The Quarterback Marketplace and the Salary Cap

Jimmy Garoppolo, heading into unrestricted free agency after a half-season rental in San Francisco, just signed a $137.5 million deal over five years with the 49ers.

Think about that. A quarterback with seven games’ worth of experience – 183 career completions – is being rewarded at the astonishing rate of three quarters of a million dollars for every past successful throw.

Now it’s not that simple. Even at fair market rate, the Patriots wouldn’t reward Tom Brady with $5 billion for his 6500-plus completions. It’s about future expectations, and Garoppolo is expected to be a franchise quarterback. So $27.5 million per year is the new normal. Which means the next time someone like Russell Wilson or Aaron Rodgers hits a contract year, agents will be talking about $35 million, hoping to settle above $30 million. And they will, soon enough.

The 2018 NFL salary cap will be about $178 million. Let’s take a look at some ratios.

The NFL rookie minimum salary will be $480,000, which is 0.27% of the salary cap. Garoppolo’s average salary is 15.45% of the salary cap. The ratio between those numbers is 57.3.

Now, let’s go back ten years. I’ll use approximations, but the idea is the same.

In 2008, the rookie minimum salary was $295,000 and the salary cap was $116 million. The crazy-high quarterback contract belonged to Carson Palmer, who was expected to make $67 million over the next five years – or $13.4 million per year.

In 2008 the rookie minimum was 0.25% of the salary cap – that’s consistent. But Palmer’s contract was 11.55% of the salary cap and you could obtain 45.4 undrafted rookies for Palmer’s cap compensation.

What’s going on here? This is an increasing effect of the 2011 renegotiated CBA between the NFL and the NFLPA. It addressed a serious problem – that contracts for first-round picks were getting out of hand and causing the value of top picks to decline. But it created a new problem – that contracts for first-round picks who end up being terrific players eat up far less cap room.

This affected the delicate balance between being able to put together a reasonable roster under the cap without discouraging teams from wanting higher picks. It’s this balance that leads to competitive balance in the NFL. Well run teams are rewarded. Owners willing to push the limits of the cap are rewarded. But no one gains from tanking and bad teams get value from picking high in round one.

I’m not claiming the NFL was broken or is broken. It obviously isn’t. But because of savings from the rookie cap, a quarterback with seven games of experience is getting a contract that would have been impossible for any player ten years ago. And we’re seeing a race developing for franchise quarterback salaries. Garoppolo’s 15.45% means someone will get 18% in the next big renegotiation.

Will that cause harm? Probably not. What will happen is that when the CBA is next renegotiated, there will be pressure to increase the cap as there’s always more attention on the highest contracts and bringing more players up to that standard is impossible without increasing the cap. Most people just see the $27.5 million average, not what that means for cap management itself.

And in this case, San Francisco is willing to channel its savings from the rookie cap adjustment into Garoppolo. Since franchise quarterbacks are hard to find these days, it may end up being a good decision. But there will be more holdouts in the near future as agents want their premier players getting a bigger share of those rookie cap savings.

The balance is changing right now, and things will get a little uncomfortable for the next year or so as teams adjust. But for the last three years – after the crazy-high pre-2011 first-round bonuses completely left the league – there’s been a period of time when it hasn’t hurt to stay under the cap. So ultimately, the Garoppolo deal and the current quarterback race is probably a good thing for the NFL.

And in San Francisco, as long as Garoppolo is as good as he’s looked in his first seven games…

Overtime in the NFL: History and Discussion

From time to time, sports fans discuss overtime.

In baseball, extra innings are easily understood and implemented. In a sport filled with tradition (except for the one bizarre exception that MLB’s two conferences play with entirely different lineup structures and rules), wrinkles like starting the 12th inning with a runner on second base don’t get a lot of support.

Basketball has so much scoring that continually adding five-minute tie-breaking overtime periods has never been controversial. Double overtime is rare enough that alterations don’t generate much support.

Hockey has tweaked its rules the most. It’s hard to remember how many players play for how many minutes and how a shootout works from season to season in the NHL. There are even alterations in the overtime rules that make calculating the standings less than intuitive. Thankfully, so many teams reach the playoffs after a marathon 82-game season that casual fans are content to trust the system and wait until playoff hockey in April when everything is sudden death and six-a-side and shootouts are relegated to a distant and vaguely unpleasant memory.

Soccer embraces the playoff shootout concept because games can remain 0-0 seemingly longer than a cricket test match and overtime is largely absent from the regular season. While periodically (every four years, with the World Cup), interest spikes in the US, this might be part of the reason MLS is a distant fifth in the US. While the “Big Four” North American sports leagues are 1st, 2nd, 3rd and 5th in the world in annual revenue, the MLS is 14th – seventh among world soccer leagues. Whatever the reason, we view sports very differently from the rest of the world.

And football is our sport. The NFL is the world’s largest league in terms of revenue – about $13 billion per year. It also supports more franchises – 32 – than any major league in the world. The Super Bowl is the world’s largest single-day sporting event.

But how does football handle overtime? That’s a tough one. College football has an alternating possession rule which somewhat resembles a shootout. The NFL allowed ties in the regular season for a long time, then implemented a single overtime period, then has tweaked that rule a couple of times in the last decade. Playoff games are not limited by time, though there’s so much scoring in the game that this has never been a problem.

Recapping the rules: in 1974, the NFL added a 15-minute sudden death overtime period for regular-season games. Overtime starts with a coin toss and a kickoff. If the game is still tied after 15 minutes, that’s the final result.

People complained the coin toss was too arbitrary and the risk of scoring quickly too great, so in 2010 for playoff games, NFL teams were guaranteed a possession in overtime unless the team receiving the initial kickoff scored a touchdown. In 2012, that exception was extended to the regular season. This year, the overtime period was shortened to 10 minutes for regular-season games.

To make matters even more complicated, in 2011 the NFL moved the kickoff from the 30-yard-line to the 35 and in 2016 touchbacks after kickoffs were moved from the 20-yard-line to the 25. These are both changes that affect overtime.

That’s an awful lot of rule churn for a league that’s number one in the world by a large margin.

Does it matter? I looked in depth at the 324 overtime games in the NFL regular season and playoffs over the last 20 seasons. In terms of studying the game, I like to consider 1978 and the modifications to passing rules the birth of the modern game and 1998, when I started work on Front Office Football and Peyton Manning entered the league, as the beginning of the time period when studying play-by-play can generate results relevant to today’s game (though it’s always best, in my opinion, to focus on the most recent five years of results).

Here are some of my findings:

Since 1998, 6.0% of regular-season games have gone to overtime and 9.1% of playoff games have gone to overtime. The difference doesn’t surprise me since playoff games are limited to the top twelve teams. The average difference in skill level between teams should be lower in the playoffs.

One factor I considered is momentum in games. Announcers and fans like to talk about momentum being significant. Some of that might be more effective strategy changes during the course of games and some of it might be the mental attitude of players or maybe even the results of injuries.

I’ve often wondered if I should add a momentum factor to Front Office Football. In the original design for the college game, I drew an elephant named Mo who was going to appear on the scoreboard to indicate a team had momentum. But ultimately, I felt it was something that would annoy people more than make them feel more invested in the game. To date, I’ve never added a momentum factor or catch-up factor to either game and it’s unlikely I ever will. My design theory is that results should always be ratings driven and there should only be tangible adjustments to ratings. Most importantly, no ratings adjustment aside from injury should ever be, on its own, more than a small percentage. That keeps the game “honest” and understandable, though the “die rolls” associated with any kind of simulation mean individual play results can vary considerably and sometimes give people the impression that something else could be going on. I can only assure you that I test this kind of thing extensively and that everyone has runs of bad luck from time to time. Anyway…

I counted teams that scored last in regulation as having momentum. These teams won 54.8% of overtime games from 1998 until the two-possession rule took effect (essentially with the 2011 playoffs, as no 2010 playoff game went into overtime). With the new rule, 63.3% of the teams with momentum have won.

Out of everything I looked at with this study, this was the most surprising. It suggests that not only is momentum real, but that the rule change – guaranteeing that the team with momentum gets the ball in overtime – has made it more significant. Maybe even made it more fair if fair is defined as treating overtime as an opportunity to extend a game. Is the difference worth noting? I think so. That’s an 8.5% difference with 98 results since the change. Running a test assuming a normal distribution of results, I get a p-value of 0.079 on the comparison. This means I can’t reject the assumption that nothing has changed with a confidence level of 95%, but it’s awfully close. Another two years’ worth of data will help.

What about the role of the first possession? Before the change, the team with the ball first won 58.5% of overtime games. Since the change, that number has dropped to 53.1%. If the goal was reduce the impact of the coin toss, it looks like that has happened, too.

Before the rule change, teams won on that first possession 33.9% of the time. The goal was simply to score points. Nothing wrong with that strategy, but it heightens the impact of the coin toss. Of the 75 first-possession wins, 61 came from field goals and 14 came from touchdowns. The TD percentage was 18.7%. In 2017, for example, that TD percentage (TDs divided by TDs + FGs) was 58.0%.

Since the change, teams win on that first possession 19.4% of the time. They’ve scored 20 touchdowns and 18 field goals (the field goals allow the other team a possession). That percentage is 52.6%. So what we’re getting is a first possession in overtime that feels a lot like a normal in-game possession. Good or bad? I don’t know.

Before the change, a team’s odds of winning if it failed to score on the first possession was 38.1%. That has decreased to 34.4%. If a team scores a field goal on its first possession, it wins 73.3% of the decisions (61.1% if you factor in ties – three of the five ties in the NFL since the change are among the 18 games where both teams started overtime with field goals). Overall, the winning percentage once a team has failed to win (or lose) on its first possession is 42.6%.

Before and after the change, teams had about a 2% chance of losing the game on the first possession due to a fumble or interception return.

Another factor to examine is home-field advantage. Since 1998, the home team wins 57.9% of the time. Before the change, the home team won 52.5% of overtime games. Since the change, the home team has won 59.4% of overtime games. Because that’s a bit closer to the overall mean, it also suggests the new overtime rules are helping with the problems that motivated the changes.

What is the tradeoff? More ties in the regular season, undoubtedly. We’ve seen ties in 5.2% of regular-season overtimes since the change. That’s compared to 1.0% of overtimes before the rule change. Now that overtimes are reduced to 10 minutes, I expect even more ties. That didn’t happen in 2017. But since 11.7% of overtimes since the rule change last four possessions and 12.6% last five or more possessions, I wouldn’t be surprised if a high percentage of those games end in a tie. My guess is the tie percentage will go to about 10% of overtimes in the long term. It’s hard to figure in strategy changes, but that seems like a reasonable estimate. The net result will be an average of about 1.4 ties per season. That’s not going to break the NFL.

Another topic I examined was weather. Is it ever to a team’s advantage to kick off to begin overtime? Between 1998 and the rule change, teams chose to kick off twice after winning the overtime coin toss. In 2000, in a snowstorm with winds gusting to more than 40 mph in Buffalo, the Bills kicked off to New England. The strategy should have worked as the Patriots failed to score and Buffalo drove to the 12 on its first possession. But a 30-yard kick was blocked, then New England drove down the field and kicked the winning 24-yard field goal with just a few seconds left on the clock. Then in 2002, Marty Mornhinweg pretty much sacrificed his job as Detroit’s head coach by choosing to kick off to Chicago in overtime, only to see the Bears kick a field goal on their first possession.

One problem with using weather is that the NFL doesn’t consistently report data for each game. For instance, the stories I’ve read about the Mornhinweg game indicate winds were at 17 mph when he made that fateful decision. My research suggests that wind significantly reduces offense, making it particularly hard to pass. But the NFL reported a wind speed of 4 mph for that game, which shouldn’t trouble anyone. Using the reported wind speeds for games is obviously tricky. How do you determine what it must have been like on the field? Unfortunately temperature, where we have more accurate data, doesn’t have much effect on NFL games. Mostly it’s heavy snow and wind that makes life difficult on the offense.

Since the rule change, four teams have chosen to kick off to start overtime – all in games with high winds reported. The receiving team scored on the first possession in one of those games, and won two of the four. That’s far too low a sample size to make any conclusions, but since Bill Belichick has been the coach to make that choice in two of those four games (winning once), the reaction to this decision in the future will not be anywhere near as strong as it was when Mornhinweg tried it (and the rules made it much more of a losing proposition).

I scored games with a wind speed of 11 or more mph and a couple of other games with heavy snow as having difficult weather. That was 25.1% of all overtime games. About 4% of overtime games were marked as having extreme weather. What I found was that with no weather issues, teams scored on their first possession 36.4% of the time. With difficult weather, that dropped to 29.6% and with extreme weather, 15.4%. However, I found no significant weather difference in the percentage of times teams scored on the ensuing possession.

Overall, since the rules change, teams are 40-32-5 with the first possession in games with no weather marked and 12-14 in games with difficult weather. Of the nine overtime games with extreme weather since the rules change, the team with the ball first is 4-5.

I think in extreme cases, the decision to kick off in bad weather might help, but not much. And in difficult weather, at best the coin-toss advantage is removed. So my advice to coaches is that move should only be considered if you’re Belichick and you’re so far ahead of any living being in terms of understanding the game that this trivial analysis couldn’t possibly help or if conditions are absolutely brutal – which is something you probably have to determine from being out there on the field during that game.

This brings me to my last set of observations. Since I suggest that weather shouldn’t alter this decision unless your smaller players are having trouble remaining upright in the wind, is there any condition to examine? I didn’t want to data-mine the spreadsheet, because the results resemble astrology if you go in that direction. Obviously, if you look at enough samples, you’ll find something that passes a high significance test simply because of the nature of confidence intervals. Perhaps you should always kick off in Sunday night games in the NFC in odd-numbered years. Or always bet on horses with 12-letter names that start in position five. Data mining can bring endless entertainment in any sport.

I looked at one factor that might be a result of bad weather or, more importantly, why it might be worth kicking off in bad weather games. What is the score going into overtime?

Obviously tied. But if it’s 3-3, maybe the field position you potentially gain with a three-and-out on defense is more important than the advantage of going first. The average score going into overtime is 21.8 points per team. Are the odds of scoring on that first possession significantly worse in low-scoring games?

Unfortunately, scores are so tightly clustered at 17-all, 20-all, 23-all and 24-all (combined 55 out of the 103 overtime games since the rules change) that sample sizes are very tiny. All I’ve noted is that teams have scored on their first possession in only three of the 12 games that were tied at 13-all or lower headed into overtime. However, that low ratio didn’t carry over to the 1998-2011 period for low-scoring games. I can’t conclude anything based on the score itself. I’ve also noted that in games that are 30-all or higher since the rules change, teams have scored on their first possession in five of 18 games. Both high-scoring and low-scoring games aren’t favoring the first possession. In between, teams have scored on that first possession in 30 of 73 games.

And while the winning percentage of teams possessing the ball first (3-8-1) in games at 13-all or lower is unusually low since the rules change, that also doesn’t hold true for the 1998-2011 period (24-18-1).

All of this seems like low-sample-size gibberish to me, and perhaps looking at the weather is gibberish as well and you should simply take the ball first no matter what. Hard to say.

Is It Tougher Beating an NFL Opponent Three Times in One Year?

Whenever the situation arises in the NFL, the media likes to repeat the cliche that it’s unusually tough to beat one opponent three times in one season. We hear the usual pseudo-analysis – that if a teams beats an opponent, it will likely stick to that game plan because it was successful while the opponent gets to try new things. And that effect would be magnified in a third contest.

But why would a coach give away a game plan? Why wouldn’t multiple results against the same team have more to do with match-ups than anything else? Is there some rule that a team that wins a game has to stick with the same planning concepts?

It’s relatively rare to see teams play three times in one year. On an average of once or a little more per year, there’s an intra-divisional playoff game. Top teams often split home-and-home games during the regular season. So it turns out that only 19 teams have ever had the opportunity to take that third victory over one opponent.

It looks somewhat likely a 20th team will get that opportunity this year, since New Orleans has beaten Carolina twice and the schedule seems to favor a third game as the NFC 4/5 wild card match-up this season. Since the three-win opportunity hasn’t occurred since 2009, it will get more attention than usual.

Naturally, pundits will spend the week explaining that Sean Payton can’t possibly come up with a third way to beat the Panthers.

So, what’s the reality of the situation? Well, the home team has won 12 of those 19 games, and the team with the two prior victories has won 13 times. Myth busted.

I’ll also take the opportunity to point out that the last team to win that third game after losing the two regular season games was the New York Giants going out on the road as the fourth seed at 13-3 Dallas in the 2007 playoffs. Those Giants ending up beating the only 16-0 regular-season team in NFL history in the Super Bowl.

Dirty Play in the AFC North?

Yesterday’s episode of Monday Night Football had more than its share of unpleasant moments. Starting with an accidental, but particularly scary back injury to Ryan Shazier. That transcends the game and I’m sure every player in the NFL, even those who really don’t like the Steelers, shares genuine concern here and hopes for a full recovery.

Unfortunately, the game quickly devolved, mostly between Pittsburgh’s offense and Cincinnati’s defense. The Bengals’ George Iloka looked like he was going after Antonio Brown whenever possible, and finally was flagged after a touchdown. He was suspended for a game (strangely, his suspension was the only one retracted this week, since his behavior seemed the most calculated). The Steelers’ JuJu Smith-Schuster head-hunted Vontaze Burfict during a play, then stood over him and received a taunting penalty. He was also suspended for a game.

These incidents, combined with the Patriots’ Rob Gronkowski’s disturbing behavior on Sunday, have the NFL once again at the top of the sports news cycle for all the wrong reasons.

Ben Roethlisberger, the Steeler quarterback with two Super Bowl rings to his name and a Hall of Fame resume, was asked about the dirty play after the game. His response? “AFC North.”

That got me thinking… are some teams more prone to dirty play or is it just perception? Is the AFC North some sort of special haven for teams that can’t help but goon it up against each other? How would you study this?

Given that dirty play stemming from high emotion is fairly easy to spot, my assumption is that penalty yardage would correlate to these games. So I constructed a spreadsheet with some penalty numbers from 2013-2017. This covers 1,260 games, including playoffs. I also separated out all the games involving two AFC North teams – a sample of 58 games.

Among these AFC North games, the 239 penalty yards yesterday was the most in a single game. The 173 from Cincinnati was second only to Cleveland’s 188 against Pittsburgh in their first matchup of 2015. Third place – and the only other +200-yard combined penalty performance was the infamous 2015 playoff game between Pittsburgh and Cincinnati.

I think NFL fans remember that game. Cincinnati looked like it had completed a fantastic fourth-quarter comeback. With Pittsburgh ahead, 15-0, Roethlisberger was sacked and injured on the last play of the third quarter. The Bengals scored two touchdowns and a field goal to take the lead with 1:50 remaining. Landry Jones promptly threw an interception and it looked like two decades of playoff futility had finally ended for Cincinnati. To that point, Pittsburgh had been penalized 142 yards to Cincinnati’s 49.

But the Steelers still had time outs, so the Bengals needed one more first down to secure the victory. Jeremy Hill fumbled on the next play. Still, Pittsburgh was back at its own 9. Roethlisberger returned. He moved the ball downfield quickly, but time was running out. He threw a long pass for Brown, maybe their last chance, and it fell incomplete. But Burfict was penalized for a nasty hit on Brown and Adam Jones drew an unsportsmanlike conduct penalty, and all of a sudden Pittsburgh was in position for the winning field goal in the closing seconds.

The way that game ended – with Cincinnati losing simply because their defensive players couldn’t control their emotions – cemented the Bengals’ reputation as an undisciplined team and lends a lot of credence to the claims Roethlisberger made yesterday.

Is all of this true? Here are some numbers:

Over the last five years, NFL teams average 56.2 penalty yards per team per game. Cincinnati has averaged 56.0 penalty yards per game. So, no, the Bengals are not a particularly high-penalty team. Teams range from Carolina (49.0 yards) to Seattle (66.3 yards). Baltimore, at 60.8 yards, is the only AFC North team in the top quartile.

Are AFC North games particularly penalty-prone? AFC North teams, overall, average 57.4 yards in penalties per game. However, divisional games average 58.3 yards in penalties. That’s not a huge difference, but Cincinnati’s 70.6-yard average against Pittsburgh (not including yesterday, it’s 57.0 yards) is the highest team versus team average.

The numbers really aren’t all that notable except for one total: in the 30 games against Pittsburgh, opponents are averaging 66.4 yards of penalties while in the 52 games against Pittsburgh played by the rest of the league, they’ve averaged 55.4 yards.

Now, one thing I haven’t done is split all divisions in this manner (I don’t want to turn this into a major project), but Roethlisberger’s perceptions seem valid (53.7 out-of-division committed by Pittsburgh, 58.2 in-division), though that experience does not hold true for the rest of the division. So, over the course of the last five years, Pittsburgh’s AFC North games have averaged about one major penalty per game more than you’d expect based on team averages. That seems significant and worth some extra attention from the NFL.

The End of an Eli?

You have to feel for Eli Manning. If he weren’t the brother of a quarterback whose face would be on a Mount Rushmore of quarterbacks, should such a concept exist, he’d be better loved. He has 118 career wins, including playoffs, and a pair of Super Bowl MVP trophies.

No modern quarterback with that many wins isn’t in the Hall of Fame or a lock to get there (like his brother). No player with multiple Super Bowl MVP Awards isn’t in or a lock to get there (like Tom Brady).

Yet somehow, it doesn’t add up. Recently, he passed the elite 30-mile club in career passing yardage. In the modern era, that club includes Brady, Drew Brees, John Elway, Brett Favre, Peyton Manning, Dan Marino and Ben Roethlisberger (also there this year). That’s it. More than 40 years of the modern passing rules, and he’s one of seven to throw for more than 52,800 yards (Philip Rivers might well make it eight late this season or in the playoffs, should the Chargers qualify).

We’re in the age when the definition of great quarterbacking is changing, and perhaps expectations are too high. Or perhaps there was a run of a few years when random luck produced a group of top quarterbacks. Hard to say. A few months ago, I tried to come up with a Bill James-style formula for calculating quarterbacks reaching the Hall, and Eli is borderline. Only Ken Anderson has more points in this formula of those who aren’t in or still playing (or like Peyton, not yet eligible), but the list of current players is impressive.

I think I’ve made my feelings about Ken Anderson’s qualifications well known (darn it, Canton, it’s time to fix this). But ultimately, I think Eli won’t make it because his brother will, and Brady and Brees and Roethlisberger and Aaron Rodgers are dead locks to make it. We’ll have quarterback fatigue.

We also have to consider quality of play. My quarterback metric is designed to analyze this across generations, and the fact is that Eli is an average-minus quarterback statistically. His career average in the metric is 49.8, a number that would and should have coaches wondering if they should draft a replacement. Only two of the Hall quarterbacks are below 56 career – Warren Moon (53.8) and Elway (52.7). And Elway is one of a handful to reach 150 wins while Moon had to prove himself in the CFL for years when he should have been in the NFL. None of the other current quarterbacks I’ve mentioned here are below 58 average for their careers (Peyton is at 61.2).

Today, New York Giants coach Ben McAdoo announced that Eli won’t be starting at quarterback the rest of this season. He offered him the opportunity to play a series or two, then come out, because Eli’s streak of 210 straight starts is second all-time among quarterbacks to Favre (though still a few years short). Manning wisely declined, understanding this kind of record is only valid when you’re playing in the fourth quarter.

Is it time for the Giants, 2-9 and mathematically eliminated from playoff contention, to consider alternatives to their 36-year-old leader? Manning’s average score in the metric is down to 44 this year, 27th among NFL starters. There’s reason to wonder if it’s time to retire. The Giants invested a third-round pick this year in Davis Webb, who is rather raw coming off his graduate-transfer year at California, but is huge and has a gifted arm. But Webb won’t start, either. That goes to Geno Smith, who has an 11-19 career record with the Jets and a 42 average in the metric. Smith is in his fifth year, and will be a free agent next spring. I’m not sure he’s worth the look if a look has to be taken. I’m not sure that’s a great decision, given that the Giants will draft high next year and really need to know all they can about Webb whereas the odds are low Smith is worth starting next year.

But decisions have a way of becoming necessary at inconvenient times, and the worry is that Webb isn’t ready or he would get the longest look. Since this is likely the end of Manning with the Giants, fans can appreciate what his long career has brought to New York, even if it’s just a little bit short of Hall quality and he has struggled along with the rest of the team this year.

This Date in History

As the Cleveland Browns stumble toward what could be the second 0-16 season in NFL history, I’m reminded of this date, Halloween, in 1999.

Halloween was unkind to the Browns this year. It’s clear that DeShone Kizer is not ready to lead an NFL team. He’s very young, and many scouts say he has talent. But starting a 21-year-old second-round draft pick at quarterback is not the NFL norm, and Kizer is really struggling.

The trading deadline was at 4:00 today, and the Browns traded for Cincinnati backup A.J. McCarron with minutes to spare. The Bengals called it in to the league office. However, for some reason, the Browns did not beat the deadline. That’s just one of those stories you can’t make up.

Anyway, McCarron, like Jimmy Garoppolo (who the Browns apparently wanted to trade for in the off-season), is in his fourth year and stuck behind an established franchise quarterback. This means he would go into next season restricted as a free agent. So the Bengals would have liked to get something for him. I’m not sure why they’d be willing to trade him in-division, but perhaps that’s another slight against the Browns.

Colin Kaepernick fans should take note of this, as an aside. If there’s one situation in the NFL where Kaepernick fits, it’s this one. As long as he’s willing to play mentor to Kizer and accept fringe starter money (this runs about $6 million for a full season these days), this would be a great road back to the NFL. I can’t say what’s in the heads of NFL GMs and owners, but this seems like a good idea while some of the other openings (backup in Tennessee, more recently) have not seemed like good fits.

But let’s flash back to 1999, the first year of the expansion Cleveland Browns (the “old” Browns became the Baltimore Ravens in 1996). In return for not causing trouble, the city of Cleveland was promised an expansion team no later than 1999, plus the expansion team would “own” the Browns’ history and team colors.

For some reason, and this was apparently unrelated to the move, the Browns also fired their head coach at the time. He found a new gig relatively quickly and has since won five Super Bowls with his new team, but that’s another story so I won’t mention his name here.

The Browns began play again in 1999 and were fairly bad. They headed into their Halloween matchup at New Orleans with an 0-7 record. As NFL games go, it was exciting. The Saints took a two-point lead with 21 seconds remaining in the fourth quarter. But quarterback Tim Couch, the first pick in the 1999 draft, was up to the challenge.

Couch completed a 19-yarder to the Browns’ 46-yard line. Time out with 0:02 on the clock. Couch then rolled right and threw the ball as far as he could. Kevin Johnson fought through a crowd in the end zone to give the new Browns their first victory.

Incidentally, as of the last time I messed with these numbers, Couch has by far the highest rate of late fourth-quarter game-winning drives in modern NFL history. No, don’t reserve a bust in Canton – his career quarterback record was 21-36. But 11 of those 21 wins came on plays just like that one (well, not quite just like that one).

Now there’s some connection between this New Orleans team and Front Office Football. For years, it was a running joke that there were too many Billy Joes in the game. When I designed the original game (and perhaps this is still an issue, because the design in this case is still quite similar, but I may have removed the name), any first name that was shared by more than one NFL player was placed on the list of more frequently used first names (IIRC, there were about 500 names on that list).

The Saints had two primary quarterbacks – Billy Joe Hobert (4-8 career record) and Billy Joe Tolliver (15-37 career record). It’s a name that stands out, I guess. In 1999, they shared quarterbacking duties. Both had 1-6 records as a starter that year. Hobert started this Halloween game. He was either hurt or pulled after throwing a second-quarter interception (he is listed as making the tackle, so I’m guessing hurt). Tolliver relieved.

Cleveland ended up winning a second game that season. And that was the Browns’ worst record (new or old) until last year. But they have finished last in the AFC Central/North in 14 of their 18 seasons since expansion and look certain to make that 15-for-19. They have a 0-1 playoff record since expansion and their last playoff victory was on New Year’s Day in 1995 against New England, who was apparently impressed by their head coach because… well… still not mentioning his name.

Finally, back to winless seasons. The Browns won in week 16 last year, beating the Chargers as their kicker missed a game-tying 45-yarder as time expired. Now in Los Angeles, the Chargers have played a bit better (3-4 so far, as opposed to 5-11 last year). They lost their first two games this year essentially on missed game-ending 44-yard field-goal attempts.

This meant YoungHoe Koo, their new kicker this year, lost his job. Koo, by the way, is only the fourth player born in Korea to play in the NFL (and the second with a father not an American stationed with the military). Since one of those four players is Hines Ward, South Korea has by far the highest percentage of native-born Super Bowl MVPs in NFL history. In case you’re interested, the Browns visit the Chargers in week 13.

Shut Out in Week Seven

It probably hasn’t escaped most NFL fans that something unusual is happening in week seven. Three different teams have been shut out.

The Cardinals were beaten, 33-0, by the Rams. In addition to treating London fans to a performance that could, on its own, cause serious harm to the NFL’s popularity overseas, Arizona lost quarterback Carson Palmer to an injury that may end his season.

The Colts fell to the Jaguars, 27-0. Jacksonville’s defense is one of the positive stories of this season – a unit that could drive a playoff run for a team that probably wouldn’t make the playoffs at all based on offense alone. The Jaguar defense has taken all the pressure off of a difficult quarterback situation.

The Broncos, suddenly looking quite bad, lost 21-0 to the Chargers, playing in front of a crowd that seemed made up mostly of family and friends of the players (I exaggerate).

Not only have three teams failed to score this week, but they lost to three teams that had a combined total of 12 wins in 2016.

Is this unusual? The three shutouts brings the 2017 total to five. That’s two more than we had in all of 2016. Since 1978, there have been 345 shutouts (8.6 per year). The most in a season was 17 in 1992. The least was two in 1994. We’re in a down-cycle lately, probably because scoring is up. Just 37 in the last eight years.

Do they come in bunches? Shutouts don’t happen all that often, so one could perceive a bunch just because they’re notable. The last time there were three in a week was week 15 of 2012. There were only two other shutouts the entire year. Three has happened a few times. The last time there were four shutouts in a week was week 12 in 1983. And the only other time there were more than three in the modern era (I go back to 1974 when the passing rules were changed) was the opening week of 1977 with five.

So I don’t think this is a sudden and notable occurrence. Odds are good we won’t have more than a handful of shutouts the rest of the season.

What about scoring in general? Is it down this season? So far this year, NFL teams have averaged 21.9 points per team per game. That’s the lowest since 2009 and down from last year’s near-record of 22.9 (a half point lower than 2013’s record total of 23.4). But 21.9 matches the most from 1968-2007, so it’s not an unusually low total. And prior to this week, teams were averaging 22.2 points, which is certainly in line with recent seasons.

My sense is that scoring is a bit down this year. If I had to put my finger on it, based on a cursory look at statistics, I’d say improved pass rushing is making teams decide to throw a tiny bit less – perhaps that’s also because we have some more inexperienced quarterbacks this season or the league is allowing a little more contact from defensive backs. It’s very hard to tell without a full season of data.

Week 5 NFL Quarterback Ratings

In Week 5 news, Mitchell Trubisky made his long-awaited debut, and while he certainly looks the part, it was not great. Take away the first drive and it was downright scary-bad. But not all rookies are Matt Ryan or apparently Deshaun Watson. Cam Newton had a great game, leading the Panthers to what may be a season-defining road win at Detroit. Carson Wentz continued his breakout season and Jared Goff returned to Earth a little.

Newton, CAR, 90 (60)
Smith, KC, 87 (81)
Wentz, PHI 78 (55)
Hogan, CLE, 73 (65)
Flacco, BAL, 73 (45)
Rodgers, GB, 68 (60)
Keenum, MIN, 65 (59)
Brady, NE, 64 (69)
McCown, NYJ, 62 (56)
Brissett, IND, 62 (48)
Watson, HOU, 58 (50)
Prescott, DAL, 57 (54)
Hoyer, SF, 55 (41)
Dalton, CIN, 53 (55)
Palmer, ARI, 53 (44)
Stafford, DET, 52 (52)
Cassel, TEN, 45 (31)
Winston, TB, 43 (52)
Wilson, SEA, 42 (48)
Manuel, OAK, 41 (40)
Bortles, JAX, 39 (40)
Bradford, MIN, 38 (66)
Manning, NYG, 35 (51)
Rivers, LAC, 31 (48)
Roethlisberger, PIT, 27 (46)
Taylor, BUF, 25 (55)
Goff, LAR, 24 (60)
Cutler, MIA, 22 (41)
Trubisky, CHI, 21 (21)
Kizer, CLE, 18 (24)

The Monday Night game illustrates some of the issue I have in tracking quarterback wins and losses. As far as the league is concerned and the media is concerned, you start a game, it’s your game. Most people would never know that in Super Bowl 26, Jim Kelly was injured and only was 4-7 passing before he left the game. Frank Reich took over in the second quarter and was 18-31. The Bills lost, 52-17.

So, is that Reich’s loss or Kelly’s? It’s Kelly’s by most standards in that he started. In baseball, pitcher wins and losses are determined by who was responsible for the baserunner who scored the run that gave the other team the lead for the last time. Under that standard, Kelly is still the loser – the Bills were down, 14-7, when he left, and never held the lead again. But Reich threw many more passes (both had two interceptions), was quarterback for a longer time. And sometimes in baseball, you see a closer who had a dreadful 1/3-inning blown save end up with a win. Scorekeepers have some discretion in assigning wins, but only when a starter fails to go five innings. I’m not sure this scorer’s ruling is done anymore or even allowed.

As an aside, the Bills had nine turnovers in that Super Bowl, which isn’t that close to the NFL record of 12.

I try to be consistent in how I assign wins and losses myself. I gave Reich the loss because he threw the ball much more, though I think it could go either way and Kelly certainly put the Bills in a deep hole with three turnovers of his own in his brief stint.

So, what about last night’s game? Sam Bradford started for Minnesota and was clearly struggling with his knee. He wasn’t mobile, it just wasn’t working for him. After a turnover near the end of the half, Bradford led the Vikings five yards in three plays and they kicked a field goal to take a 3-2 lead.

Case Keenum relieved Bradford for the last half-minute of the second quarter and the entire second half. The Vikings won, 20-17. Bradford threw for 36 yards and had a game score of 38. Keenum threw for 140 yards (17-of-21) and had a game score of 65. Now Chicago did tie the score late and Keenum led the winning drive right in the final minute. So under baseball’s rules, Keenum would get the win. I had no problem giving him the win.

But would I have done the same if Chicago had failed on its two-point try in the fourth quarter and the Vikings won, 20-15, without ever having lost the lead they gained with Bradford? I think so. It gets complicated. What do you do with a quarterback who enters the game in the fourth quarter, throws an interception, the other team ties the game and sends it to overtime, where that quarterback who gave up the lead (blew the save) leads the team to victory (perhaps without even throwing a pass)?

Since wins are not an official quarterback statistic, the NFL doesn’t worry about this. I don’t really worry, either, but my primary tool in calibrating my quarterback metric is correlating quarterback statistics with wins and losses. So assigning wins and losses more accurately, whatever that means, leads to a more accurate game score.

Week 4 NFL Quarterback Ratings

Quarterback game scores for week 4 in the NFL. Season averages in parentheses. This data has yet to be adjusted to 2017 totals, but shouldn’t vary that much in the end.

Andy Dalton 86 (55)
Cam Newton 85 (53)
Russell Wilson 76 (49)
Deshaun Watson 74 (48)
Alex Smith 73 (80)
Tyrod Taylor 70 (62)
Aaron Rodgers 68 (58)
Tom Brady 65 (71)
Kirk Cousins 64 (61)
Derek Carr 63 (61)
Kevin Hogan 63 (61)
Drew Brees 61 (67)
Jameis Winston 61 (55)
Philip Rivers 60 (53)
Marcus Mariota 55 (52)
Trevor Siemian 55 (50)
Jared Goff 50 (69)
Carson Palmer 49 (42)
Carson Wentz 49 (50)
Josh McCown 49 (55)
Ben Roethlisberger 47 (51)
Case Keenum 46 (56)
Eli Manning 46 (56)
Matthew Stafford 46 (52)
Dak Prescott 45 (53)
Jay Cutler 43 (47)
E.J. Manuel 38 (38)
Mike Glennon 34 (41)
Joe Flacco 30 (38)
Matt Ryan 25 (60)
Brian Hoyer 24 (38)
Jacoby Brissett 24 (44)
Blake Bortles 17 (41)
Matt Cassel 17 (17)
DeShone Kizer 16 (26)

Week 1 Average: 52
Week 2 Average: 52
Week 3 Average: 58
Week 4 Average: 51

Mike Glennon’s weak week four performance, complete with four turnovers, has led to his benching while #2 pick Mitchell Trubisky takes the Bears’ reins. Glennon only has a 5-17 quarterback record over his career. His average game score of 55 is good for a player with his limited experience, but he was signed to keep the Bears competitive while Trubisky developed. The Bears are looking at long odds to reach the playoffs, there’s a bye week coming and Glennon hasn’t been the game manager he was signed to provide. The only reason not to start Trubisky is if there’s worry he will struggle like fellow rookie DeShone Kizer, and playing him too early might cause long-term damage. Hopefully for Chicago fans, this isn’t the case, as head coach John Fox is unlikely to keep his job if the Bears don’t make significant progress the rest of the season and these decisions shouldn’t be made out of desperation.

Top quartile Pass Defenses, by Game Score against:
1. Buffalo 37
2. Jacksonville 38
2. Pittsburgh 38
4. Kansas City 40
5. Baltimore 41
5. Seattle 41
7. Cincinnati 45
8. New York Jets 46
8. Detroit 46

Bottom quartile Pass Defenses, by Game Score against:
31. Miami 73
31. New England 73
30. Cleveland 71
29. New Orleans 66
28. Oakland 64
27. Tampa Bay 62
25. Carolina 61
25. Los Angeles Chargers 61
23. Indianapolis 59
23. Philadelphia 59

It’s much too early for conclusions based on this small a sample size, but asking if certain performances are “for real” can be addressed in a superficial manner, understanding that each of these performances make up one quarter of the opponent’s data this season.

– Notably off of career averages –
Alex Smith, 80 average, 3 bottom quartiles, 1 middle.
Tom Brady, 71 average, 1 bottom, 2 middle, 1 top.
Jared Goff, 69 average, 1 bottom, 3 middle.
Russell Wilson, 49 average, 1 bottom, 3 middle.
Carson Palmer, 42 average, 1 bottom, 2 middle, 1 top.
Mike Glennon, 41 average, 1 bottom, 2 middle, 1 top.
Joe Flacco, 38 average, 1 bottom, 3 top.

– The Rookies –
Deshaun Watson, 48 average, 1 bottom, 1 middle, 2 top.
DeShone Kizer, 26 average, 1 bottom, 3 top.

Week 3 NFL Quarterback Ratings

Quarterback game scores from Week 3 in the NFL, with season averages in parentheses. An average game score for a starting quarterback is 52. Scores are based on the weights I used for the 2016 season. Those will change, but very little from year-to-year.

Kirk Cousins 96 (59)
Case Keenum 94 (62)
Jared Goff 91 (76)
Dak Prescott 85 (56)
Tom Brady 83 (73)
Jacoby Brissett 82 (54)
Drew Brees 78 (68)
Josh McCown 78 (57)
Tyrod Taylor 78 (60)
Andy Dalton 77 (45)
Alex Smith 72 (82)
Blake Bortles 69 (49)
Eli Manning 65 (59)
Brian Hoyer 62 (43)
Aaron Rodgers 60 (55)
Matt Ryan 59 (71)
Marcus Mariota 58 (50)
Ryan Mallett 56 (56)
Deshaun Watson 55 (39)
Carson Wentz 54 (50)
Russell Wilson 54 (40)
Jameis Winston 52 (52)
Carson Palmer 51 (40)
Matthew Stafford 39 (54)
Ben Roethlisberger 38 (52)
Mike Glennon 37 (43)
Trevor Siemian 34 (49)
Cam Newton 32 (42)
Jay Cutler 32 (50)
Derek Carr 29 (61)
Joe Flacco 19 (41)
Philip Rivers 18 (50)
DeShone Kizer 16 (29)