[Today’s post is brought to you by Neil Paine, my comrade at Pro-Football-Reference.com and expert on all things Sports-Reference related. You can follow Neil on twitter, @Neil_Paine.]

Most fans like to think of the NFL’s playoff system as being the final word on each team’s season — run the table and you’re the champs, the “best team in football”; lose, and your season means nothing. But what if I told you that the NFL playoffs are getting a lot more random in recent seasons? Would it change your attitude if you knew we were getting closer to the point where every playoff outcome might as well be determined by a coin flip?

To research this phenomenon, I want to explore two models of predicting playoff games: one powered by as much information as possible, the other completely ruled by randomness. I then want to simulate the last 34 postseasons, and see how much of a predictive edge that information actually gives you. If it’s giving you less of an edge, it means the playoffs are being ruled more by randomness.

First, I grabbed every playoff game since 1978 and looked at the Vegas lines. To convert from a pointspread to a win probability, you have to use Wayne Winston’s assumption that “the probability […] of victory for an NFL team can be well approximated by a normal random variable margin with a mean of the Vegas line and a standard deviation of 13.86.” If the Patriots are favored by 7 over the Ravens, this means you can calculate their odds of winning in Excel via:

p(W) = (1-NORMDIST(0.5,7,13.86,TRUE))+0.5*(NORMDIST(0.5,7,13.86,TRUE)-NORMDIST(-0.5,7,13.86,TRUE)) = 69.3%

This gives us a good prediction — in fact, perhaps the best possible prediction — of the outcome going into the game. So for each playoff, I’m going to say a “Smart” fan picks winners based on these numbers; 69.3% of the time he’ll pick the Patriots, and 30.7% of the time he’ll pick the Ravens. Of course, we also need a control, a fan who picks completely at random, so I’m also going to track a “Dumb” fan who thinks every single game is a coin flip.

I’m going to simulate these decision-making processes for the Smart and Dumb fans in every playoff since 1978, running through each year 1,000 times. How much better at picking do you think the Smart fan will be than the Dumb one?

Well, over the course of the whole sample, the Smart fan averaged a little more than 204 correct picks in 356 games, which is good for a 56.6% rate. The Dumb fan had 178 correct picks, a 50% success rate. In other words, being “Smart” gave you an edge of 6.6% over the fan who picked Aaron Eckhart-style.

But what I really want to know is whether this number has changed over time. The logical comparison I wanted to make was pre- and post-free agency, but it turns out there is practically no difference. From 1978 through 1993, the Smart fan would pick winners at a 56.6% rate (6.8% better than his Dumb counterpart), and from 1995-2011, he picks at a 56.3% clip (6.2% better than the Dumb fan). That observed difference, less than a half a percentage point, can be chalked up completely to random variation, so there’s no evidence that the playoffs have been more or less random in the salary cap era.

However, if you compare pre-2005 to post-2005, you see a major difference that cannot be explained away by chance alone. From 2005-2011, the Smart fan would have picked only 53.2% of playoff games correctly; that’s a difference of 3.2 percent from 2005-11, vs. 6.6 percent over the course of the full sample!

Let me restate this finding: the difference between an intelligent prediction of NFL playoff games and a pure coinflip has been sliced in half in the last seven postseasons. In other words, the playoffs are more random now than they’ve ever been in the last 35 years, something we’ve all seen anecdotally with the 2005 Steelers, both Giants championships (especially last year, when they were actually outscored during the regular season), and the 2008 Cardinals’ unexpected SB run, among others.

So does this change how you feel about the playoffs? Do you still think the “best team” is synonymous with the Super Bowl Champion, or do you think it’s more of a crapshoot than ever before?

The last few years, first at the PFR Blog and later at Smart Football, I’ve tracked the college football season with a modified version of the Simple Rating System. The SRS thrives on interconnectivity — we need each of the teams to play each of the other teams as many times as possible. You can’t create a predictive version of the SRS until after several weeks of results: an objective strength of schedule can’t be created until the system seems how teams perform against multiple teams.

But we can see how teams performed in week 1 compared to expectations, by comparing the actual results to what the SRS would have predicted if the same teams had instead met at the end of the 2011 regular season. For example, the 2011 Pittsburgh Panthers had an SRS of 39.9, while the 2011 Youngstown State Penguins — an FCS team but a very good one — had an SRS of 28.0. With YSU heading to Pittsburgh, we would project Pittsburgh to win by 14.9 points, factoring in three points for home field.

As it turns out, the Penguins beat the Panthers by 14 points, meaning YSU surpassed “expectations” by 28.9 points. At least according to this unusual definition of expectations. But that wasn’t the biggest upset of the weekend, and not just because Pittsburgh was mediocre last year. In 2011, YSU handed eventual FCS National Champion North Dakota State their only loss of the season — in Fargo — last November. No, the biggest upset of the weekend came at the expense of the 13th best team in the SRS last year…. to a team playing its first game at the FBS level.

You may recall that the Houston Cougars started last season 12-0, and were in the running for a BCS Bowl berth before losing in the Conference USA Championship Game to Southern Mississippi. Since then, Cougars coach Kevin Sumlin jumped to Texas A&M while star quarterback Case Keenum finally exhausted his eligibility. Regression was expected — assumed, even — but to see the Cougars lose to Texas State was astonishing. Texas State plays in San Marco, Texas, located roughly halfway between San Antonio and Austin, and joined college football’s highest ranks this season. The Texas State Bobcats were an FCS school last year and went 6-6; against their only non-FCS opponents in 2011, the Bobcasts lost 50-10 to Texas Tech and 45-10 to Wyoming. And coming into the game, Texas State was a 34.5 point underdog. Update: This morning, Houston offensive coordinator Mike Nesbitt “resigned”, and head coach Tony Levine announced that Travis Bush will now handle the play-calling duties.

Here were the biggest “upsets” of week 1 according to the 2011 SRS. The final column shows the difference between the actual results and the expected score:

Team	PF	Opp	PA	Loc	TmConf	OppConf	EXP MOV	Diff
Texas St-San Marcos	30	Houston	13	Road	WAC	CUS	-40.2	57.2
Youngstown St	31	Pittsburgh	17	Road	fcs	BgE	-14.9	28.9
Ohio U.	24	Penn State	14	Road	MAC	B10	-12.1	22.1
Duke	46	Florida Int'l	26	Home	ACC	Sun	-1.5	21.5
Eastern Washington	20	Idaho	3	Road	fcs	WAC	-0.2	17.2
Nevada	31	California	24	Road	MWC	P12	-8.3	15.3
Colorado St	22	Colorado	17	Denver CO	MWC	P12	-6.4	11.4
Troy	39	Alabama-Birmingham	29	Road	Sun	CUS	-0.2	10.2
Arizona	24	Toledo	17	Home	P12	MAC	-2.8	9.8
McNeese St	27	Middle Tennessee St	21	Road	fcs	Sun	-3.8	9.8
Texas-San Antonio	33	South Alabama	31	Road	WAC	Sun	-4.7	6.7
Michigan St	17	Boise St	13	Home	B10	MWC	-1.7	5.7

Again, obviously not all of these were upsets. Boise State was expected to decline following the loss of Kellen Moore and a stellar senior class, and actually covered the spread in their loss to Michigan State. But this helps to at least give a hint of what were some possible upsets. The Pac-12 only went 2-2 in their games against the Mountain West this weekend, as Colorado and California came out flat against Colorado State and Nevada. In addition to McNeese State’s victory over MTSU, there was a 4th victory by an FCS school over an FBS team: but it doesn’t register as an upset on the SRS meter. Tennessee-Martin defeated Memphis 20-17 on a field goal in the final seconds; while UT-Martin was a 9.5 point underdog according to Las Vegas, they actually finished 6 points higher than Memphis in the SRS last year.

Impressive wins by Favorites

We can use the same formula to look at the most impressive wins by the SRS favorites in FBS games. Subjectively, it’s hard to top what Alabama did to Michigan on Saturday Night; if it’s possible for the #1 or #2 team in the country to look better than we thought, the Crimson Tide did just that this weekend. But looking at simple arithmetic…

Team	PF	Opp	PA	Loc	TmConf	OppConf	EXP MOV	Diff
Ohio State	56	Miami OH	10	Home	B10	MAC	15.4	30.6
Notre Dame	50	Navy	10	Dublin Ireland	IND	IND	14.2	25.8
Nebraska	49	Southern Miss	20	Home	B10	CUS	6.6	22.4
Central Florida	56	Akron	14	Road	CUS	MAC	21.6	20.4
UCLA	49	Rice	24	Road	P12	CUS	6.6	18.4
Alabama	41	Michigan	14	Arlington TX	SEC	B10	8.8	18.2
West Virginia	69	Marshall	34	Home	B12	CUS	17.3	17.7
Connecticut	37	Massachusetts	0	Home	BgE	MAC	20.2	16.8
Baylor	59	SMU	24	Home	B12	CUS	19.7	15.3
Brigham Young	30	Washington St	6	Home	IND	P12	9.5	14.5
Iowa St	38	Tulsa	23	Home	B12	CUS	0.5	14.5
Southern Cal	49	Hawai`i	10	Home	P12	MWC	26.1	12.9
Illinois	24	Western Michigan	7	Home	B10	MAC	6.3	10.7

Urban Meyer’s debut was about as good as he could have hoped, thumping a Miami of Ohio team that was solid in 2011. Notre Dame, excellent at disappointing its fan base, destroyed Navy in Saturday’s early game in Dublin. Nebraska’s Taylor Martinez had perhaps the best passing game of his career over Southern Miss, who is replacing head coach Larry Fedora (now in North Carolina). Baylor was only a 7-point favorite against SMU in its first game After RGIII; based on their success last year, the SRS projected Baylor as a 20-point favorite. Still, the Bears blew out Southern Methodist 59-24, in an effort to prove that they weren’t a one-man program. Not every school was as fortunate…

Honorable Mentions

San Jose State, a projected 32-point loser in Palo Alto, nearly pulled off a huge upset in Stanford’s first game After Luck. The Cardinal needed a last second fourth-quarter field goal to win, 20-17. Northern Iowa, a 25-point projected loser to Wisconsin, lost 26-21, a sign that the Panthers should be in for a good year. Maryland needed a 4th quarter touchdown to defeat William & Mary, 7-6, despite being a projected 15.5 point winner. In other depressing ACC news, Wake Forest got a scare from Liberty — a team they were projected to beat by 16.7 points — but won 20-17.

Coming up with trivia questions every weekend isn’t as easy as you might think. Or, if you think it’s easy, submit them to chase [at] footballperspective [dot] com. Otherwise, you’ll get oddball questions like this one today.

Daunte Culpepper’s 2004 season was one of the most incredible in football history. He gained 5,123 combined passing and rushing yards, which stood as an NFL record until 2011. He also threw for 39 touchdown passes and ran for two more, making it one of the most impressive statistical seasons in history.

It’s tempting to give all the credit to Randy Moss, but that was actually Moss’ worst season in Minnesota. Due to a hamstring injury, he was inactive or ineffective for five games, and ended the year with only 767 yards. That brings us to Sunday’s trivia question. Can you name the player who led the ’04 Vikings in receptions?

The past three days, Football Perspective has looked at the best quarterbacks in NFL history. On Wednesday, I explained the methodology for grading each quarterback in each season. Thursday, I came up with an all-time career list of the best quarterbacks based on their regular season play. Yesterday, I presented the data on playoff performances.

Which leads us into today’s trivia question. Only two quarterbacks have ever led two different teams to championships. Can you name either of them? No quarterback has ever won Super Bowls with different teams, although a certain Mile High quarterback will attempt to do that this year.