The Pro Football Hall of Fame has announced the nominees for the Class of 2013:

John Lynch, Michael Strahan, Steve McNair and Morten Andersen are among 13 first-year eligible players for the Pro Football Hall of Fame.

Safety Lynch, defensive end Strahan, quarterback McNair and kicker Andersen join offensive linemen Jonathan Ogden and Larry Allen, defensive tackle Warren Sapp and 121 other total nominees for induction. The list will be whittled to 25 semifinalists in late November.

Fifteen finalists from the modern era will be announced in early January, with elections taking place Feb. 2, 2013, the day before the Super Bowl.

Between four and seven new members will be selected, with inductions next August.

Other first-time nominees are running back Priest Holmes, wide receiver Keenan McCardell, center Tom Nalen, defensive tackles Sam Adams and Ted Washington and defensive end Bryant Young.

Among the contributors nominated are former NFL Commissioner Paul Tagliabue and longtime team owners Bud Adams of the Tennessee Titans and Robert Kraft of the New England Patriots. Former Cleveland Browns and Baltimore Ravens owner Art Modell, who died this month, also is a nominee.

Other holdover nominees include receivers Cris Carter, Andre Reed and Tim Brown, running back Jerome Bettis, guard Will Shields, defensive end Charles Haley, linebacker Kevin Greene and defensive back Aeneas Williams, all finalists for the 2012 class.

As you may recall, the two senior nominees, Curley Culp and Dave Robinson, were announced last month. On the modern era side, I’d be shocked if the Hall’s selectors did not use their maximum allotment and select five players.

This could be a particularly enjoyable class for fans of the trench battles. There have only been two classes with four lineman. In 2001, Mike Munchak, Jackie Slater, Ron Yary and Jack Youngblood were inducted, while this past year, Dermontti Dawson, Chris Doleman, Cortez Kennedy and Willie Roaf took center stage.

At first blush, Will Shields seems like a likely selection, as the only explanation I can come up with as to why he wasn’t selected last year was that some didn’t feel he deserved “first-ballot” status. With 12 Pro Bowls, Shields will soon have a bust in Canton. Among the first-time selections, Larry Allen (11 Pro Bowls, 6 first-team All-Pros from the Associated Press) and Jonathan Ogden (11, 4) seem like the safest bets.

On the defensive side, I can see a polarizing player like Warren Sapp having to wait, but I wouldn’t be surprised to see both Michael Strahan and Sapp inducted in 2013. Or it’s possible that Charles Haley or Kevin Greene finally get over the hump. Add in Curley Culp’s likely induction, and this could be the heaviest HOF class of all-time.

In this post, I noted that the Steelers could have punted to the Raiders, leaving Oakland with the ball likely at their own 33-yard line in a tie game with just under 4 minutes remaining.

You are the head coach of a team with a league average offense and league average defense. You are given the ball on 1st and 10 at your own 33-yard line. The game is tied and both you and your opponent have all of your timeouts left.

You are given the option of picking how much time is left in the game. What is the optimal decision?

Roy Jefferson isn’t well-remembered today, but he was one of the top receivers at the start of the Super Bowl era. Jefferson was a second round pick of both the Steelers and Chargers in 1965, back when the leagues held separate drafts. Jefferson chose to sign with Pittsburgh, and in his second season, he led the NFL with a 24.1 yards per reception average. In 1968, Jefferson led the NFL in receiving yards and scored 11 touchdowns, one behind Paul Warfield for the lead. Jefferson matched his production the next year and was a unanimous first-team All-Pro selection. But for Jefferson, personal glory was the only success he would see in Pittsburgh, as the Steelers went just 7-33-2 from ’67 to ’69.

Jefferson’s 1969 performance was interesting for another reason. He gained 44% of his team’s receiving yards, and since then, only a few other players have reached that mark:

As Steelers fans know, 1969 was a key year in the franchise’s history. It was Chuck Noll’s first season, and his first draft selection was Joe Greene. After finishing with the league’s worst record in 1969, Pittsburgh won the rights to draft Terry Bradshaw. On the field, Jefferson was the best player in Noll’s first season. But that doesn’t mean Noll and Jefferson got along.

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Some additions to the weekly power rankings table. After the team name, I have listed each team’s record in column two and the number of wins I’m projecting each team to finish the season with in column 3 (i.e., the power rankings and the metric by which the table is sorted). The fourth column – PWIN – shows how many wins I projected for that team last week, and the difference column represents how many wins I added or subtracted this week. The “RSOS” column stands for the remaining SOS for the team, based on the number of projected wins I’m giving to each of their opponents. The “RHG” column stands for remaining home games. Lastly, my witty and insightful comments remain in the final column.

A lot of power rankings out there had Green Bay as #1 entering week 1, New England up top before week 2, and the 49ers in the 1 spot last week. That means each week of the season, the #1 team on most power rankings have lost. I didn’t do pre-season power rankings, but I did have New England first two weeks ago and San Francisco number one last week. This week, it’s the Texans chance to disappoint their fan base.

The other surprising nugget? There are just two 0-3 teams so far this season, and one of them is the Saints. The Cleveland Browns are now everyone’s front runners to win the Matt Barkley sweepstakes. If Brandon Weeden wants to keep his job, he’ll have to earn it.

Team	Rec	Wins	PWin	Diff	RSOS	RHG	Comment
Houston Texans	3-0	12	11	1	0.471	6	No compelling reason not to list the Texans as the best team in the NFL. The schedule is easy -- Houston will be favored in nearly every game -- so the Texans can easily go 9-4 the rest of the way.
San Francisco 49ers	2-1	11	12	-1	0.500	6	A loss to Minnesota has to drop them a game. I'll keep them at 11 for now, but a loss to either the Jets or the Bills the next two weeks probably gets them back down to 10.
New England Patriots	1-2	11	12	-1	0.481	6	By sweeping their not-so-good division, New England can go 4-3 against the rest of their schedule and get to 11 wins. A 12- or 13-win season isn't out of the question, and the Pats are only two plays away from 3-0.
Baltimore Ravens	2-1	11	10	1	0.490	7	Joe Flacco was his typical inconsistent self, but Torrey Smith gets the award for performance of the week. Without Terrell Suggs I hestitate to put them at 11 wins, but their rest of season schedule is pretty manageable.
Atlanta Falcons	3-0	11	10	1	0.466	6	I still have questions about Atlanta's offensive line and defense, but they're off to a great start. With an easy schedule and three banked wins -- the Falcons are probably a favorite to get a bye.
Pittsburgh Steelers	1-2	10	11	-1	0.481	6	The bye week comes at a good time for the Steelers, who should get a healthy James Harrison, Troy Polamalu and Rashard Mendenhall in week five. I'm only dropping them one win for that ugly second half against Oakland because Ben Roethlisberger had another great game.
Green Bay Packers	1-2	10	11	-1	0.457	7	Technically, four of my top five teams from last week lost. And technically, Green Bay is now 1-2. Officially, the Packers passing offense looks like garbage, as Aaron Rodgers ranks 28th in ANY/A. The Packers get the Rams, Colts and Jaguars in October, which is a decent consolation prize.
Philadelphia Eagles	2-1	9	10	-1	0.505	6	Yeah, they had a disaster against Arizona. And the Eagles can't protect Michael Vick. But doesn't this happen every year and then Philadelphia wins 5 in a row?
New York Giants	2-1	9	9	0	0.534	7	Giants looked outstanding against Carolina, but not ready to bump them to 10 wins/project a 8-5 finish against a brutal remaining schedule. A win in Philadelphia this weekend bumps them to 10 wins, but a loss probably won't drop them from 9 wins.
Dallas Cowboys	2-1	9	9	0	0.510	6	A 'take care of business' day against Tampa Bay. For any team in the NFC East, that's a must.
Seattle Seahawks	2-1	9	8	1	0.500	7	The Seahawks got a free win this week, but Russell Wilson struggled for much of the game. Still, an excellent performance by the defense against Green Bay and a strong running game show that they are a real threat in the NFC.
Arizona Cardinals	3-0	9	7	2	0.514	7	A two-game bump seems appropriate given how dominant the Cardinals' defense and special teams have been so far. I'm far from convinced about this team, though, which is why I'm still projecting a losing record the rest of the way.
Denver Broncos	1-2	9	10	-1	0.466	7	You know, this power rankings thing is harder than I thought. There's a very strong temptation to drop losing teams by a win and bump winning teams by one. I'm trying to resist that temptation, but so far, I'm not very good at it. Expect future Chase to make fun of current Chase for really squiggly lines when I post the final win charts. Oh, and Denver is lucky the AFC West stinks and their remaining schedule is full of flour and sugar.
Chicago Bears	2-1	9	9	0	0.510	7	An unimpressive win against the Rams. Jay Cutler is last in the NFL in ANY/A. The Bears have already used their Rams and Colts coupons [1]I liked when Mike Tanier used that line last week, so I'm going to steal it. Although I don't know if it's stealing it if I announce that I'm doing it. which means they need to play a lot better to go 7-6 the rest of the way. Fortunately the defense looks good so far.
San Diego Chargers	2-1	8	9	-1	0.481	7	Philip Rivers has a career high completion rate (67%) and a career low yards per attempt average (6.7). You know what that means: his anemic 10.0 yards per completion is horrible by any standard, let alone that of the guy who led the league in that metric in '09. I'm not ready to bail on the Chargers, but I'm close. Unfortunately for San Diego, I don't think an easy schedule means much for a team accustomed to shooting itself in the foot.
New York Jets	2-1	8	9	-1	0.510	6	A win over Miami helps, but the Jets drop due to the Darrelle Revis injury. Even 8 wins will be tough, but I think the Jets can win 2 games against the AFC South, with 2 out of 4 against BUF/MIA/NE/NE, and then 2 out of 5 against the NFC West and San Diego.
Cincinnati Bengals	2-1	8	7	1	0.495	6	After an ugly week 1, Andy Dalton and the Bengals are looking better. I'm far from on the bandwagon, but they might be the favorite right now for the AFC's 6 seed.
Buffalo Bills	2-1	8	7	1	0.500	6	Took care of business against the Browns; hopefully the injury to C.J. Spiller doesn't cost him to miss much time. If Ryan Fitzpatrick could improve even a little, Buffalo could sneak into the playoffs.
Detroit Lions	1-2	7	9	-2	0.538	6	A fluky game all around in Tennessee, but that's a bad loss for the Lions. They're a last-second win against the Rams from being 0-3, a bad sign for a team with a brutal remaining schedule.
New Orleans Saints	0-3	7	8	-1	0.548	7	If we restarted the season, I would still like New Orleans. But I can't project them to do any better than 7-6 against the rest of the way against the toughest schedule in the league.
Carolina Panthers	1-2	7	8	-1	0.519	7	Projecting a 6-7 finish for a team with 6 home games left and no cupcakes until December. Playoff hopes on the brink this weekend in Atlanta.
Tampa Bay Buccaneers	1-2	7	7	0	0.481	6	A close in Dallas isn't anything to cry about. But if they have playoff aspirations, they'll need to beat Washington this week. Of course, the same holds true for the Redskins. Huge difference between 1-3 and 2-2.
Kansas City Chiefs	1-2	7	6	1	0.471	6	A save the season win in New Orleans gives them a one win bump. The good news is Jamaal Charles looks great and the AFC West is as wide open as it gets.
Minnesota Vikings	2-1	7	5	2	0.510	7	If we chose Pro Bowlers after week 3, Christian Ponder would make it in the NFC and Aaron Rodgers and Drew Brees would not. A huge win over the 49ers at least gives the Vikings some playoff hope.
Washington Redskins	1-2	6	6	0	0.534	6	I'm not going to sour on Robert Griffin III, but losing to Cincinnati and dropping to 1-2 is a blow to playoff aspirations when you have a tough remaining schedule. Do-or-die game against Tampa Bay this week.
Miami Dolphins	1-2	6	6	0	0.500	7	The run defense has been excellent and Reggie Bush looked as good as I've seen him in the first half against the Jets; fortunately his knee injury is not expected to cause him too miss much time.
Tennessee Titans	1-2	6	5	1	0.490	7	Jake Locker had a great game, but the defense and Chris Johnson are very shaky. When Locker is the consistent element of your team, you're in trouble.
Oakland Raiders	1-2	6	5	1	0.481	7	That was a gritty win against the Steelers, but Oakland has to get a lot better if they want to make the playoffs. Their defense is not very good.
St. Louis Rams	1-2	5	6	-1	0.553	6	The NFC West is brutal; the Rams are going to be heavy underdogs most weeks, making even 5 wins a challenging goal. They need to win at least one game the next two week as they host Seattle and Arizona or this season could go downhill in a hurry.
Jacksonville Jaguars	1-2	5	5	0	0.490	6	Blaine Gabbert still has a long way to go. Before the 80-yard throw to Cecil Shorts that won the game, he was averaging fewer than five yards per attempt this year.
Indianapolis Colts	1-2	5	5	0	0.490	7	Tough loss to the Jaguars and one where Chuck Pagano again made some questionable strategy calls. But I think Luck and the offense has enough firepower to get them 4 more wins.
Cleveland Browns	0-3	4	4	0	0.524	7	The schedule doesn't lighten up, and the Browns are staring 0-6 down the hole with trips to Baltimore and New York on tap. I'll wait until they lose both of those games before dropping them to 3 wins.

This week’s Fifth Down post looks at the surprising 3-0 Cardinals. Did you know that Arizona has been an underdog in each game this season? Since 1978, Arizona is just the 7th team to start 3-0 despite being given points by Vegas each week:

• 2010 Kansas City Chiefs: The 2009 Chiefs were 4-12, and 2010 wasn’t expected to be much better. But despite being underdogs against San Diego, Cleveland and San Francisco, the Chiefs won all three games, en route to a 10-6 season and an unlikely division championship.
• 2007 Green Bay Packers: Surprised to see the Brett Favre Packers on here? Green Bay had gone just 8-8 the prior season and faced a brutal early schedule in ’07. The Packers were a 3-point underdog against Andy Reid and Donovan McNabb’s Philadelphia Eagles in the opener and 2.5-point underdogs against the eventual champion New York Giants in week two. In week three, San Diego — 14-2 the prior season — was a 5.5-point favorite at Lambeau Field. Green Bay would start 4-0 and finish the regular season 13-3, but the team’s hopes ended in overtime in the N.F.C. Championship Game against the Giants.
• 2004 Jacksonville Jaguars: Jacksonville had back-to-back-to-back crazy, last minute wins to start the season 3-0. In the season opener in Buffalo, Byron Leftwich threw the game-winning touchdown on 4th and goal from the 7 with no time left to Ernest Wilford, giving the Jaguars a 13-10 win. Jacksonville led Denver 7-6 in their home opener the next week, but the Broncos had the ball with 37 seconds left on the Jacksonville 23-yard line. Then Denver running back Quentin Griffin fumbled, Akin Ayodele recovered, and the Jaguars were 2-0. The theatrics continued the next week against Tennessee. Trailing 12-7 with 13 seconds remaining, Fred Taylor scored a one-yard touchdown to keep the streak alive. But the anemic offense eventually caught up to the Jaguars, who missed the playoffs after going just 6-7 the rest of the way.
• 1997 Tampa Bay Buccaneers: Tampa Bay drafted Warren Sapp and Derrick Brooks in 1995. Tony Dungy came in 1996, and Tampa finished 6-10. The Buccaneers drafted Ronde Barber in 1997, and the key cogs that formed one of the league’s most dominant defenses were then in place. Tampa upset San Francisco at home and then won at Detroit and Minnesota in week three; the Bucs would eventually go to 5-0, before finishing 10-6 and earning a playoff berth.
• 1996 Carolina Panthers: Dom Capers completed one of the great coaching jobs in NFL history, taking Carolina from an expansion team in 1995 to the N.F.C. Championship Game in 1996. Carolina beat Atlanta and New Orleans, but really caught the attention of the NFL when they defeated San Francisco 23-7 in week three. Behind an excellent defense and an efficient offense, the Panthers finished the season 12-4.
• 1992 Pittsburgh Steelers: Chuck Noll’s last season was 1991, when Pittsburgh stumbled to a 7-9 record. Expectations were not high for rookie head coach Bill Cowher’s team in ’92. As 12.5-point underdogs in Houston, the Steelers pulled off the upset 29-24, before handily defeating the Jets and Chargers in weeks two and three. Pittsburgh finished 11-5 and made the playoffs.

What can we make of the Cardinals’ surprising start despite being underdogs? Combining the three games, Arizona has been underdogs of 17 points so far this year. How does that compare to other 3-0 teams?

From 1990 to 2011, there were 111 teams that started the season 3-0. Only the ’92 Steelers were bigger underdogs at -18 points. The table below divides the 111 teams into four groups, based upon the total number of points they were given (or they gave) in their first three games. For example, 19 of the 3-0 teams ended up being given more points than they gave (i.e., were underdogs) in their first three weeks; on average, they were 2.4-point underdogs, and on average, they ended the year with 9.5 wins (which means they were an even .500 over their last 13 games). As you can see, there is a pretty clear relationship between expectations and ultimate results.

Spread            #Tms   Avgline SeaWins
Underdogs         19     +2.4      9.5
0-9.5 pt Favs     29     -1.6     10.2
10-19.5 pt Fav    37     -4.9     10.9
20+ point Favs    26     -7.9     11.7

You can read the full post here.

Over at the PFR Blog, we used to post Checkdowns from time to time, shorter posts that were often just data dumps. Every once in awhile a random question would come to mind and we usually had the database power to answer the question. So after spending a few minutes get our results, but there was little more to say. The question had been answered, but there wasn’t enough to write a full post (or we weren’t interested in analyzing the results any further). But why hide the results?

So today I’m bringing the Checkdowns category to Football Perspective. I was wondering how often a team defeated both eventual Super Bowl participants in the same season. There have been 42 Super Bowl champions since the merger (no team could have done this in the pre-merger era), and surprisingly, 16 teams have accomplished this feat. Most recently, the 2010 Patriots defeated both the Steelers and Packers (playing with Matt Flynn and not Aaron Rodgers). The table below lists all 16 teams, with linkable boxscores to the games in question. I’ve also shown the team’s overall record and winning percentage during the regular season. As always, all columns are sortable.

Team	Year	SB Winner	SB Loser	Win %	Record
NWE	2010	GNB 31-27	PIT 39-26	0.875	14-2-0
PHI	2008	PIT 15-6	ARI 48-20	0.594	9-6-1
NYG	2008	PIT 21-14	ARI 37-29	0.750	12-4-0
JAX	2005	PIT 23-17	SEA 26-14	0.750	12-4-0
PIT	2004	NWE 34-20	PHI 27-3	0.938	15-1-0
WAS	2000	BAL 10-3	NYG 16-6	0.500	8-8-0
TEN	2000	BAL 14-6	NYG 28-14	0.813	13-3-0
DAL	1996	GNB 21-6	NWE 12-6	0.625	10-6-0
MIA	1993	DAL 16-14	BUF 22-13	0.563	9-7-0
SEA	1986	NYG 17-12	DEN 41-16	0.625	10-6-0
MIA	1985	CHI 38-24	NWE 30-27	0.750	12-4-0
CLE	1981	SFO 15-12	CIN 20-17	0.313	5-11-0
SDG	1980	OAK 30-24	PHI 22-21	0.688	11-5-0
DAL	1980	OAK 19-13	PHI 35-27	0.750	12-4-0
SDG	1979	PIT 35-7	RAM 40-16	0.750	12-4-0
RAM	1978	PIT 10-7	DAL 27-14	0.750	12-4-0

While some of these teams were in the same division as a Super Bowl participant, none of them swept their division foe and also defeated the Super Bowl representative from the other conference.

Each team on the list has its own interesting story. The 1981 Browns won just 5 games, but managed to beat both the 49ers and Bengals that season. The Don Coryell–Dan Fouts Chargers appear on this list in consecutive years. In 1979, San Diego blew out Pittsburgh and Los Angeles and finished the year with the NFL’s best record. But in one of the most improbable upsets in playoff history, the Houston Oilers and shocked San Diego and won, 17-14. In 1980, San Diego went 11-5 and won close games over both the Raiders and Eagles. After defeating Buffalo in the division round of the playoffs, Oakland upset San Diego 34-27 in the AFC Championship Game en route to becoming the first wildcard team to win the Super Bowl.

What sticks out to you on the table?

[Note: I’m scheduled to appear on The Bobby Curran Show on ESPN 1420 at just after 12:30 today. If you’re interested, you can listen here.]

If you weren’t watching the Steelers-Raiders game, you probably didn’t hear about Mike Tomlin’s gutsy call late in the 4th quarter. That’s because it worked.

On 3rd-and-1 with 4:34 remaining in a tie game, Pittsburgh had the ball at their own 29-yard line. The Steelers ran Isaac Redman over the left guard for no gain, leaving them in a precarious position. According to Brian Burke, immediately following Redman’s run, Pittsburgh had just a 34% chance of winning the game. This makes sense, because on average, punts from the 29-yard line end up with the other team gaining possession at their own 33-yard line (net of 38 yards). This conforms with Burke’s win probability model, which states that a team with 1st and 10 at their own 33 with 3:45 remaining has a 66% chance of winning.

That’s just the average, though. What about the specific teams in this case? Pittsburgh has a rookie punter, so we probably shouldn’t assume anything better would happen if they punted. The biggest variable in the Raiders’ favor was the presence of Sebastian Janikowski, an uber kicker who appears capable of connecting from anywhere on the opponent’s side of the field. Since 2010, Janikowski is 12-of-18 from 50-yards or more, including a miss from 65; on average, those 18 kicks were 55-yard attempts. Essentially, if the Raiders got 30 yards after the punt, they would have had a very good chance of winning the game.

Of course, the Steelers defense is generally one of the best in the league, even without Troy Polamalu and James Harrison. The Raiders had scored 3 touchdowns and a field goal on their prior 4 drives, although we shouldn’t let a small sample size persuade us too much. Additionaly, the Steelers would go three-and-out after converting the 4th down, and the Raiders ended up driving down the field and kicking the game-winning field goal, anyway. Again, it’s tempting to consider this when determining the Raiders’ odds of winning following a punt, but that’s the sort of logic I would rally against if the circumstances were different.

My gut tells me the Raiders being at home, having a pretty decent offense, and a super kicker would outweight the fact that generally Pittsburgh has a very good defense. So at a minimum, I’d argue that a Steelers punt gives the Raiders a 66% chance of winning.

If Pittsburgh converted, they’d probably have the ball somewhere between their own 30 and 35-yard lines; ironically, right where the Raiders ended up having the ball. That makes the calculus pretty easy: Pittsburgh would have a 66% chance of winning if they converted. You might argue that their odds would be greater, because of the presence of Ben Roethlisberger and a strong passing attack and considering Oakland’s pass defense is suspect. I’m sure Steelers fans were very confident that they would win the game after converting on 4th-and-1, but taking the conservative approach would say Pittsburgh had “only” a 66-percent chance of winning if they converted.

Now what were the odds of converting? As always, you can trade a larger sample for a more precise one, and determining the appropriate cutoff is tricky. I looked at all plays in the second half or overtime of games where the team had 4th-and-1 on their own side of the field. I also limited this to games where the team was trailing by 3 or fewer, tied, or winning, to make sure that defenses were truly focused. That left 64 examples from ’00 to ’11.

Teams converted 48 of the 64 attempts, or exactly 75% of the time. On average the teams gained 2.8 yards with a median gain of 2 yards. 55 of the 64 times the team ran the ball, with 44 of those being successful (80%). Only 4 of the 9 passes were successful, although the quarterbacks in the misses (Ryan Leaf, Byron Leftwich, Jason Campbell, Gus Frerotte and Alex Smith) leave something to be desired.

If we increase the sample to any 4th-and-1 attempt outside of the opponent’s 30 (so the first 70 yards of the field for the offense), teams converted 67% of the time. Let’s split the difference and give Pittsburgh a 70% chance of converting.

Facing 4th-and-1, Pittsburgh has a 70% chance of getting a 66% chance of winning the game; that means they have a 46% chance of converting the 4th-and-1 and of then winning the game. This ignores the possibility of Pittsburgh missing the 4th-and-1 and still winning the game, which is clearly non-zero. And remember, if they punt, they have only a 34% chance of winning. Even if we force them to automatically lose if they don’t convert, they still are more likely to win the game by going for it. In fact, they only need to convert half of the time on 4th-and-1 to make it a break-even proposition, and that’s still ignoring the possibility of failing and still winning.

What are the odds of that? With just under 4 minutes left, maybe not as bad as you think. If Oakland has the ball at the Steelers’ 29-yard line, they are extremely unlikely to be able to run out the clock. Pittsburgh called its first timeout before the 4th-down decision, meaning the Steelers still would have had 2 timeouts left if they could not gain one yard. Odds are the Raiders play it pretty conservatively and kick a field goal, and the Steelers have 2 minutes to go to kick a field goal to force overtime (or score a touchdown). That’s hardly a hopeless position in which to be.

Based on past history, Oakland would have had an 82% chance — not 100% — of winning if they had the ball at the Pittsburgh 29-yard line with 3:45 left in the game. Oakland’s odds would be higher because of Janikowski, although that would be counterbalanced by Pittsburgh having one of the best quarterbacks in the league in the two minute drill.

Add it all up, and it becomes a pretty obvious call… unless you’re risk averse. If Pittsburgh punts, they have just a 34% chance of winning, maybe even lower because of Janikowski. If Pittsburgh is successful, they are the team with the 66% chance of winning; if they miss, they still have an 18% chance of winning, based on having a small chance of winning in regulation and a decent chance of still going to overtime based on the amount of time remaining. Note that if there was one minute left, Pittsburgh’s odds of winning drop to just 9% if they don’t convert, but with nearly 4 minutes to go, they would not be out of the game if they failed. Considering a 70% success rate on 4th and 1, and they would have a 52% chance (66% x 70% + 18% x 30%) of winning they game if they went for it. In other words, punting it on 4th and 1 would drop Pittsburgh’s odds of winning from 52% to 34%, making this a significant and obvious decision for Tomlin.

To make punting the better decision, you would really need to skew the odds. If you have the utmost faith in your defense, perhaps you think the Raiders having the ball at their own 33-yard line with 3:45 to go doesn’t make them the favorite to win. If you view that as a coin-flip game — a pretty difficult proposition to believe — Pittsburgh would *still* benefit by going for it, since their win probability was 52%.

It also would have been wise to go for it if they were winning by 1 or 2 points… or even 3 points. A larger lead and it gets a little cloudy, but this is not much different than Bill Belichick’s decision against the Colts a few years ago. At the end of the game, especially in today’s high-octane NFL, you don’t want to be in a close game without the ball.

And as you can see, converting the 4th down was one of the biggest swings in the game. Take a look at Brian Burke’s win probability graph:

I said it was an obvious call unless you’re risk averse. As we all know, NFL coaches think conservatives are very liberal. On the surface this wasn’t a unique situation, but when you try to find comparables, you have to limit yourself. Since 2000, I looked at all situations where a team faced 4th-and-1 on their own side of the field, in a game where they were leading by 8 or less (or were tied), and with between 2 and 6 minutes remaining. There were only 20 situations like that, and 18 times the teams punted. The two other times? One came in week 17 for the Steelers in the game where Jamal Lewis crossed the 2000-yard mark and Pittsburgh was trying to close the curtain on a 6-10 season. A year after “4th and 2“, Bill Belichick went at it again against the Chargers. With exactly 2 minutes to go and the ball at the Patriots 49, New England ran it on 4th and 1. They missed, but went to win after Kris Brown could not connect on a 50-yard field goal.

I leave the baseball analysis to my brothers at baseball-reference.com, but I know enough to be dangerous. There’s a stat called BABIP, which stands for Batting Average on Balls In Play. A “ball in play” is simply any at bat that doesn’t end in a home run or a strikeout. The thinking goes that luck and randomness is mostly responsible for the variance in BABIP allowed by pitchers to opposing batters. Pitchers can control the number of strikeouts they throw and control whether they allow home runs or not, but they can’t really control their BABIP.

Therefore, if a pitcher has a high BABIP, sort of like an NFL team with a lot of turnovers, he’s probably been unlucky. And good things may be coming around the corner. A high BABIP means a pitcher probably has an ERA higher than he “should” and that his ERA will go down in the future. In fact, you can easily recalculate a pitcher’s ERA by replacing the actual BABIP he has allowed with the league average BABIP. And that ERA will be a better predictor of future ERA than the actual ERA. At least, I think. Forgive me if my baseball analysis is not perfect.

Are you still awake? It’s Monday, and I’ve brought not only baseball into the equation, but obscure baseball statistics. Let’s get to the point of the post by starting with a hypothesis:

Assume that it is within a quarterback’s control as to whether he throws a completed pass on any given pass attempt. However, if he throws an incomplete pass, then he has no control over whether or not that pass is intercepted.
[continue reading…]

The Tennessee-Detroit game was an instant classic today, with one of the wildest fourth quarters anyone will ever see. The 46 points scored were the second most in NFL history, trailing another recent game involving the Lions.

The scoring was crazy. Tommie Campbell had a 65-yard punt return at the end of the first quarter; a few minutes later, Jared Cook caught a 61-yard touchdown, and both were more incredible than I’m describing. But that was about it until the 4th quarter, save a one-yard Mikel Leshoure touchdown. Then, in the 4th, Nate Burleson (3 yards), Darius Reynaud (105), Nate Washington (71), Alterraun Verner (72), Calvin Johnson (3) and Titus Young (46) scored touchdowns, the last coming on a Hail Mary.

All told, there were 9 touchdowns scored in the game, and those touchdowns covered a total of 427 yards. The Titans became the first team in NFL history to score five touchdowns of 60 or more yards. But that 427-yard mark? That just sneaks into the top 10 all-time for yards on touchdowns in a game (click on any of the boxscores below to take you to that game):

That top game was one of the most memorable games of the ’60s and remains the game with the most points ever scored in an NFL game.

Of course, a lot of the craziness was coming from Tennessee, which managed to gain 374 yards on their touchdowns. That’s good enough for 2nd place — in the Redskins-Giants game, Washington’s touchdowns covered 403 yards. Here’s a list of the single teams to cover at least 300 yards on their touchdowns in a game:

It’s still too early to really put a lot of faith into the SRS ratings, but hey, we’ve got enough games to at least give it the old college try. As always, thanks to Dr. Peter Wolfe for providing the game scores for all of college football. As a reminder, here’s the system.

1) For each game not played at a neutral site, 3 points are given to the road team. After that adjustment, all wins and losses of between 7 and 24 points are scored as however many points the team won by. So a 24-10 road win goes down as +17 for the road team, -17 for the home team.

2) With one exception, wins of 7 or fewer points are scored as 7-point wins and losses of 7 or fewer points are scored as 7 point losses. So three 4-point home wins (+3 before the adjustments, +21 after) is worth more than two 10 point road wins and a 1 point home loss (+19 before, +19 after). The one exception is that road losses of 3 or fewer and home wins of 3 or fewer are graded as 0 point ties. So a 21-20 home victory goes down as a tie for both teams.

3) Wins/Losses of more than 24 points are scored as the average between the actual number and 24. This is to avoid giving undue credit to teams that run up the score. So a 67-point home win goes down as a 44-point win.

After four weeks, what are the results?

[continue reading…]

Yeah, yeah, Football Perspective turned 100 today, blah blah blah. I have something on my mind and I need the wisdom of this crowd. Below is a thought experiment.

You are highly incentivized to correctly guess how many interceptions a quarterback threw in a specific game. If you can answer it correctly within the one-tenth of an interception, you win. (You can assume this is the average of 100 games, if you like, but the point being your answers should not be limited to whole numbers.)

I will inform you that the quarterback in question threw exactly 13 incomplete passes (or each of the 100 quarterbacks threw exactly 13 incomplete passes).

Now, before you guess as to the number of interceptions thrown by this quarterback, I could also let you know how many pass attempts the quarterback had. But I don’t have to. Do you want to know how many attempts he threw, or is that information irrelevant?

If it *is* relevant information that you want to know, how does that knowledge affect your answer? If you knew he threw 45 passes, will you now project him to have more interceptions or fewer interceptions? Please vote in the poll below, but I’m just as interested in your comments. So get to commenting!

[poll id=”6″]

It’s been an incredible 100 days here at Football Perspective. When I started this site, I had no idea what to expect. Fortunately, the success so far at Football Perspective has exceeded my wildest expectations. Starting a football site in June isn’t the smartest thing in the world, but I think I’ve been fortunate to develop a pretty loyal fan base.

But I have the traffic numbers to prove that some of you weren’t here on day 1, or day 15, or day 37. At the top of each page at Football Perspective is a tab titled “Historical Archive.” One thing I know: very, very, few people have ever clicked that button.

But you should. If you want to catch up on any of the first 100 or so posts at Football Perspective, check out the historical archive tab. Let me know in the comments which post has been your favorite, and have a great rest of the weekend. I’ll be back tomorrow with another college SRS post.

Alex Smith has had an incredible career revival since Jim Harbaugh came to San Francisco. The first six seasons of his career, Alex Smith won just 38% of his 50 starts, but he has an incredible 15-3 regular season record since 2011 (83%). From 2005 to 2012, Smith had an ugly 72.1 passer rating, the worst of any quarterback with 1500 attempts over that span. Since Harbaugh came to town, Smith has a 93.6 passer rating, the 7th best mark of any quarterback over that time frame.

But there are two other, related, metrics, that indicate a fundamental shift in Smith’s style of play. In 2011, Alex Smith led the NFL in interception rate, but he also led the league in sacks. Smith threw an interception on just 1.1% of his passes in 2011 but took a sack on 9.0% of his dropbacks; this year, his sack rate has jumped to 10.9% while he has yet to thrown an interception.

Last year, the average quarterback threw an interception on 2.9% of his passes and was sacked on 6.4% of his dropbacks, meaning Smith’s interception rate was just 39% of the league average while his sack rate was 41% higher than league average. Smith also averaged just 197 passing yards per start, 80% of the league average metric.

It’s extremely early, of course, but Smith looks to be on a similar path this year. Which made me wonder: how often does a quarterback ^[1]For purposes of this study, I also limited the group to quarterbacks since 1978 who played for the same team for both years and who threw at least 200 passes in both years. have a two-year stretch with (1) an excellent interception rate, (2) a bad sack rate, and (3) a below-average amount of passing yards per game? The answer is very rarely.

There’s a lot of information to present, so I’ve overloaded the table below. This lists all quarterbacks since 1978 who over a two-year period had a sack rate at least 30% higher than average, an interception rate of 70% of league average or lower, and were below league average in passing yards per game. After the traditional categories, I’ve listed each quarterback’s sack rate, interception rate and yards per game, and then how their sack rates, interception rates and yards per game compared to league average. The last two columns show the quarterback’s record over those two years.

QB	Tm	Years	Att	Yd	TD	INT	Sk	SkYd	SkRt	INTRt	YPG	Sk%	INT%	YPG%	Rec	Win%
Charlie Batch	DET	1998--1999	573	4135	24	13	73	408	11.3%	2.3%	180	159.9%	68.3%	80.1%	11-11-0	0.500
Steve Young	SFO	1996--1997	672	5439	33	12	69	380	9.3%	1.8%	201	134.6%	55.6%	91.5%	21-6-0	0.778
Jim Harbaugh	IND	1996--1997	714	4690	23	15	77	446	9.7%	2.1%	180	140.7%	65.4%	81.9%	9-16-0	0.360
Jim Harbaugh	IND	1995--1996	719	5205	30	16	72	409	9.1%	2.2%	179	145.3%	69.2%	78.6%	14-12-0	0.538
Jim Harbaugh	IND	1994--1995	516	4015	26	11	53	291	9.3%	2.1%	149	156.2%	69%	64.3%	11-10-0	0.524
Ken O'Brien	NYJ	1987--1988	817	5263	28	15	87	631	9.6%	1.8%	202	134%	46.6%	91.9%	11-12-1	0.479
Neil Lomax	STL	1985--1986	892	5797	31	24	113	823	11.2%	2.7%	193	141.2%	65.9%	85.8%	9-20-1	0.317
Ken O'Brien	NYJ	1984--1985	691	5290	31	15	84	567	10.8%	2.2%	203	130.1%	52.8%	89.9%	12-9-0	0.571
Steve Bartkowski	ATL	1983--1984	701	5325	33	15	91	648	11.5%	2.1%	213	140.5%	50.8%	94.6%	9-16-0	0.360
Neil Lomax	STL	1982--1983	559	4003	29	17	74	549	11.7%	3%	182	147.7%	69.6%	82%	12-9-1	0.568

During Jim Harbaugh’s 4 years in Indianapolis, he was essentially Alex Smith. He had a 9.6% sack rate and a 2.1% interception rate, while averaging under 180 passing yards per game. When discussing Joe Namath, I noted that he almost never took sacks, which by some measures penalized him because it drove down his completion percentage and increased his interception rate. You can put Alex Smith and the Indianapolis version of Jim Harbaugh on one end of a spectrum and Joe Namath on the other. Both interceptions and sacks are bad, but to some extent, quarterbacks can decide whether they want to throw interceptions or take sacks. Smith, under Harbaugh’s tutelage, has clearly chosen the latter.

On a team with a great defense, that can work. Namath’s defenses weren’t always good, but when they were, the Jets were Super Bowl contenders. When the defenses struggled, Namath pressed even more, and ended up throwing even more interceptions. Smith is never asked to do too much, and Harbaugh has surrounded him with enough talent on the other side of the ball to make that a winning formula.

From 1994 to 1996, Jim Harbaugh went just 20-26 with the Colts. In 1997, Harbaugh had the lowest interception rate in the NFL and the second highest sack rate in the league. But the 1997 Colts ranked in the bottom 5 of the NFL in points allowed, passing touchdowns allowed, interceptions forced, rushing yards allowed, rushing touchdowns allowed and yards per carry allowed. The team went 3-13 overall, and 2-9 with Harbaugh, indicating that this conservative philosophy has its limitations.

Often times we use stats as a way to rank players, where more of one stat or less of another means a player is good, and less of one stat and more of another means a player is bad. But stats can also be used descriptively without overarching themes of good or bad. Just like some running backs are big and slow and others are small and fast, some quarterbacks are risky and some are risk-averse.

Harbaugh clearly was a risk-averse player in Indianapolis under Lindy Infante. What about the other players on the list? Conservative and risk-averse were good adjectives to describe Charlie Batch’s first two years in the league. In 1998, he had Barry Sanders, but Batch’s numbers were nearly identical both seasons (of course, you would normally expect some improvement by a quarterback betwen year one and two). It looks like he played things very safe as a rookie on a good team in 1998, and let’s not forget how he got the starting job: Scott Mitchell was benched after throwing a pick-six in overtime. We can safely conclude that Batch was told to avoid interceptions at all costs, for many reasons.

Steve Young led the league in passer rating in ’96 and ’97, and for many reasons, doesn’t really feel like a comparable player to Alex Smith. He had already been a two-time MVP by 1996.

Ken O’Brien was a very accurate quarterback who led the league in interception rate in ’85, ’87 and ’88. But he took a ton of sacks, in part because of a below-average offensive line. At his peak he was better than Smith has been so far — in ’85 he was 2nd in yards per attempt and he was 5th in that metric in ’86 — but there are some similarities between the two players.

From 1982 to 1986, Neil Lomax had a 10.5% sack rate but a tiny 2.8% interception rate; despite the conservative nature, his team went just 30-36-2 over that span. Lomax was outstanding in 1984, but otherwise was a solid but unspectacular player during this span (Lomax made the Pro Bowl in ’87 when he led the league in completions, attempts, and passing yards.) Lomax also benefited from consecutive All-Pro seasons from Roy Green in ’83 and ’84, but poor defenses prevented Lomax from compiling a winning record in St. Louis.

In the early ’80s, Steve Bartkowski had some success under Leeman Bennett, and made the Pro Bowl in ’80 and ’81. During those years, he was at or above average in sack rate and also interception rate, but then his interception rate improved dramatically in ’83 while his sack rate fell off for the rest of his career. A likely explanation is the hiring of Dan Henning that season, who may have emphasized a more conservative approach.

The two years before Harbaugh arrived, Smith had a 6.2% sack rate and a 3.1% interception rate, both numbers which were pretty close to league average. But Alex Smith 2.0 is not trying to prove to the world that he’s the #1 pick who can do everything; this version is concerned with minimizing risks at all costs. So far, it’s been a very successful formula.

[Today is a two-post day at Football Perspective. Check here for my week 2 power rankings, while Neil provides an innovative look at the biggest comebacks of the last 35 years in this post. — Chase

In my last post, I introduced a method of estimating the home team’s pre-game win probability in Excel using the Vegas spread:

p(W) = (1-NORMDIST(0.5,-(home_line),13.86,TRUE)) + 0.5*(NORMDIST(0.5,-(home_line),13.86,TRUE)-NORMDIST(-0.5,-(home_line),13.86,TRUE))

Let me explain the rationale behind the scary-looking equation. The first part represents the probability that the home team ends regulation time with a lead of 1 point or more, using Hal Stern’s finding that the home team’s final margin of victory can be approximated by a normal random variable with a mean of the Vegas line and a standard deviation of 13.86. The second part is the probability that regulation ends in a tie, multiplied by 0.5 (this assumes each team has roughly a 50-50 chance of winning in overtime).

With a small twist, we can also apply this formula within games, to the line-score data for every quarter. Within a game, the home team’s probability becomes:

p(W) = (1-NORMDIST(away_margin+0.5,-home_line*(minleft/60),13.86/SQRT(60/minleft),TRUE))+0.5*(NORMDIST(away_margin+0.5,-home_line*(minleft/60),13.86/SQRT(60/minleft),TRUE)-NORMDIST(away_margin-0.5,-home_line*(minleft/60),13.86/SQRT(60/minleft),TRUE))

This is the same equation as before, but we’re adding in Home_Margin (home team pts minus road team pts for the game, through the end of the quarter in question), reducing the effect of the home Vegas line linearly based on how much time remains in the game, and changing the standard deviation of scoring margin to become:

Stdev = 13.86 / sqrt(60 / n)

where n = the number of minutes remaining in the game.

These changes will help us estimate a team’s chances of winning at the end of each quarter. For instance, Monday night’s game — where the Falcons were a 3-point home favorite over the Broncos — goes from:

To this:

[continue reading…]

With week 2 in the books, it’s time to present updated win projections for each team. I kept half of the league’s teams at the same win total as last week, gave one additional win to one-quarter of the league, and took one win away from the remaining eight teams.

This week, the 49ers move in to the top spot. More on the remarkable transformation of Alex Smith tomorrow, but right now San Francisco will be the top team in most power rankings. With a great defense and an efficient offense, it’s hard to imagine the 49ers losing many games. San Francisco has held a 4th quarter lead in 19 of 20 games under coach Jim Harbaugh, and was tied in the 20th (against Baltimore). The only reason the 49ers may not win 12 games is that they could fall victim to the same trap that catches some teams that succeed with a conservative offense juxtaposed opposite an elite defense: a couple of random bounces can turn the game. These defensive-heavy teams generally live on the edge, with only a small margin for error most weeks.

Team	Wins	PrvWin	Diff	Comment
San Francisco 49ers	12	11	1	Alex Smith led the NFL in interception rate and in sacks in 2011; so far his interception rate is lower and his sack rate is higher in 2012. These metrics may be related.
New England Patriots	12	13	-1	I suspect that I will regret dropping them a win because the Patriots occasionally stumble early, but a home loss to the Cardinals can not go unpunished.
Houston Texans	11	10	1	No, destroying Jacksonville didn't tell us anything we didn't know. But dominating the bad teams is the sign of an elite team, so I'm happy to bump them this week. Some tough games coming up, but Houston shouldn't be afraid of any opponent.
Pittsburgh Steelers	11	10	1	I don't know if he's going to get MVP recognition, but I've been very impressed with Ben Roethlisberger in 2012. This is subjective, but I sense a lot of maturation to his game vs. where he was even two years ago. Steelers defense will be elite once they're healthy.
Green Bay Packers	11	11	0	Aaron Rodgers is currently 25th in the NFL in ANY/A. He's 27th in NY/A. Until Rodgers gets back to his old form, 11 wins is the ceiling for this team, but I'm not going to drop them after a win against the Bears.
Philadelphia Eagles	10	10	0	It's just perfect that Andy Reid's Eagles are the first team to ever start the season with two one-point wins. A 16-0 season followed by a division round blowout loss to the Giants would have Philly fans calling for Reid's head. Big win against the Ravens, but I was already high on the Eagles.
Baltimore Ravens	10	10	0	Joe Flacco was fantastic in the first half and then miserable in the second half. I kind of feel like we might see this comment again this year. Ravens still look like a 10-win team, and a road loss to an NFC team doesn't hurt too much.
Denver Broncos	10	10	0	Peyton Manning showed that he's got some rust to shake off, but the Broncos still look like a 10-win team to me. 5-1 in the division is attainable.
Atlanta Falcons	10	9	1	Falcons have already notched two wins and looked pretty good doing it. The schedule isn't easy, but Atlanta isn't going to be an underdog very often.
Chicago Bears	9	10	-1	The Bears blocking scheme looks like it was devised by the guy who came up with the Randy Ratio.
New York Giants	9	9	0	As my friend Mike Tanier tweeted during the game, the Giants condensed a typical season into 1 game against the Bucs. Eli Manning can take the Giants far, but let's not forget that New York has a brutal schedule and the Giants only won 9 games lats year.
Detroit Lions	9	9	0	Detroit needs to beat Tennessee and Minnesota the next two weeks, because the schedule is filled with landmines after the bye. The key to being a playoff team is taking care of business against the bad teams.
San Diego Chargers	9	9	0	The Chargers looking good early doesn't suit them well, as no one is talking about them. What is Norv Turner thinking?
Dallas Cowboys	9	9	0	A disappointing loss after a big win? No, my opinion of the Cowboys didn't change this week. I expect this to be a top-10 offense and at worst an average defense, which gets me to 9 wins.
New York Jets	9	9	0	Losing to the Steelers doesn't change much for the Jets. Neither will a win against Miami this weekend, if they get it. If not .
New Orleans Saints	8	9	-1	I still like the Saints offense, but the defense looks downright dreadful. I expect them to beat the Chiefs but lose to the Packers, so putting them at 7-5 after that is a nod to how good the offense can be. But this is far from a good team right now.
Seattle Seahawks	8	8	0	Seattle has a tough schedule but I like the makeup of this team. Very good defense, strong running game, and I think Russell Wilson can get them 8 wins. Yes, this was the comment from last week.
Carolina Panthers	8	8	0	Huge for the Panthers to erase some doubts and knock off the defending division champs. But this is a difficult schedule to maneuver and even if Cam Newton has a monster year the Panthers might only get 8 wins.
Cincinnati Bengals	7	7	0	The next four games: @Washington, @Jacksonville, Miami and @Cleveland. I wouldn't be surprised if the Bengals were 1-5 or 5-1 at the end of that stretch. For now, they are a mediocre team in a tough division.
Tampa Bay Buccaneers	7	7	0	I don't get the sense that Tampa Bay is quitting on anything this year. They are far from complete on either side of the ball, and most weeks will be difficult. The next two weeks take them to Dallas and then home for Washington; a split would be a success there.
Buffalo Bills	7	6	1	Bills notched a win and looked good doing it. The schedule is manageable and C.J. Spiller looks like a star. A loss in Cleveland this week would drop them back to 6 wins, but I don't see that happening.
Arizona Cardinals	7	6	1	Had them at 6 wins last week, and you can imagine that that none of those wins were projected to come against the Patriots. But still not convinced about this offense, hence just a one-game bump to 7 wins.
Kansas City Chiefs	6	7	-1	They've now been outscored by 204 points in their last 20 games. I kind of doubt the prescription for that is Drew Brees.
Washington Redskins	6	7	-1	The loss of Brian Orakpo is huge, but at least Washington still has Ryan Kerrigan! Losing to the Rams drops the Skins, but Robert Griffin III is for real.
St. Louis Rams	6	6	0	Impressive performance against the Redskins. 6 wins is a nod to Jeff Fisher, as I think the Rams are one of the least talented in the league. Yes, this was essentially the same comment as last week.
Miami Dolphins	6	5	1	Their remaining schedule is workable. Games against the 3 bottom feeders of the AFC South and Cincinnati will let us know if Miami is on their level or a tier above. Reggie Bush is second in the league in rushing.
Tennessee Titans	5	6	-1	No bigger disaster so far in the NFL than the Tennessee Titans. They might need to split against IND/JAX just to get to five wins. Chris Johnson looks lost while the defense is struggling. Don't expect any leniency this week when former coach Jim Schwartz brings his Lions to town.
Oakland Raiders	5	6	-1	Raise your hand if you thought Darren McFadden would stay healthy but be ineffective. Oakland has just two offensive touchdowns and Dennis Allen looks overwhelmed as a head coach. Allowing 263 rushing yards to Miami was embarassing.
Minnesota Vikings	5	6	-1	Their last six games feature 4 against the Bears and Packers and one against the Texans. Minnesota might need to go 4-4 over the next 8 weeks if they want to finish with 5 wins.
Jacksonville Jaguars	5	5	0	A loss in Indianapolis this weekend would be devastating. I'm not sure if they win more than two games outside their division (remaining non-division schedule is GB/CHI/DET; AFC East; CIN, @OAK).
Indianapolis Colts	5	4	1	Andrew Luck is too good to keep them at 5 wins. A playoff berth might be too much, but they can end up with the second best record in the division.
Cleveland Browns	4	4	0	Brandon Weeden looked much better and Trent Richardson looked great. Now the Browns look like a decent team with a brutal schedule instead of a bad team with a brutal schedule. Must-win game against the Bills this weekend ahead of road games against the Ravens and Giants.

**Update. It occurred to me that it would be easy to calculate remaining strength of schedule based on the projected wins I’m giving to each opponent. So I did that. The Saints and Giants have the toughest remaining schedules, while the Steelers and Packers have the easiest slates.

OppWin%	Team
0.549	New Orleans Saints
0.545	New York Giants
0.536	Minnesota Vikings
0.536	Arizona Cardinals
0.536	St. Louis Rams
0.531	Seattle Seahawks
0.527	Washington Redskins
0.518	Carolina Panthers
0.513	Dallas Cowboys
0.513	Philadelphia Eagles
0.513	Cleveland Browns
0.509	Baltimore Ravens
0.496	Cincinnati Bengals
0.496	Detroit Lions
0.496	New England Patriots
0.496	San Diego Chargers
0.496	Miami Dolphins
0.496	New York Jets
0.496	Oakland Raiders
0.491	Atlanta Falcons
0.491	Tampa Bay Buccaneers
0.491	Chicago Bears
0.487	Tennessee Titans
0.482	Buffalo Bills
0.482	Kansas City Chiefs
0.478	Denver Broncos
0.478	San Francisco 49ers
0.478	Houston Texans
0.473	Indianapolis Colts
0.473	Jacksonville Jaguars
0.451	Pittsburgh Steelers
0.451	Green Bay Packers

This week’s Fifth Down post focuses on the blueprint for 0-2 teams to make the playoffs.

Six N.F.L. teams have started the season 0-2, the lowest number since 1997. No doubt the most surprising of the winless teams is the New Orleans Saints, who happen to be the only winless team in the N.F.C.

Over in the A.F.C., the Jacksonville Jaguars, the Tennessee Titans, the Cleveland Browns, the Oakland Raiders and the Kansas City Chiefs are still looking for their first wins. Among the winless teams, the Chiefs head to New Orleans to face the Saints this weekend, in a desperation game for both.

Since 1990, only 22 of the 184 teams (12 percent) that started the season 0-2 ultimately made the playoffs. Of course, most of those 184 teams missed the playoffs not because they lost their first two games, but because they weren’t very good. Since the league expanded to 32 teams in 2002, only 11 of the 72 teams that started the season 0-2 would have made the playoffs had they won two more games.

It’s not the case that each team that loses its first two games has a 12 percent chance of making the playoffs. Just like a snowflake, every 0-2 N.F.L. team is unique, if not necessarily pretty. By placing the 22 “0-2 to playoffs” teams into specific groups, we can try to see if there is a blueprint out there for the current crop of 0-2 teams.

Made a key change (6 of the 22 teams)

Six teams made significant changes during the season, which made the team that took the field the first two weeks a different team from the one that made the playoffs.

In 1998, Glenn Foley and Rob Johnson went 3-6 as the starting quarterbacks for the Jets and the Buffalo Bills; they were replaced by the veterans Vinny Testaverde and Doug Flutie, who combined to go 19-4. Both Testaverde and Flutie made the Pro Bowl despite starting the season on the bench.

A similar story took place in Pittsburgh in 2002, as Tommy Maddox revived his career as turned the run-heavy Steelers into a more balanced and explosive offense. And, of course, Drew Bledsoe started the first two games of the season for the 2001 Patriots before Tom Brady took over for the rest of the season, setting the stage for a dynasty.

In 1993, the star running back Emmitt Smith held out for the first two games of the season, and Dallas struggled without him. In 2008, the Dolphins got a similar boost to their running game when they introduced the Wildcat formation to the league in Week 3 against the Patriots.

2012 blueprint: These changes are hard to see until they happen. It’s possible that the Tennessee Titans could switch from Jake Locker to Matt Hasselbeck, who played well at times in 2011. In Jacksonville, Maurice Jones-Drew’s holdout is already over, although it was a poor pass offense that sank the team in Week 2. For the Raiders’ sake, there must be better options on which to pin their hopes than Terrelle Pryor. And unfortunately for the Saints, Sean Payton isn’t walking through that door.

High-scoring offenses (4 of the remaining 16; 4 of 22 over all)

The Saints have scored 59 points through two games, the fourth-highest total of any team to start 0-2 since 1990. The 1994 Patriots (70 points), the  2008 Chargers (62) and the 2002 Vikings (62) were the only teams to score more points, and the Patriots and the Chargers each went on to make the playoffs. Only 15 teams even reached 45 points after two games, and one of those was the 2007 Giants, an eventual Super Bowl champion (the other was the 2002 Atlanta Falcons). That means 27 percent of the teams to score at least 45 points but start 0-2 went on to make the playoffs, and that number probably underestimates New Orleans’s chances considering just how effective the Saints’ offense has been over the past half-decade.

2012 blueprint: The Saints stand out as the 0-2 team most likely to turn it around. High-scoring teams always have a chance to win, and the Saints are still capable of winning a bunch of shootouts in 2012.

You can read the full post here.

Also, my Pro-Football-Reference comrade Mike Kania is at it again with the week 2 penalty data:

Some additional thoughts…

No one who watched the games this weekend came away thinking the replacement referees had no impact on the game.  But to understand exactly what happened, you need to dig deeper than the raw data, which reflects no change on the surface.  I noted last week that: “On average, over the last 10 years, 208 penalties have been called in Week 1. With the replacement referees over the last week, there were 206 penalties, in line with historical averages.”  There were 211 penalties in week two, which wouldn’t ordinarily make anybody bat an eye.

There were some interesting changes in the penalty data in week two.  As you may recall, there were 26 defensive pass interference penalties enforced in week 1 — an extremely high number — compared to just 5 defensive holding penalties and only one illegal contact penalty.  In week two, only 14 defensive pass interference penalties were enforced, but the number of defensive holding (10) and illegal contact penalties (6) each rose by five.  This is more in line with historical data, and a good sign that the replacement officials aren’t simply calling everything pass interference (Ike Taylor’s penalty against the Jets, notwithstanding).

There were fewer personal foul and unnecessary roughness penalties enforced in week one of the 2012 season than in week 1 last year, but things changed quickly in week two.  Teams had 23 total personal foul or unnecessary roughness penalties enforced against them in week 2, compared to just 11 last week.  Of course, as most fans who watched the majority of the games this weekend noticed, there was good reason for the uptick.  With the regular officials not around, the N.F.L. players seemed to treat the replacement officials like substitute teachers, consistently pushing the boundaries to see what they could get away with.  According to Matt Pomery, the manager of NFL Network Research, the average game in week two was 3 hours and 14 minutes, tied for the third longest average game time in regulation (excluding overtime) in a week in the last 20 seasons.

Last week, I hinted that there may be a bias by the officials in favor of the home team, as these less-experienced referees may be more likely to side with the voices of the crowd.  That hypotheses certainly wasn’t disproved this week, as 14 of the 16 home teams won, the first time 14 home teams have won in a week since the league expanded to 32 teams. So far this season, there have been 231 penalties against visiting teams and only 188 penalties against the hosts.  That ratio — road teams having to deal with 23% more penalties — is far out of line with historical data, which informs us that road teams had 7% more penalties enforced against them than home teams from 2000 to 2011.

An interesting discussion broke out in the comments to Friday’s post, as sn0mm1s pointed out a bizarre result he’d come across. Before the NFL adopted the 2-point conversion option following touchdowns, teams that trailed by 8 points entering the 4th quarter had a lower winning percentage than teams that trailed by 9 points.

My initial assumption was that this observation is tangentially related to a couple of posts Doug and I had at the old PFR blog where we saw that teams that scored 16 points have had a better winning percentage than teams that scored 21 points and about why teams that scored 13 points had fared better than teams with 14 points. In those cases, scoring 13 or 16 points wasn’t causing teams to win (relative to scoring 14 or 21 points) but rather was an effect of game situations. Teams that scored 13 or 16 points were occasionally kicking field goals to take the lead, while teams that scored only touchdowns were doing so because they were trailing big and eschewing field goal attempts.

In this case, the effect is less clear. Let’s start with the facts. From 1970 to 1993, take a look at the success of teams entering the 4th quarter trailing by 7, 8, or 9 points. The fifth and sixth columns there show how many points the teams had scored and allowed just before the start of the 4th quarter, while the last two columns show the final points scored and allowed data.

Just so we’re clear on how that table reads, there were 594 games where a team trailed by 7 entering the final frame, and they won 21.3% of those games (including ties). On average, at the start of the 4th quarter, they had scored 9.3 points and allowed 16.3 points, and, on average, the game ended with them scoring 15.6 points and allowing 22 points.

It shouldn’t be surprising that trailing by 8 entering the 4th quarter is worse than trailing by 7 in any environment, but especially so in one that does not have the two-point option. The surprising part is that 20% of teams won games when trailing by exactly 9 points at the start of the 4th quarter. That’s a particularly high number. It is possible that there is nothing to this effect; this distinction would fail standard significance tests, ^[1]If we include every game in NFL history, the results would only be significant at the p=0.13 level; over the period form ’70 to ’93, it would only be significant at the p=0.25 level. but we also know that we don’t always want to apply such methods. I’ll get into this more, but suffice it to say I do think there is something going on here, even if there is almost certainly not a causal relationship.

A look at two types of scores in each group is instructive. Trailing 14-6 or 21-13 entering the 4th quarter, teams won just 10 of 63 games (16%). On the other hand, when trailing 16-7 or 23-14, teams have pulled off the upset 13 of 52 times (25%).

I’ll note that there are some weird things going on with the data, which does make me wonder if this is due to randomness. For example, 32 of the 52 teams (62%) trailing 16-7 or 23-14 were at home compared to just 26 of 63 teams (41%) trailing 14-6 or 21-13. Overall, teams trailing by 9 points were significantly more likely to be at home (57% of the time) than teams trailing by 8 points (43%). So that’s… odd.

Although that doesn’t tell the full story, ^[2]i.e., this is not an example of Simpson’s Paradox as 9-point teams still did better than 8-point teams regardless of location. In 70 home games, 9-point teams won 15 games, for a 21.4% rate. In 52 road games, 9-point teams won 19.2% of the time (10 games). In 50 home games, teams trailing by 8 when entering the 4th quarter won 20% of the time, but on the road, they won just 7 of 66 such games (10.6%). Road comebacks when trailing by 8 points were extremely rare, while road teams trailing by 9 won nearly twice as often.

I have point spread data from 1978 to 1993, ^[3]Ignoring games played with replacement players in 1987 so let’s re-work the data around that time frame. Not much changes — 50 of the 88 teams (57%) to enter the 4th quarter trailing by 9 were the home team while just 38 out of 86 teams (44%) that trailed by 8 at the start of the final quarter were the hosts. Those 88 teams trailing by 9 points were, on average, 1.1-point underdogs entering the game. Of the 86 teams trailing by 8 points, they entered the game as … 1.2 point underdogs, on average.

I also looked at the scoring logs in the 4th quarter. We have 174 games to look at, with a nearly 50/50 split between 8- and 9-point games. There were 44 games where the trailing team did not score in the 4th quarter. 22 were in 8-point games, 22 were in 9-point games. So nothing there.

On the other hand, that makes the rest of the results more pronounced. This means that in 20 of the 66 games where a team trailing by 9 in the 4th quarter scored, they won, vs. 13 of 68 games when trailing by 8. Can we get any more detail?

Unfortunately, nothing else really interesting comes out of this. The teams trailing by 9 were more likely to kick field goals and the teams winning by 9 were less likely to pass for touchdowns. It is certainly possible that teams leading by 9 became more conservative; it doesn’t make rational sense in an era before the 2-point conversion for teams to treat an 8-point lead differently than a 9-point lead, but it’s possible that coaches did.

At this point, I pretty much ran out of ideas. Except for this: I have play by play logs since 2000. This is obviously during the 2-point conversion era, but maybe something useful would come of it?

From 2000 to 2011, 12 of the 59 teams to enter the 4th quarter trailing by 9 went on to win, or 20.3% of all teams. Over that same span, only 12 of the 85 teams trailing by 8 entering the 4th quarter — or 14% — ultimately won. ^[4]It’s probably more appropriate to note that 9 of the 85 teams went on to force overtime — and all three won. If we counted all OT games as tied, the winning percentage would drop to 12%, … Continue reading

So again we’re seeing significant differences and unexpected results. This makes me think it is likely that something actually is going on here, as a different set of data produced the same results despite it being less likely to have done so because of the two-point option.

On average, the 9-point games were 18.0 to 9.0 after three quarters, while the 8-point games were more high-scoring with an average of 20.2-12.2. Unlike with the prior data set, just 24 of the 59 nine-point games (40.1%) saw the trailing team at home; in addition, 33 of the 85 eight-point games (38.8%) were at home. This is more in line with what you would expect, as home teams are less likely to be trailing late in games. My guess is the numbers in the prior set on home/road splits were just random results.

Here’s another area where the data diverges. On average, the 8-point trailing teams were 2.8-point underdogs, while the 9-point trailing teams were 0.1-point favorites. Thirteen times since 2000 a team was favored to win by at least 7 points but then trailed by 9 entering the 4th quarter; four of those teams still went on to win (30.1%). Similarly, 3 of the 10 teams to trail by 8 after being a touchdown or more favorites went on to win. So in this case, it’s at least possible that truly better teams end up trailing by 9 points rather than 8.

I looked at the numbers through 3 quarters, and well, it wasn’t all that helpful.

Margin	G	PFs4Q	PAs4Q	Line	Yards	Rsh	Pass	RYD	PYD	TO	OPPTO	NY/A	YPC
-8	85	12.2	20.2	2.8	235.8	19.8	26.4	87	148.8	1.2	0.8	5.6	4.4
-9	59	9	18	-0.1	198	18.2	23.6	73.8	124.2	1.5	0.7	5.3	4.1

The teams trailing by 9 points seem to have played worse on offense, gaining significantly fewer yards through 3 quarters, averaging fewer yards per pass and per carry, and scoring 3.2 fewer points. That doesn’t exactly scream “more likely to score more points in the 4th quarter” but perhaps it also plays into the theory that the opponents are letting up.

Generally, teams trailing by 9 points have scored touchdowns, as a 9-point differential comes from the opponent getting 3 more FGs. 16-7, 19-10, 23-10, and so on. On the other hand, trailing by 8 usually happens when you score 2 FGs and your opponent scores 2 touchdowns. So you’re down 14-6, or 17-9, or 21-10.

Maybe this “trailing by 9” thing is random variation. Maybe it’s something I haven’t considered. The best I can come up with right now is that teams up by 9 really are letting the pedal up on the gas. Often times they will have scored on 3 more drives than their opponent, whereas the 8-point games often feature teams that have scored on the same number of drives. In addition, the overall offensive stats are closer in the 8-point game. If just a few teams up by 9 gave up too soon based on how the game unfolded, that would be enough to skew the numbers. But for now, that’s just a guess.

Let’s run through six of yesterday’s games and look at some of the more interesting stats from week 2:

Carolina 35, New Orleans 27

We need to incentivize this defense: Half of Carolina’s ten drives went for 58 yards or more, with four of them ending in touchdowns. Like every year since Sean Payton and Drew Brees came to town save 2009, this Saints defense simply isn’t very good. New Orleans allowed the Panthers offense to score 4 touchdowns a week after allowing the Redskins offense to score 4 touchdowns. The Saints ranked last in expected points added and win probability added, and I don’t know if there’s much reason for optimism in New Orleans. The offense is operating at something below peak levels but above the standards of mere mortals, and that will be enough against some opponents. New Orleans’ pass defense ranked last in PFR’s Expected Points Added metric in week 1, and then allowed three Panthers to rush for over 50 yards on Sunday. Against the Chiefs this week, the Saints can just bring their offense and win, but a week 4 trip to Lambeau Field could be a season-defining game for New Orleans.

To be the best…: For Carolina, knocking off the Saints is the next step towards becoming a playoff contender. The Panthers struggled in close games last year and in week 1, and Cam Newton still has just one 4th quarter comeback win in his career. But beating a team that swept them last year is a sign that Carolina still could be a breakout team in 2012, despite that ugly performance against Tampa Bay in week 1. Oh, and since this is called Stats Recap…. Cam Newton now has 3 games with 250 yards passing, 50 yards rushing, and at least one touchdown on the ground and through the air. Since 1960, only Jeff Garcia, Kordell Stewart and Steve Young have reached those marks three times, and none of them hit those thresholds a 4th time. And in case you forgot, yesterday was Cam Newton’s 18th game of his career.

Indianapolis 23, Minnesota 20

Rookie quarterback saves rookie coach. Andrew Luck had impressive numbers — he gained 224 yards on 31 passes and threw 2 touchdowns — but he was outstanding against the Vikings. He led all quarterbacks in Expected Points Added and ESPN’s Total QBR, a sign of just how effective he was against the Vikings. And he was at his best late. Following a Minnesota touchdown to tie the game, the Colts got the ball on their own 20 with 31 seconds remaining. Luck threw consecutive deep passes to Donnie Avery and Reggie Wayne for 20 yards, and a Minnesota offsides penalty wiped out his third throw, a seven-yard completion to Avery. The Colts kicked the game winning field goal in the first of what should be many performances where Luck was the main reason the Colts won.

On the coaching front, it was disappointing. With 2 minutes to go in the first half, the Colts faced 3rd and 1 on the Minnesota 8-yard line. Indianapolis ran up the middle for no gain, and then kicked the field goal. Going for it on 4th-and-1 is an obvious no brainer, even if it going for it is slightly less valuable as the half is winding down (in the event of a failed conversion, you have pinned your opponent back and are likely to score next; the calculus changes a bit with only 120 seconds remaining). This comes after last week, when Chuck Pagano elected to punt on 4th and 1 on the Bears 47-yard-line.
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As a guy who loves the Simple Rating System, the start of the college football season can be frustrating. Until we get a few weeks in, we can’t really use the Simple Rating System to analyze results. A similar problem affects all computer rating systems. Jeff Sagarin notes in his rankings that that for the first few weeks of the season — until the teams are “well connected” — he uses a starting weight to help match the results to our expectations. By “well connected” Sagarin simply means we need the teams to play each other more frequently so we can have more confidence in our results.

So while it’s fun to watch the games, part of me is disappointed that I can’t run all the teams through the simple rating system. If only we could double the sample size of the games played — after six weeks, teams are fairly well connected — we’d be in business.

Well, I thought of a cheat to do just that. Each game has a point spread, a quantitative expectation of how each team will perform according to the best minds in the betting community. So when Florida plays Tennessee, there are two games that are happening. One is the result of the actual game, Florida winning by 17. The other is what we expected to happen, which is Tennessee winning by 3.

It might seem odd to use projected results as inputs into the SRS. And maybe it is. But why not? It’s similar in ways to using preseason projections, and I generally have faith in the betting community. Plus, what else I am supposed to do until a few more weeks.

So here’s what I did. I took every game where the point spread was less than 35 points (under the assumption that games with ridiculous betting lines or that don’t even have a line are just tune ups) and counted it twice. Once for the actual results, and once for the point spread.

Washington, for example, has played 3 games this year. They played San Diego State, were favored by 15, and won by 9 points. They played LSU, were 22.5 point underdogs, and lost by 38 points. And they played Portland State, were 32-point favorites, and won by 39 points. As a result, in six “games” this year, Washington won by an average of 5.8 points. Their strength of schedule was pretty tough, too — iterated, of course — so they will fare pretty well. How does the rest of college football look?
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Three teams have started 0-2 and won the Super Bowl. In 1993, the Dallas Cowboys started 0-2 in part because Emmitt Smith was holding out for a new contract. In 2001, the New England Patriots — with Drew Bledsoe as starting quarterback — began the year 0-2, before Tom Brady got his first professional start in week three. In 2007, the Gianst allowed 80 points in the first two weeks of the regular season, months before shutting down the highest scoring offense in NFL history in Super Bowl XLII.

There have been 68 teams to win a championship since 1950, including the six AFL champions in the pre-Super Bowl era. 41 of those teams started the season 2-0, and the group as a whole had a 0.790 winning percentage after two weeks. That shouldn’t be too surprising, as the best teams are likely to win most weeks. The last six Super Bowl champions not named the Giants have started the year 2-0.

But which Super Bowl champ had the greatest points differential after two weeks? One team started the year with wins of 34-3 and 39-13 (and won 42-10 in week three).

Note: Tomorrow, in lieu of Sunday trivia, I’ll present the first edition of the SRS for college football teams.

Let’s start with the obvious: your odds of winning when trailing by 15 in the 4th quarter are really, really low. From 1994, the first season the two-point attempt was introduced to the NFL, to 2011, 68 teams have entered the 4th quarter trailing by exactly 15 points. Only one of those teams won.

Over that same period, there have been 81 times when a team scored a 4th-quarter touchdown when trailing by 15 points, cutting the lead to 9 (pending the extra point or two-point conversion). Only 5 of those teams went on to win the game, with the most recent occurrence happening last year when the Dolphins were Tebowed.

So when trailing by 15 in the 4th quarter, even after scoring a touchdown, your odds of winning aren’t very good. But of those 81 teams that scored a fourth-quarter touchdown to cut the lead to 9, only nine of them went for two after the touchdown. While the time remaining could play a part in the decision, the fact is most of the other 72 teams made a strategic error in kicking the extra point when trailing by 9 points.

The last ^[1]Technically, the last team to do this was the 2007 Jets. Trailing by 15 points with 3 seconds left, the Jets threw a touchdown as time expired, and then went for and converted a totally meaningless … Continue reading coach to recognize that going for two is the correct call? College football’s renegade, Steve Spurrier. In college football, the two-point conversion has been around since 1958, and in general, college football coaches are much more comfortable ‘going for 2’ than their NFL counterparts. ^[2]It’s worth noting that the American Football League had the 2-point conversion, and several teams there took advantage of the rule. In a 1965 game against the Oilers, the great Hank Stram … Continue reading

Against the 49ers on Sunday, with 6 minutes left in the final frame, Aaron Rodgers connected with James Jones to cut the lead to 30-21. At that point, attempting a two-point conversion is the obviously correct call, in an attempt to cut the lead to 7. I was disappointed but not surprised that Mike McCarthy decided to go for 1. But what did surprise me was seeing a number of smart people on twitter disagree with me that going for 2 is the right call. So I figured I’d devote a post to explaining why in this situation, it’s a no-brainer to go for two.

The counterargument goes something along the lines of “just take the points, that way it is a one-score game.” Essentially, people are afraid of missing the two-point attempt and trailing by 9 points. But it’s not a one-score game. Trailing by 8 isn’t a one-score game if you are going to fail on your two-point try. And there’s no reason to think your odds of converting a 2-point attempt are higher when trailing by 2 than by 9. Trailing by 8 is a 1.5-possiession game; half the time it is a 1-possession game, and half the time it is a 2-possesion game. To simply put your head in the sand and say “I don’t wanna know!!” may keep hope alive longer but it lowers your odds of winning.

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In my experience, most power rankings are pretty vague about what the rankings are supposed to represent. In general, ranking systems are usually either retrodictive or predictive, meaning they’re either supposed to explain the past or predict the future.

If you’re going to make power rankings, you should be clear what you’re rankings are supposed to represent. Are they a snapshot of how good teams are right now? Are they a prediction for which teams have the best odds of winning the Super Bowl? Are they supposed to predict which teams will end the year with the best record? Are they supposed to reflect what we have seen so far?

Nearly every set of power rankings conflate these principles. It’s true that in some ways, the philosophies of retrodictive and predictive are less binary and more two ends of a continuum. On the far left end of the spectrum you have the actual NFL standings, published every day. On the far right you would have the Las Vegas power ratings which drive the point spread in each game (or the Simple Rating System). Power rankings sort of hover in the middle, with writers generally ranking teams by record but then bumping up the teams they like because they think they will play better soon.

Another component of most power rankings: they’re usually forgotten as soon as next week’s rankings are released. But I want to create power rankings that are testable. So here’s the plan. Each week, I’m going to predict how many wins I expect each team to have by the end of the season. Right now, this isn’t so easy. By week 16, it will be really easy. I’m curious to see how my thoughts change on certain teams throughout the year, and the goal is to put up a cool chart at the end of the season tracking the progress. At least, that’s the plan.

Without further ado, here are my Week 1 Power Rankings, which simply represent my best guess — as of today — as to the total number of games each team will ultimately end up winning this year.
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For the past few years, I have written a weekly in-season article for the New York Times’ football blog, The Fifth Down. We are teaming up again this year and below is an excerpt from some thoughts I had on the replacement refs:

It was an uneventful Week 1, in a good way, as the N.F.L. replacement referees did not steal much attention from the players on the field.

There were the usual complaints and borderline calls, including a flag thrown on a textbook block in the back by Green Bay on Randall Cobb’s touchdown return against San Francisco on Sunday. Instead, the referees picked up the flag, and the Packers’ score counted. In Arizona, an inexcusable gaffe allowed Seattle to have four timeouts as they frantically attempted to tie the game. But both the Cardinals and the 49ers won, muting any cries about the replacement officials.

It’s difficult to test whether the replacement referees were any different than the regular crews. Tests work best with objective data, and the performance of referees is inherently subjective. But we do have some numbers to go by.

Some have argued that the officiating crews let defensive backs play more physically than the regular officials have allowed in recent years, thinking that the replacements were loath to throw huge flags in key situations. But in that infamous final minute in Seattle, the referees flagged Arizona for defensive pass interference on two key plays. In fact, there were 29 defensive pass-interference penalties called by the referees in Week 1, the most during an opening week since at least 2000. Over the last 10 years, there have been 130 such penalties called during the opening weeks of N.F.L. seasons, or 13 per year.

Despite the subjective arguments, replacement officials called defensive pass interferences more than twice as frequently as the regular crews have done in Week 1. Maybe coaches were instructing their defensive backs to play more physically, hoping that the referees would be afraid to throw the flag. Regardless, the evidence in no way supported the idea that the replacements were letting defensive backs get away with more.

What about penalties over all? On average, over the last 10 years, 208 penalties have been called in Week 1. With the replacement referees over the last week, there were 206 penalties, in line with historical averages. Penalty yardage was slightly up, most likely as a result of more defensive pass interference calls, but that metric was also in line with norms.

You can read the full article, here.

Since then, Mike Kania, who refers to himself as the code junky for Pro-Football-Reference and the other Sports-Reference websites, sent me some additional data. The table below shows the number of each type of penalty called in week 1 of the 2011 season and week 1 of the 2012 season ^[1]I’m not sure why Mike and I have slightly different numbers on defensive pass interference penalties; it might be that 29 were called and 26 were enforced (i.e., 3 were declined), but I … Continue reading, along with how many penalty yards were associated with each penalty. In the far right three columns, I’ve shown the difference between the two seasons.
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How much should the week 1 results impact your projections for team wins in 2012? That’s what this post will attempt to answer.

Let’s start with the basics. Before the season, if you knew nothing about a team other than how many games it won the prior year, how many wins should you project for such team this year? This is a relatively simple question to answer giving enough historical data and a program to perform a regression analysis. After doing just that, I can tell you that you should project each team to win 5.28 games plus 0.34 times the number of games they won in the previous season. So a 4-win team projects to 6.6 wins, a 6-win team projects to 7.3 wins, and an 11-win team should drop down to 9.0 wins. There is a significant regression to the mean force at play here, unsurprisingly. Even a 15-win team projects to “only” 10.4 wins.

Of course, this is far from perfect. The R^2 of this model is just 0.11, an indication that there are significantly more factors at play in determining a team’s record than their amount of wins the prior year. Well, duh. However, we can improve on that 0.11 number. If we use SRS ratings as inputs instead of wins, that R^2 goes to 0.15. This is not surprising, and this is exactly what I mean when I say that the SRS is more predictive of future performance than wins. What’s the best-fit formula?

Each team should win 8.05 games plus or minus 0.196 wins for every point a team had in the SRS in the prior season. This means that a team that was 5 points better than average should be projected to win 9.0 games the next season, while a team that was 11 points below average in 2010 projects as a 5.9-win team in 2011.

At this point, you might think: okay, great, now let’s combine them both! Let’s use both SRS ratings and team wins as inputs and Year N+1 wins as outputs. Well, doing that adds nothing to the predictive power of the model. This is another reason not to use actual records for predictive purposes. For illustrative purposes, I performed such a regression, and the model tells us that the “record” variable has a p-value of 0.61, making it nowhere near statistically significant (and the weight on the variable was -0.04, making it practically insignificant as well). In layman’s terms, what this means is that if we already know a team’s SRS ratings, also knowing their won-loss record is not helpful to predicting their future performance.

Now have a simple way to project each team’s number of wins in a given season: 8.05 + 0.196*each team’s SRS rating from the prior year. You might wonder why that number is at 8.05 and not 8.00; that’s because I didn’t simply use the standard, regular season SRS ratings, but rather I calculated each team’s SRS score based on all of their games, postseason included. Therefore, the average is slightly higher than 8.00 since the best teams played the most games. There’s no good reason to ignore the postseason when projecting future performance (other than laziness, in which case I approve). I didn’t put special weight on games from the 2011 playoffs, but simply counted them as additional games. Anyway, the table below shows the SRS ratings from each team in 2011 and their projected 2012 wins based on the above formula:
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The first Monday night of the regular season gives us two football games to enjoy. At 7:00, the Bengals travel to Baltimore giving Cincinnati an immediate chance to prove that last year’s playoff berth was no fluke. At 10:15, the Chargers travel to Oakland and look to show that missing out on the last two postseasons was nothing more than a fluke.

Let’s start with the Bengals. In 2011, Cincinnati lost every game they played against playoff teams and won every game against non-playoff teams. The nine wins came against Cleveland (twice), Buffalo, Jacksonville, Indianapolis, Seattle, Tennessee, St. Louis and Arizona. On the other hand, the Bengals lost twice each to Pittsburgh, Baltimore, and Houston, and lost in Denver and San Francisco early in the year.

That is more an interesting bit of trivia than anything else. No team since the merger had ever done that before, and only two pre-merger teams managed to pull of that feat. ^[1]In the early ’50s, the playoffs consisted of just a championship game between the two division winners. In 1953, the 49ers lost both games division rival Detroit and to Eastern division champ … Continue reading For the Bengals, the odd split is more an embarrassing blemish that rival fans can point to than anything else. It’s not as if the Bengals can’t beat playoff teams, it’s simply that they didn’t. In 1969, the Cowboys went 0-3 against playoff teams and 11-0-1 against non-playoff teams; the next season, Dallas made the Super Bowl and in 1971 the Cowboys won it. Lombardi’s Packers pulled off the same feat in the middle of their great run: in ’63, Green Bay was 0-2 against playoff teams and 11-0-1 against non-playoff teams a year after having one of the most dominant seasons in football history. The Bengals weren’t a great team last year, but had they gone 7-2 against non-playoff teams and 2-5 in the regular season against playoff teams, would they — or rather, should they — be viewed as any better? Swapping a win against Pittsburgh and Baltimore for losses against say, Cleveland and Seattle?
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Welcome back, NFL. The first of 17 great Sundays is upon us, and this is always one of my favorite days of the year. I’ll even put up with the garbage that is pre-game and post-game shows to watch football from 9 in the morning until after midnight. I’m sure many of you will do the same, so good luck to whomever you’re rooting for today.

In Friday’s post, I noted that Anquan Boldin gained 217 receiving yards in week 1 of the 2003 season, trailing only Frank Clarke (1962) for most receiving yards on opening weekend.

But as you get ready for today’s actions, chew on this trivia question. Which player gained the most rushing yards in week 1 of an NFL season? Like yesterday, I’ve given you a special hint with this mystery photo.

Yesterday, I wrote about the interesting career of Anquan Boldin. If I had written that article a year ago, I would have noted that Boldin was the all-time leader in receptions per game in NFL history. At the time, Boldin had 650 receptions in 111 games, an average of 5.86 receptions per game. But after just 3.6 catches per game with the Ravens in 2011, Boldin’s rate dropped to 5.66 for his career, good enough for only third place in NFL history.

But who is number one? Jerry Rice is one of 10 players to average at least five receptions per game for their career, but he’s number 10. With 303 career games, there’s a limit to what we could have expected from him. The career leader in receptions per game averaged exactly 5.80 receptions per game. To help you out, I broke out my MS paint skills to give you a photo of this man. Can you guess who it is?

Nine years ago today, Anquan Boldin became a household name in his very first game. Boldin gained 217 receiving yards, the most in week 1 of an NFL season since Frank Clarke in 1962 and the most by any player in his first game.

It was as amazing was it was unexpected. Boldin was a second-round pick who had an solid college career but one tarnished by an ACL tear that caused him to miss his junior season and struggle at the Combine. He wasn’t even the highest wide receiver drafted by the Cardinals, who selected Bryant Johnson in round 1 despite the fact that he never won a college football game. No one had high expectations for the Arizona offense, with Jeff Blake at quarterback and Dave McGinnis as head coach; the Cardinals would ultimately end up last in the NFL in points scored. As an unheralded rookie on a bad team, Boldin wasn’t one of the top sixty wide receivers drafted in fantasy leagues, and probably wasn’t even among the top 100. That makes his production even more incredible.

The table below lists the best fantasy performances by wide receivers in week 1 of the NFL since 2000, with 1 point per reception, 0.1 points per receiving yards, and 6 points per touchdown. The “Exp” column shows the experience level of the receiver; the last column shows the player’s Average Draft Position among wide receivers, if in the top sixty.
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The San Francisco 49ers were the breakout team of the 2011 season, going from 6-10 in 2010 to 13-3 last year. The Cincinnati Bengals were the surprise team of the AFC, jumping from four to nine wins and earning a playoff berth. The Houston Texans, Detroit Lions, and Denver Broncos all made the playoffs after notching four more wins in 2011 than they had in 2010. But could you have known after just one week that those teams were on track for such breakout seasons? Let’s review.

San Francisco 49ers 33, Seattle 17

This was an odd game, and Jason McIntyre explains why:

San Francisco had just 12 first downs and 209 yards … but still beat the Seahawks by 16 points. The real reason the 49ers won was because Ted Ginn ran a punt and kickoff back for touchdowns in a span of 59 seconds. But offensively, Frank Gore averaged 2.7 ypc and Alex Smith threw for just 124 yards. San Francisco had the ball for 31 minutes and mustered only 12 first downs. As bad as the 49ers looked offensively, the defense did sack T-Jack five times and generate three turnovers. But if the 49ers couldn’t move the ball against a mediocre Seahawks defense … what will they be able to do against the Cowboys, which annihilated the Jets’ offensive line Sunday night? The 49ers have opened as 3-point dogs against Dallas next weekend … I humbly suggest loading up on Romo in that one. No word if San Fran will be without Michael Crabtree.

The 49ers offense wasn’t impressive, but San Francisco’s defense and special teams were dominant. That formula proved to work all season, although few expected it to work against teams better than Seattle. At the time Seattle was considered one of the worst teams in the league (they were a 14-point underdog in Pittsburgh the following week), which made the victory look even less impressive. After week one, Jason Lisk unveiled his Week 1 Power rankings, placing NFL teams into seven tiers. The 49ers were placed in Tier 6 with the comment “When you need two returns by Ted Ginn to put away the Seahawks, you are not good.” ESPN’s power rankings placed San Francisco at #22.

Cincinnati 27, Cleveland 17
This was an ugly game that caught almost nobody’s attention. The big stories of the game were the officiating and the performance of Bruce Gradkowski, who came and led Cincinnati to a win after Andy Dalton was injured. Many in Cleveland blamed the referees, as the Browns were flagged for 11 penalties, compared to just three for Cincinnati. And on the game’s pivotal play — a 41-yard touchdown to A.J. Green — the Browns were still in their defensive huddle at the start of the play, and later argued that the quick snap wasn’t a legal play. The Bengals defense was excellent, shutting down Peyton Hillis and Colt McCoy, but many thought that was simply a product of the schedule. Suffice it to say, no one was boarding the Bengals’ bandwagon after week one. Lisk placed Cincinnati in Tier 5: “Still not sold here, especially if Bruce Gradkowski is QB. Haden shut down Green until the play where he was uncovered at the snap, and Benson’s numbers boosted by a late TD run.” ESPN ranked the Bengals 30th… and the Browns 32nd. The Bengals would lose in Denver and in San Francisco the next two weeks, dropping to 1-2.
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