EXP 13 13 2 30 28
Scoring % 17 12 4 27 28
Turn over % 27 9 11 6 13
points /drive 18 12 3 32 35
passer rating 11 10 2 23 22
Sack % 16 6 2 32 40
rush yds/att 27 27 1 24 23
rush yds/gm 27 16 5 25 31
punt yds/ret 7 26 24 9 -34
kick yds/ret 15 31 18 27 -7

The above table shows the rankings (1-32) in 10 statistical categories for each team’s offense and defense.  The NO NET ADV. column gives the Saints statistical ranking advantage (or disadvantage if negative).  The 179 is the sum of all 10 advantages, meaning the Saints enjoy a 17.9 average ranking advantage.  Biggest advantage for the Saints is sack % where Saints offense is 2nd best and the defense is 6th best while the Bucs’ offense is 16th, but their defense is 32nd.  Thus, 32+16 = 48 – (2+6) = 40.  Biggest advantage for the Bucs is on special teams in the punt and kick return game, which is an area the Saints have struggled with all year.

nfl no vs tb graph1

In the chart above lines that extend to the right of 0 show advantage Saints, those to the left show advantage Bucs, the longer the line the bigger the advantage.

nfl no vs tb graph2

In the above graph the shorter the bar the better (lower, as in smaller number) the ranking.  All data comes from pfref.com.

The Saints *should* win this game, based on the above analysis.  Also, Bucs are 4-11 and have lost 5 in a row while the Saints are 11-4.  But caveat aleo, even though the Bucs have lost 5 in a row they’ve been in those games down to the final few minutes.  Last 3 losses have been by 3 points each.  In his last 4 games Jameis Winston has had 8 TD’s against just 2 INT’s.  He’s getting healthier and the Bucs might be playing their best ball of the year.  And, even though the Saints are 11-4, they’re only 3-3 on the road in true road games (not counting the neutral field London game).


It has been brought to my attention (via Twitter) that the NFL gave the Saints the Superbowl in 2009, because of Katrina.  Why the NFL waited 4 years to do it is still unclear, but, hey, at least they came through eventually.  Thank you, Roger Goodell.

Thank you, Atlanta Falcons.  If the Saints had not swept (excuse me, if the Falcons had not let the Saints have both of those games) the Falcons that year, it would have been the Falcons that were 13-3 and the Saints that were 11-5.  Saints would not have had home field advantage throughout, but would have instead been a wildcard team traveling in the playoffs, and the Falcons would have been the #1 seed.  Thank you, Arthur Blank.  Who dat!, buddy.  Who dat!

Thank you, Matt Ryan.  You were awesome that year against the Saints: 19/42 (45.2%), 1 TD, 3 INT’s, passer rating: 46.6.  ‘Preciate you for doing your part, man.  You even sat out one game against the Saints.  What did you tell them?  Your tummy hurt?  He he.  Thanks, man.  Took a while, but we got you that MVP, as promised.  He he.

Thank you, Brett Favre.  Thanks for throwing that interception to Tracy Porter.  That was a great sacrifice you made.  I know you wanted to win the Superbowl that year, but you agreed to throw that pick so the Saints and the city of New Orleans could have that Superbowl win.  That was awesome of you, man.  And it was a perfect pass, too, just like Roger Goodell told you on the phone.  Remember that conversation?  “Now, remember, Brett.  He’s a cornerback, not a receiver.  It needs to a perfect pass.”  And you nailed it, dude, right between the numbers.  Hope you’re enjoying that Wrangler contract we got for you.  Real.  Jeans.  Dude, you nailed that one, too!  Who Dat!

Thank you, Peyton Manning.  I know it was tough, man.  I know it was tough to throw that pick-six in the Superbowl, but it had to be done.  And the way you threw it right to Tracy Porter, I mean, right to him, that was sweet.  Everybody thinks you were trying to throw it to Reggie Wayne, who was standing right there behind Tracy, but we know better.  [nod, nod, wink, wink]  Oh, yeah, and thanks for striking that pose on your elbows as you watched Tracy and Will Smith and those guys celebrate on the way to the end zone.  That was a great picture.  Roger told you that was gonna be an epic, iconic picture.  ‘Preciate you.  Sorry we weren’t able to get you that parade at the airport after the game.  We called a lot of Colts fans to try to get that lined up.  Not our fault only 5 of them showed up.  Hope you’re still not bitter.  And, remember, we got the AP to give you that MVP trophy even though they wanted to give it to the real MVP that year.  We good, right?

Thank you, Kareem Moore.  (Who?)  Thanks, Kareem.  Other fans might have forgotten you and what you did for us, but I remember.  Thanks for letting Robert Meachem have that interception and run it in for the score.  That was swell of you, man.  Saints might have lost that game otherwise.  Nice handoff, man.  Thought Robert might drop it there for a moment.  He he.

Well, this is getting long, so let me wrap it up.  So many people to thank, so little space to do it in.  I want to thank all the quarterbacks who threw all those interceptions to the Saints that year.  26 of them, and we needed them all.  And thanks for not throwing too many TD’s against our team, too.  You guys kept it down to just 15 the whole year.  That’s pretty amazing.  Your generosity that season truly knew no bounds.

Special thanks to the entire Colts team that year.  Thanks for letting us have that onside kick.  Thanks for not tackling Pierre Thomas on that screen pass.  Special thanks again to Peyton for the pick-six.  But most of all, thank you, Atlanta Falcons.  Saints simply could not have done it without you guys.  That #1 seed you guys gave us that year, I can’t emphasize it enough.

And, Roger, what can we say?  You made so many phone calls setting all this up.  Wasn’t easy, I know.  But, hey, that’s why we pay you the big bucks.  He he.  Don’t worry about Jerry.   And don’t worry about those tv ratings, man.  We got you.  He he.

Philly has locked up the #1 seed, but they are vulnerable.  In fact, I think they go 1-and-done in the playoffs against any of these teams: NO, CAR, LAR, or MIN.  They might be able to take down ATL or SEA, but that’s about it.

#2 seed is up for grabs, but MIN has the inside track.  CAR is still alive, but they need NO to lose to TB *and* they need to beat ATL in ATL.  Neither of these is likely to happen.

#3 seed is there for the taking by the Rams *if* they want it.  Rams might elect to rest starters and slide into the #4 seed, hoping to get PHI in the division round.  We’ll see how they play it.  SF might beat LAR outright in any case because since they started starting Jimmy GQ, they’ve won 4 in a row.  Saints can take the #3 seed by beating TB if LAR falls to SF.  (It’s also possible MIN slides to #3 if CAR takes #2, but that requires NO losing to TB and CAR beating ATL.)

#4 seed is probably where the Saints land.  They can lock that up by beating the Bucs, assuming LAR beats SF.

#5 is probably where CAR lands unless NO falls to TB and CAR beats ATL in ATL.  Only CAR and NO can be #5, no other team can get this seed.

#6 is probably going to ATL, but SEA might get it if ATL falls to CAR and SEA beats ARI.

The 2 toughest matchups for the Saints (IMO) would be @ LAR and @ MIN.  The Saints can take CAR at home or on the road either way if it comes to that and the Saints can take out PHI if it comes to that.  Should we Saints fans be pulling for the #4 seed instead of the #3 seed?  That’s a good question.  The #4 seed likely means playing CAR in the Superdome, then going to PHI in the division round, then finishing up in the NFC CG @ MIN.  I’ll take it if it happens, but I don’t like the Saints’ chances in MIN, to be honest.  If the Saints get the #3 seed it likely means hosting SEA/ATL, which the Saints should win, then going to MIN in the 2nd round, which, again, is a tough matchup for the Saints.  But *if* they can win in MIN they can then host the NFC Championship Game against (probably) the Rams.  I’m not crazy about either matchup (@ LAR or @ MIN), but I like the Saints chances hosting LAR in the NFCCG, so the #3 seed is probably the one to hope for.

Brees’ numbers aren’t as gaudy as they’ve been in the past because they haven’t had to be.  The passing yards, the passing TD’s, those numbers are down, but the efficiency is there.  As an example, he’s on pace to set a new all-time single-season completion percentage record at 71.8%.  (Best all-time currently belongs to Sam Bradford at 71.6%.) Let’s look at some of the qualifications we might look for in an MVP candidate and where Brees fits in.

Passer rating

Let’s start with passer rating.  No MVP candidate shall have a passer rating below 100.0.  If there are no quarterbacks in a given year with 100.0+ passer ratings, let’s just give it to a running back, receiver, or defensive player.  Let’s plug passer rating into a search query at the player season finder at pfref.com.

Minimum games won

Now, let’s add another filter to that search.  We’ll require the MVP candidates must have at least 10 wins.  We can up this later after the season is over, but 10 right now is a fair number to use.

Adjusted net yards per attempt

Finally, let’s sort our remaining candidates by adjusted net yards per attempt.  You might ask what is “adjusted net yards per attempt”.  (Or you might not.)  This is a stat pfref provides that takes into account completions, attempts, yards, sacks, TD’s, and INT’s.  It all goes into that equation.  Basically, it’s:

“(Passing Yards – Sack Yards + (20 * Passing TD) – (45 * Interceptions)) / (Passes Attempted + Times Sacked)”

So, what they’re doing is giving a 20-yard bonus for each TD and a 45-yard penalty for every INT.  If you’re throwing a lot of short passes you’ll get penalized with the reduced yardage, but if you’re throwing a lot of picks or a lower completion percentage you also get penalized.  I think it’s a really good way to measure the production level of a quarterback.  It also takes into account sacks because it counts as an incompletion (something passer rating stat does not do) and also the lost sack yardage goes against the passing yardage.

Here’s what we get when we require 100.0+ passer rating, 10+ QB wins, and when we sort the list by adjusted net yards per attempt: (May I have the envelope, please.)

making case for brees mvp pic

You can certainly make a case for the other 2 guys on this list.  Wentz has more TD’s, but he’s also got the lowest adjusted net yards per attempt, and unfortunately for all of us who have enjoyed watching him play, he’s now injured and out for the season.  He’s tied for the most wins (11), but will that hold?  Doubtful.  Another strike against him is that completion percentage, by far the lowest in this group, 60.23%.  The last time Drew Brees had that low a completion percentage (57.6%) was 2003, his first year as a starter in San Diego when he went 2-9.  His average completion rate as a Saint is 68.0%, that’s like 7.77% better than Wentz, and that’s just his *average*.  Dude’s completing them at a 71.76% clip this year.

What about Brady?  He has more yards, shouldn’t he get it?  He’s got more yards because he has had to get more yards.  That defense has been pretty bad, especially earlier in the year when he had to win a lot of shootouts.  He’s got more yards because he’s got more attempts.  He’s got 38 more attempts than Brees, of course he’s going to have more yards.  If Brees had 38 more attempts he’d have just about as many yards.  It would be a trivial difference.  Let’s do the math.  Brady has 4163 yards to Brees’ 3850, a difference of 313.  Brees’ yards per attempt is 8.05.  38 * 8.05 = 305.9, call it 306.  We’re talking 7 yards difference here.

Brady has more TD’s.  This is true, and definitely a point in his favor, but again, more attempts.  How many more TD’s would Brees have with those 38 extra attempts?  He has 21 TD’s on 478 attempts, so that’s about 4.4%.  Multiply it by 38 you get 1.67, somewhere around there.  He’d have probably a couple more TD’s to narrow that gap.  The season isn’t over yet, so we’ll see where they end up when all is said and done.   Bear in mind Brady got 20 yards extra for each of those TD’s and it still wasn’t enough to put him over the top in adjusted net yards per attempt.  That’s the game changer here, those adjusted net yards per attempt.

Season isn’t over yet

Let’s let the rest of the season play out and come back later to revisit these numbers.  I just wanted to make this early case for Brees to put it out there for your consideration.

Using the game play finder tool at pfref.com I pulled up the 1st down conversion rankings for the Saints on 1st, 2nd, 3rd, and 4th downs.  I excluded from the plays all FG’s (sometimes teams kick field goals on other than 4th down at the end of games/halves), punts (hard to get a 1st down on 4th down when you punt…), and quarterback kneel downs (teams aren’t really trying to get a 1st down in those situations).

Here are the results:

1st down 2nd down 3rd down 4th down
Conversion % 25.90% 36.90% 40.00% 84.60%
League Rank 3 1 15 1
Def Conv % 18.70% 32.20% 40.00% 22.20%
Def Rank 8 22 17 2
% total plays 44.10% 33.30% 21.20% 1.50%

Now you might be thinking, okay, Mark, but why the heck are you looking at 1st down conversion rates on 1st down?  All that matters is 3rd down and 4th down, right?  Wrong.  You want to get 1st downs.  Doesn’t matter if they’re coming on 3rd down, 2nd down, 1st down, or 4th down.  The key is to keep getting those 1st downs to keep the drives going.  I would argue it’s even more important getting a 1st down on 2nd down than on 3rd down because you’re not putting the offense in those turnover-prone 3rd and long situations.

Notice how the Saints are 15th on offense in 3rd down conversion rates (40%).  That’s not good, that’s mediocre.  Looks like a very average (is “very average” oxymoronic?) offense, doesn’t it?  Not so fast, my friends.  Look at the 1st down conversion rates on 1st, 2nd, and 4th downs, 3rd best on 1st down, best on 2nd down, best on 4th down.

The defense has struggled most on 2nd down where they’re ranked 22nd.  That’s not good, not even mediocre.  It’s bad.  But they’ve been good on 1st down (8th best), average on 3rd down (17th) and stellar on 4th down (2nd).  4th down stops are huge because those often come at the ends of games when the opponent is in desperation mode trying to come back on you.

The bottom row “% total plays” shows the percentage of these (offensive) plays that occurred on each down.  Notice the weakest down (3rd down) features only 21.2% of the total plays.  Twice as many (44.1% versus 21.2%) plays come on 1st down where the Saints are 3rd best in the league at picking up 1st downs.  78.9% of offensive plays come on downs where the Saints are ranked 1st, 1st, or 3rd best at picking up 1st downs.  Saints have been phenomenal on 4th down at 84.6%, but it’s also the smallest sample size (only 1.5% of offensive plays, again not counting FG’s or punts).  On 13 4th down plays the Saints picked up 11 1st downs, average yards to go was only 1.85 yards (least of any yards to go average for any team).  4th and longs come when you’re desperate late in the games, which at 10-4 hasn’t happened too often.

Why the Saints do so well on the other downs, but struggle so much (relatively speaking) on 3rd downs is a bit of a mystery.  I thought perhaps it was because they were facing a lot of 3rd and longs, but that’s not it.  Average distance to go is only 6.88 on 3rd down (8th least in the league).  7.28 to go on 3rd down is the league average.  Green Bay had the least with 6.28, Chicago the most with 8.37.

Since 2015, kickers have made 3215 out of 3419 extra point tries (94.03%).  As these are worth 1 point each, the expected outcome is 0.94 points per extra point try.

Since 2015, teams have been successful on 128 of 272 2-point tries (47.05%).  These are worth 2 points each, so the expected outcome is 0.941 points per 2-point try.

Basically, it’s a wash.  You have twice as good a chance of making the XP, but since you get twice as many points for making the 2-pt play, it works out to be pretty much the same thing in the long run.

Of course, coaches are less concerned about the long run than they are about winning the game at hand.  Game situations will dictate which strategy to use.  Coaches with a firm grasp on the strategies involved will have the advantage.  It’s not surprising the New England Patriots were the team to suggest moving XP tries back.  Their coach is playing chess while often the opposing coach is playing checkers.

Another aspect of this is how good the offense is versus how good the defense is in a given matchup.  Coaches who feel their offense has the advantage should go for 2 unless the game situation dictates going for 1.  For example, in tonight’s game the Falcons have the 3rd best yards/play average on offense (6.0) and are going up against the worst defense in the league in the Buccaneers (6.1 per play allowed).  Falcons should go for 2 every time until later in the game when the game situation might call for going for 1 instead.

Problem with this strategy is Falcons coach, Dan Quinn, probably wants to keep his job.  If he goes for 2 every time and misses on more than half of them and the team loses as a consequence of that he’ll be putting his job in more jeopardy than if they miss an XP kick and he loses by the same amount.  The owner would almost certainly blame the kicker on the loss in the latter case, but the coach gets the blame in the former.

This is kind of like the economics of weather forecasting.  The last thing the weather forecaster wants is to predict no rain and to have rain.  So, the smart thing to do is to hedge a little bit and predict a slight chance of rain even in cases where rain isn’t expected.  Let’s say the model calls for 10% chance of rain.  The forecaster is better off prediction 20% chance of rain.  He’ll be wrong more often, but when there’s no rain nobody really cares that you predicted 20% instead of 10%, but all those folks that left their umbrellas home *are* going to be upset about it when it does rain on those 10% days.  And they’ll remember it.  And they won’t be forgiving.


In the pro bowl there will be 2 starters at WR, 2 reserves at WR, and 2 alternates.  (I believe the alternates are considered “pro bowlers” if they accept the invitation to be alternates.)

The following table shows the receiving stats for the 8 leading WR’s (8 with most receiving yards) in the NFC up to the end of fan pro bowl voting (up to and including week 14 games).  It is sorted by 1st downs gained on receptions (including those that came on 1st, 2nd, 3rd, and 4th downs).

Player 1st Downs Receiving Yards Receptions Receiving TD’s
Michael Thomas 58 992 85 4
Julio Jones 55 1161 73 3
Adam Thielen 52 1161 80 4
Larry Fitzgerald 52 922 87 5
Davante Adams 43 828 69 9
Doug Baldwin 38 860 66 5
Golden Tate 37 852 79 4
Marvin Jones 36 885 51 8

Thomas is #1 in 1st downs, #3 in yards, #2 in receptions, and #5 in TD’s.  If we’re strictly going by yards the 2 starters should be Julio Jones and Adam Thielen.  If we’re going by receptions it should be Larry Fitzgerald and Michael Thomas.  If we’re going by TD’s it should be Davante Adams and Marvin Jones.  And if we’re going by 1st downs it should be Michael Thomas and Julio Jones.

Julio Jones makes it 2x (1st downs and yards), Michael Thomas makes it 2x (1st downs and receptions), Adam Thielen makes it 1x (yards), Larry Fitzgerald makes it 1x (receptions), Devante Adams makes it 1x (TD’s), and Marvin Jones makes it 1x (TD’s).  Based on that analysis, your 2 pro bowl starters at WR for the NFC should be Julio Jones and Michael Thomas.

nfl cantguardmike recsnfl cantguardmike ydsnfl cantguardmike 1dsnfl cantguardmike tds

The above 4 graphs depict how Michael Thomas is in the top 4 (for purposes of being named either starter or reserve) in all but 1 of the rankings (TD’s, where he’s tied for 5th).

If we’re going 4 deep (instead of 2 deep as above, when considering the 2 starters) here’s how many times each of the 8 players makes the top 4 for these 4 stats:

Larry Fitzgerald 4x (TDs, 1ds, yds, and recs)
Michael Thomas 3x (recs, yds, and 1ds, but not TD’s)
Adam Thielen 3x (1ds, yds, and recs, but not TD’s
Julio Jones 2x (yds and 1ds, but not recs or TD’s)
Davante Adams 1x (TDs, but not 1ds, yds, or recs)
Doug Baldwin 1x (TDs, but not yds, 1ds, or recs)
Golden Tate 1x (recs, but not yds, 1ds, or TDs)
Marvin Jones 1x (TDs, but not yds, 1ds, or recs)

Based on this analysis, your 4 pro bowlers would be Larry Fitzgerald, Michael Thomas, Adam Thielen, and Julio Jones.

You might be thinking, okay, Mark, but 1st downs aren’t a stat that’s commonly used for such things.  I would argue two things to that: 1) they should be because picking up 1st downs is critical, and 2) even if we don’t use 1st downs Michael Thomas is still only 1 of 3 players to have 2x finishes in the top 4 of these stat comparisons.  Fitzgerald would have 2x, Thomas would have 2x, and Thielen would have 2x, while all the others have just 1x.

Would it be possible to come up with a composite score to settle this?  Let’s say we give 1 point per reception, 1 point per 10 yards, 2 points per 1st down, and 6 points per TD.  Is that fair?  Here is a new table, ranked by this type of composite scoring system:

Player 1D Receiving Yards Receptions Receiving TD’s Composite
Michael Thomas 58 992 85 4 324.2
Adam Thielen 52 1161 80 4 324.1
Julio Jones 55 1161 73 3 317.1
Larry Fitzgerald 52 922 87 5 313.2
Davante Adams 43 828 69 9 291.8
Golden Tate 37 852 79 4 262.2
Marvin Jones 36 885 51 8 259.5
Doug Baldwin 38 860 66 5 258

These are the same values used in PPR scoring (except the 2 points for 2-pt conversions is given to first down catches).

If we exclude 1st downs from the composite scoring and only use 1 point per reception, 1 point per 10 yards receiving, and 6 points per TD, we get:

Player Receiving Yards Receptions Receiving TD’s Composite
Adam Thielen 1161 80 4 220.1
Larry Fitzgerald 922 87 5 209.2
Michael Thomas 992 85 4 208.2
Julio Jones 1161 73 3 207.1
Davante Adams 828 69 9 205.8
Golden Tate 852 79 4 188.2
Marvin Jones 885 51 8 187.5
Doug Baldwin 860 66 5 182

Michael Thomas absolutely belongs in the pro bowl.  If he doesn’t get an invite it will be a travesty.

Recently I gave the playoff records of home teams in the various rounds of the playoffs.  Here is the table from that earlier blog post:

Post merger (since 1970) records home win percentage
regular season .576
playoffs overall .679
wildcard round .630
division round .713
conference round .681

I also gave some probabilities based on those records of the various seeds getting to the Superbowl, but those probabilities were based on some further assumptions:

“The table below shows the various probabilities of making it to the Superbowl based on the above records and based on the assumption the 5 and 6 seeds travel in every round, the 3 and 4 seeds host in the first round and travel the rest, the 2 seed hosts in all but the conference round, and the 1 seed hosts every round.  1 and 2 also don’t have to play in the wildcard round.”

That was intellectually lazy, bad as I hate to do it to myself.  I decided to break it down into getting to the conference championship game (ccg) as both host and visitor, and then calculate it from there, which is fairly straightforward.

First, let’s setup a few variables.  Let divHome be the home records of division home games in the playoffs (.713).  Let divAway be 1 – divHome.  Similarly, wcHome = .630, wcAway = 1 – .630, confHome = .681, and confAway = 1 – .681.

Seed1’s probability of hosting the ccg is straightforward.  It just needs to win its home division game.

seed1Host = divHome

Seed2 needs to win its division home game, but it also needs for seed1 to lose its division home game (or else seed1 would be host).

seed2Host = divHome * divAway

For seed3 to be host of the ccg it needs to win a wildcard home game + a division away game + it needs the other division away team to win (to knock off either seed1 or seed2 in the other division game).

seed3Host = wcHome * divAway * divAway

For seed4 to be host of the ccg it needs to win its wildcard home game against seed5 + it needs seed6 to beat seed3 in its wildcard away game + it needs to beat seed1 in its division away game + it needs seed6 to beat seed2 in its division away game.

seed4Host = wcHome * wcAway * divAway * divAway

For seed5 to host the ccg it needs pretty much the same thing to happen for it that seed4 needed to happen for it except the only difference is seed5 is playing a wildcard away team that it needs to win whereas seed4 is playing a wildcard home game that it needs to win.

seed5Host = wcAway * wcAway * divAway * divAway

Seed6 cannot host the ccg under any scenario.

seed6Host = 0

Now, we work on how the various seeds can be the ccg away team.

Seed1 cannot under any scenario be the ccg away team because if it gets there it will host over any other opponent.

seed1Away = 0

Seed2 can be the away team at the ccg game by winning its division home game + having seed1 win its division home game.

seed2Away = divHome * divHome

For seed3 to be the away team at the ccg it needs to win its wildcard home game + it needs to win its division away game + it needs the other division home team (seed1 or seed2) to win.

seed3Away = wcHome * divAway * divHome

For seed4 to be the away team at the ccg is where it starts getting complicated.  Seed4 needs to (obviously) get to the ccg, but the ccg needs to be against a higher seed (not against seed5 or seed6).  Seed5 is easily taken care of because that’s seed4’s wildcard round opponent, but seed6 could get there, in which case seed4 would be the host.  Seed4 needs either seed6 to lose to seed3 in the wildcard round *or* seed6 to lose to seed1 in the division round.  The probability of seed6 losing one or the other is the same as the probability of it *not* winning both (1-(wcAway*divAway)).

seed4Away = wcHome * divAway * (1-(wcAway *divAway))

Seed5’s road to getting to the ccg as visitor is almost the same for seed4 except its wildcard game is an away game instead of a home game.

seed5Away = wcAway * divAway * (1-(wcAway*divAway))

Seed6 cannot ever host the ccg because no matter what happens in the other games it will always be the lower seed in the ccg if it gets that far, which merely involves winning 2 away games (wcAway and divAway)

seed6Away = wcAway * divAway

So, now we know the probabilities for each of the 6 seeds of both hosting the ccg and being visitor in the ccg.  We also know the historical home records in the ccg, so it’s really just a matter of adding them up.

seed1Win = seed1Host * confHome + seed1Away*confAway
seed2Win = seed2Host * confHome + seed2Away*confAway
seed3Win = seed3Host * confHome + seed3Away * confAway
seed4Win = seed4Host * confHome + seed4Away*confAway
seed5Win = seed5Host * confHome + seed5Away * confAway
seed6Win = seed6Host * confHome + seed6Away * confAway

wcHome 0.63
divHome 0.713
confHome 0.681
wcAway 0.37
divAway 0.287
confAway 0.319
seed1Host 0.713
seed2Host 0.204631
seed3Host 0.05189247
seed4Host 0.0192002139
seed5Host 0.0112763161
seed6Host 0
seed1Away 0
seed2Away 0.508369
seed3Away 0.12891753
seed4Away 0.1616097861
seed5Away 0.0949136839
seed6Away 0.10619
seed1Win 0.485553
seed2Win 0.301523422
seed3Win 0.0764634641
seed4Win 0.0646288674
seed5Win 0.0379566364
seed6Win 0.03387461

link to csv file (right-click, save as, rename from png to csv and import into spreadsheet)

Here are the formulas for Seeds 1 through 6 getting to the Superbowl in case anybody wants to write a program to do it using different values for wcHome, divHome, and confHome:

S1[] := confHome*divHome;
S2[] := divHome*(confHome + (1 – confHome)*divHome – confHome*divHome);
S3[] := (-1 + divHome)*(confHome*(-1 + divHome) – (1 – confHome)*divHome)*wcHome;
S4[] := -((-1 + divHome)*wcHome*(confHome*(-1 + divHome)*(-1 + wcHome) + (1 – confHome) * (divHome + wcHome – divHome*wcHome)));
S5[] := (-1 + divHome)*(-1 + wcHome)*(confHome*(-1 + divHome)*(-1 + wcHome) + (1 – confHome)*(divHome + wcHome – divHome*wcHome))
S6[] := (1 – confHome)*(-1 + divHome)*(-1 + wcHome)


Saints are in pretty good position to win the division or at least make the playoffs.  If they run the table in the final 3 weeks they’ll win the division and go 12-4, but if they go 2-1 they can still win the division and go 11-5, or at least make the playoffs as a wildcard.  The most important thing is to make the playoffs, where anything can happen, but getting to 12 wins has been critically important as a step towards winning the Superbowl.

The following table shows all the Superbowl winners in seasons where there were 16 games played in the regular season.  In other words, all the Superbowl winners since 1978, except for the 2 strike-shortened seasons in 1982 and 1987.  The table basically gives us the regular season records of 38 Superbowl champions.

Record SB Wins
9-7 1
10-6 4
11-5 4
12-4 11
13-3 8
14-2 8
15-1 2

Notice how teams with 11 wins only won 4 Superbowls compared to 11 Superbowls for teams that went 12-4.  How to explain this?  Could be 12-4 teams have a better shot at home advantage.  Could be they’re just better than the 11-5 teams, which makes perfect sense, too, but if it were just a matter of being better, then teams with 13+ wins should have won even more Superbowls, which isn’t the case.  My guess, without digging deeper, is you just don’t have as many 13-3 teams as you have 12-4 teams.

Notice how there are no 16-0 Superbowl winners.  One reason for this is going 16-0 is really difficult.  Only 1 team has ever gone 16-0 in the regular season (1972 Dolphins went 14-0, not 16-0), and of course, that was the 16-0 Patriots team that lost to the 10-6 Giants following the 2007 season.

The argument that there are more 12-4 teams than there are 13-3 or 14-2 or whatever teams has merit as an explanation for why there might be more 12-4 Superbowl winners than 13-3 Superbowl winners, but surely there are more 11-5 teams than there are 12-4 teams.  Logically, then, there should be more 11-5 Superbowl winners than 12-4 Superbowl winners, but that’s not what the data tells us.  Sidenote: there has only been one 11-5 team that failed to make the playoffs, as far as I know (Patriots the year Cassel played in Brady’s place).

nfl sb wins pienfl sb wins line

The following table shows the statistical rankings (prior to the Monday Night Football game this week) in 10 different stats.

EXP 21 14 2 21 26
Scoring % 22 13 3 15 21
Turn over % 15 11 4 15 15
points /drive 22 13 2 19 26
passer rating 12 13 2 18 15
Sack % 30 7 3 23 43
rush yds/att 22 28 1 14 7
rush yds/gm 21 18 4 21 20
punt yds/ret 31 28 24 26 5
kick yds/ret 26 32 24 19 -11
Total net adv: 167
  • EXP is pfref.com‘s expected points stat.
  • Scoring % is percentage of drives ending in a score (either FG or TD)
  • Turnover % is percentage of drives ending in a turnover (either INT or lost fumble)
  • Sack % is the percentage of times a quarterback gets sacked while attempting to pass

Each column represents the team’s ranking (1-32) in that staff, offensive in one comlumn, defense in another.  The final column is the NO Net Adv., which stands for New Orleans Net Advantage in the ranking comparison.  Look at points/drive row as an example.  The Saints’ offense is #2, Saints’ defense is #13, Jets’ offense is #22, Jets’ defense is #19.  In the matchup of the Saints’ offense versus the Jets’ defense (#2 versus #19) the Saints have a 17-ranking advantage.  In the matchup of Jets’ offense versus Saints’ defense (#22 versus #13) the Saints have a 9-ranking advantage.  17+9 = 26.  That’s basically how we get the number for the NO Net Adv. column, the higher that number the better the advantage for the Saints.  Negative values mean the Jets have the advantage.

Here’s a graph of the above table, focusing on the net advantage numbers:

nfl nyj vs no graph1

Saints have very strong advantages across the board in the matchup, biggest of which is sack %.  Brees doesn’t get sacked much while McCown was getting sacked quite a lot (but McCown is out the rest of the season with a broken hand, so Bryce Petty will start versus the Saints, or at least that would be my guess).  Only advantage for the Jets is in the kick return game where the Saints have been atrocious all year.  Jets are sub-average in this stat, too, but the Saints are dead last in kick return coverage.  Lutz is making so many tackles in the kicking game he’s beginning to “mix it up” out there when things start getting chippy.

If you’re wondering why I put the turf background in the horrid graph below it was because I could.  In this graph the shorter bars are better.  They graphically represent the ranking for each of the 10 statistical categories.  Thus, shorter bar means higher ranking.

nfl nyj vs no graph2

%d bloggers like this: