yards per target allowed (6.76) to the slot.

Of course, Kupp is more than a mere X-factor, but Boyd could be a real difference-maker within this game if he can break free from a better-than-average slot defense.

Do the Weak Run Games Matter?

As mentioned, neither team ranks inside the top 20 in adjusted rushing efficiency via numberFire's metrics.

However, you gotta establish the run, right? After all, over the past five Super Bowls, the team that had more rushing attempts is a perfect 5-0!

Well, you know what else? Teams with more Total Net Expected Points earned won all 5, too, and the more efficient passing team by Passing NEP is 4-1.

The better passing team that lost? That happened when the Kansas City Chiefs (0.91 Passing NEP) beat the San Francisco 49ers (1.32) in Super Bowl LIV.

And I think we could say the Chiefs' passing game helped them win that game while the 49ers' didn't.

These offenses should go as the passing offenses go.

Special Teams

Special teams often get overlooked through the regular season, and the magnifying glass comes out for the Super Bowl.

Here's how each unit fared in Special Teams NEP on the season.

Special Teams
NEP (Rank)
Offensive Defensive Total
Cincinnati 42.4 (4) 7.9 (6) 34.5 (6)
Los Angeles 52.5 (2) 46.5 (31) 1.8 (14)

This is something fun.

Both teams have pretty explosive and successful special teams units offensively.

The Bengals do well to stymie returns: they're top-10 in yards per return allowed on both kickoffs and punts. The Rams have been a bit susceptible on punt returns (they're sixth-worst in yards per return allowed).

But, of course, we have to talk about kickers Evan McPherson and Matt Gay in more detail.

Here are their Field Goal NEP and Field Goal NEP per attempt ranks among 28 kickers with at least 20 attempts this season (including playoffs).

Field Goal
Field Goal NEP
per Attempt
Evan McPherson 42.0 (1) 0.93 (2)
Matt Gay 20.4 (10) 0.74 (14)

Money McPherson earned the nickname this year for sure. He has not only the ice-cold demeanor but also the stats to back it up.

McPherson (0.08) also ranks fourth in field goals over expectation per attempt among this same sample, according to nflfastR's field goal probability metrics.

Gay (0.04) once again is near the sample average (13th).

The punters -- Johnny Hekker for the Rams and Kevin Huber for the Bengals -- have virtually league-average punting stats.

Hekker has averaged -0.12 EPA per punt (the NFL average is -0.13). Huber's at -0.14.

Analytically Comparable Teams

At numberFire, we can dig into our database (back to 2000) and see which historical teams are most similar to current teams.

Here are each team's top-five comparable squads and their results.

Result Bengals
2010 Chargers Missed Playoffs
2016 Chargers Missed Playoffs
2011 Cowboys Missed Playoffs
2008 Bears Missed Playoffs
2012 Broncos Lost Divisional Round
2014 Cardinals Lost Wild Card
2003 Titans Lost Divisional Round
2002 Steelers Lost Divisional Round
2017 Vikings Lost NFC Championship
2019 Rams Missed Playoffs

Here's a closer look at the Rams' comps.

NEP Ranks
Team Total
2021 LAR 6 2 28 4 10 7
2010 LAC 8 2 27 3 1 11
2011 DAL 11 5 27 19 18 9
2012 DEN 10 6 22 2 3 7
2003 TEN 9 3 26 9 12 14
2017 MIN 8 5 22 2 2 6

Elite passing offenses and bad rushing offenses with mostly elite defenses. That checks out.

I know Bengals fans are probably wondering why a 5-11 team is the top comp for them, but the Chargers, despite the poor record, had a nERD of 0.71 in 2016, giving them an expected win rate of 52.2%. They were a better-than-.500 team, same as the other top comps.

NEP Ranks
Team Total
2021 CIN 15 12 21 12 14 13
2016 LAC 17 17 28 12 10 11
2008 CHI 28 25 29 8 13 5
2014 ARI 19 21 26 7 11 11
2002 PIT 18 14 23 12 13 16
2019 LAR 16 10 26 9 15 10

They're pretty similar to those 2016 Chargers after all.

Expected Outcome

numberFire's algorithm gives the Rams a 60.7% chance to win, which falls shy of their implied moneyline odds (66.4%), given their -198 moneyline at FanDuel's Online Sportsbook.

As a result, the model here at numberFire views a one-star lean on the Bengals to cover.

That's what happened in the most historically comparable game to this one in our database: a 31-24 win by the Carolina Panthers over the Minnesota Vikings in Week 14 of the 2017 season.

The projected final score, via numberFire's algorithm: Rams 24, Bengals 21.