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)

Week 2 NFL Quarterback Ratings

Updating with the game scores from Week 2 in the NFL. For each quarterback, their average game score for this season is in parentheses.

As an aside, I’ve actually received a handful of questions about why I stopped doing the college ratings. The simple answer is just that I’m busy and it’s a lot of work to set them up for a new season. It means compiling the season-opening ratings and then entering the schedules for 130 FBS schools. I ran them for 20 years. I don’t think I’ve received a single comment about them in a decade.

For a while I had hoped (because I’ve been part of Kenneth Massey’s comparison since the beginning and mine are decently accurate) I might become part of the media that takes part in the national computer rankings. But, somewhat like Lana Turner and the Top Hat Malt Shop and the legions of wannabe actresses who put away endless sodas hoping to follow her footsteps, no one discovered them. So I’m seeing what it feels like not to spend every early Sunday morning during the fall entering lots of data.

The NFL ratings are a lot less work and they tie more into the continual research I’m doing on pro football, so I’m continuing with them for now.

As another aside, I’ve noticed someone out there has made a rather determined effort to hack into this blog through a Ukrainian proxy. Just in case Robert Muller is one of my readers, no, I had nothing to do with the 2016 election. And I hope I’m practicing safe blogging by keeping WordPress updated and greatly limiting login attempts. Not sure why someone would want access to this blog – but if you ever see anything completely weird on my web site, like pictures of unclothed Ukranians, it wasn’t me.

Anyway…

Quarterback, Week 2 (Season Average)
Tom Brady 95 (68)
Derek Carr 81 (77)
Philip Rivers 81 (66)
Alex Smith 80 (88)
Matt Ryan 74 (78)
Jay Cutler 67 (67)
Ben Roethlisberger 61 (59)
Joe Flacco 60 (52)
Josh McCown 58 (47)
Kevin Hogan 58 (58)
Trevor Siemian 58 (56)
Matthew Stafford 56 (61)
Drew Brees 55 (64)
Cam Newton 54 (47)
Eli Manning 54 (56)
Jameis Winston 52 (52)
Jared Goff 52 (68)
Kirk Cousins 52 (41)
Aaron Rodgers 49 (53)
Tyrod Taylor 49 (51)
Marcus Mariota 48 (47)
Mike Glennon 46 (46)
Carson Palmer 45 (35)
Andy Dalton 43 (29)
Deshaun Watson 43 (32)
Carson Wentz 38 (48)
Russell Wilson 35 (34)
Blake Bortles 31 (39)
Dak Prescott 31 (42)
Case Keenum 29 (29)
Brian Hoyer 25 (33)
Jacoby Brissett 25 (25)
DeShone Kizer 15 (35)

Week 1 NFL Quarterback Ratings

I don’t know how often I’ll do this, but I thought I’d put out my quarterback scores for week 1 of the NFL season. The average game score is about 52 for a starter. These scores are based on 2016 normalizations. I’ll redo the normalizations and factor in a couple of other minor things at the end of the year, but these scores won’t change much. In parentheses is a quarterback’s average game score from 2016, if he had six or more qualified games.

Alex Smith, KC 95 (55)
Sam Bradford, MIN 94 (62)
Jared Goff, LAR 84 (30)
Matt Ryan, ATL 81 (74)
Derek Carr, OAK 72 (55)
Drew Brees, NO 72 (63)
Matthew Stafford, DET 66 (56)
Carson Wentz, PHI 58 (44)
Ben Roethlisberger, PIT 57 (55)
Eli Manning, NYG 57 (48)
Aaron Rodgers, GB 56 (60)
DeShone Kizer, CLE 55
Trevord Siemian, DEN 54 (48)
Tyrod Taylor, BUF 52 (52)
Dak Prescott, DAL 52 (64)
Philip Rivers, LAC 51 (51)
Blake Bortles, JAC 46 (41)
Mike Glennon, CHI 45
Marcus Mariota, TEN 45 (54)
Joe Flacco, BAL 43 (48)
Brian Hoyer, SF 41 (59)
Tom Brady, NE 40 (66)
Cam Newton, CAR 39 (42)
Josh McCown, NYJ 35 (34)
Tom Savage, HOU 33
Russell Wilson, SEA 32 (58)
Kirk Cousins, WAS 30 (60)
Scott Tolzien, IND 30
Carson Palmer, ARI 24 (48)
Deshaun Watson, HOU 20
Andy Dalton, CIN 14 (57)

Two-Point Conversions

From time to time, I like to take the opportunity to challenge my own perceptions about football. One strategy that’s often debated is whether teams should attempt a two-point conversion after a touchdown.

Decades ago, legendary coach Dick Vermeil, then a coordinator at UCLA, created a chart that’s still in popular use today. It’s not a chart I used when developing Front Office Football, but it’s not that different. Some of it is obvious; for instance if you trail by two after scoring a touchdown, you should try and tie the game. But even then, when in the game should you start consulting the chart?

Some of it is complex, or even controversial. You’re supposed to go for two when you lead by four after scoring. The idea is that if you make it, a subsequent field goal will give you a two-score lead. But if you miss, a subsequent field goal will leave your opponent the opportunity to tie on a touchdown without going for two.

Since the two-point conversion rate in the NFL is about 45% and the extra-point rate with the new distance rule is about 97%, I’d hesitate to start using any chart until well after halftime. Just take the point.

A few months ago, when working on a percentage win calculator that I’ve yet to put into any product, I analyzed a few seasons’ worth of play-by-play data and compiled a chart that could be useful for making these decisions. As an aside, I do this kind of thing a lot. Most of what I discover on these odysseys never amounts to meaningful work within my products. This might well fall into that category. But it could also be useful in compiling a more fine-tuned chart – one that even incorporates time remaining.

Today, I watched a good part of the Lions’ opener against Arizona. With 3:07 left in the third quarter, the Lions scored to cut the Cardinal lead to two. Some might say it was too early to start using a chart, but no one would question the wisdom of the decision in the closing moments. The Lions tried the conversion and failed. How did that change their win chances?

I have my play-by-play data broken into 100-second increments. To take a broader brush to include as much as is reasonable, I used the categories from the end of the third quarter to 6:40 remaining in the third quarter. There have been 2,797 plays undertaken with the score tied and a team with the ball, 1,031 plays with a one-point lead and 397 with a two-point lead. Not an overwhelming amount of data, especially since you can’t assume a reasonably uniform distribution of field position within that small a data set with the two-point lead. But in 1,629 of the tied scenarios (58%), the team with the ball won (possession matters – Arizona would have possession after the ensuing kick). In 574 of the one-point lead scenarios (56%), the team with the ball won and in 280 of the cases with a two-point lead (71%), the team with the ball won.

This is a great example of where sample size lets you down. The reason I’m writing about this is to give you some insight into my process when examining a particular question. When do you make a conclusion and when do you accept that you just don’t have enough information? This is several seasons’ worth of complete play-by-play data (350,000+ plays broken down by lead and time to go blocks), and the raw data set still isn’t good enough to make solid conclusions.

What the above numbers suggest is that the value of the extra point is immaterial, but there’s a 10-15% game-win cost in going for two and failing. That just doesn’t feel like a reasonable conclusion. When I was doing the initial work with this particular data set, I ran a whole series of rolling averages to come up with a win-percentage chart that supported the data with less precision, but a consistent set of percentages that required the least amount of intervention on my part (making “decisions” about interpretation and then using those decisions to influence how the rolling averages were applied). I feel more confident in presenting that chart as reasonable, at least in the sense that it could be used to help with this kind of decision. If this work results in use in any product, I would use that more processed chart.

Going back to the analysis of the first Lions decision: I come up with a 55.8% Arizona win percentage when tied during that time block, 61.1% with a one-point lead, 64.3% with a two-point lead. So, -3.2% for Detroit with a failure, +5.3% with success. Assuming 45% success on two-point tries and 97% success on extra points, the decision to go for it, in itself, raises Detroit’s win percentage by about a half a percentage point. I think it’s reasonable to conclude that it was a good decision. In general, my data supports this case up to about midway through the third quarter. Earlier than that, I would advise against ever going for a two point conversion except when desperate and in need of multiple positive results (let’s say you score and trail by 18).

The second Lions decision came with 9:27 remaining in the game. This time, they led by four. Vermeil’s chart says “go for it.” I don’t know if Jim Caldwell uses this particular chart, but he went for it. The Lions failed. The value of success and penalty for failure is explained at the start of this article. Now to break down it down using the data…

If the Cardinals gain possession with a six-point deficit (Detroit makes the conversion), they have a 29.2% chance of winning. With a five-point deficit, that’s 36.0% and a four-point deficit, that’s 41.0% percent. Factoring in analysis of success and failure, that amounts to, again, about a half-percentage-point increase in the Lions’ win chances. This surprised me a little, but, as it turns out, a six-point lead is quite a bit better than a five-point lead, even relatively early in the game.

Vermeil’s chart may be old, but it holds up even in the modern game.

NFL Quarterbacks for 2017

Now that the preseason is over and around 1,000 players were released this weekend, we have a good picture of the quarterback situation for 2017. I’ve put together a chart that I use as a quick reference.

Teams usually activate two quarterbacks for a game. Many keep a third quarterback on the 53-man roster and leave him inactive most weeks. This is a good place for a draft pick that isn’t expected to contribute his rookie year. Teams that don’t have three quarterbacks on the 53-man roster often have a quarterback on their practice squad. This is often a young player, but since any team can sign someone else’s practice-squad player by offering a roster spot, it’s not a place to stash a draft pick with a high upside.

There are some exceptions. A handful of teams won’t have a third quarterback, figuring on holding tryouts the next Monday in case of an injury. After all, 37 quarterbacks were released this week. Even though that group has a combined record of 26-78, there’s some talent in there, presumably in playing shape. And there are a few injured quarterbacks who need to be protected because they could be activated later in the season.

Practice squads will be formed this week. These will include at least a few of the quarterbacks released this week. A team will sometimes sign a quarterback to its practice squad that it just released.

A quarterback’s age and NFL record is in parenthesis. For rookies, their draft position is included rather than a record. For a quarterback’s record, I calculate wins and losses much like baseball does. Playoffs are included, though. Age is as of opening day next week.

*A – Indicates player is on Injured Reserve and won’t play this season. *B – Indicates player is on 53-man roster, but is likely to be placed on Injured Reserve with the possibility of returning later in the season. *C – Indicates player is on 53-man roster, is injured, but is likely to be healthy early enough to be worth keeping off of the PUP list. *D – Indicates player is on the non-football injury list and could be reinstated later in the season. *E – Indicates player is on the PUP list and will be eligible to return to the active roster after six weeks.











































AFC East
BuffaloMiamiNew EnglandNew York Jets
Tyrod Taylor (28, 15-15)Jay Cutler (34, 70-70)Tom Brady (40, 207-60)Josh McCown (38, 17-41)
Nathan Peterman (23, 171st)Matt Moore (33, 16-15)Jimmy Garoppolo (25, 2-0)Bryce Petty (26, 1-3)
T.J. Yates (30, 5-3)Ryan Tannehill *A (29, 36-40)
Christian Hackenberg (22, 0-0)
AFC North
BaltimoreCincinnatiClevelandPittsburgh
Joe Flacco (32, 93-59)Andy Dalton (29, 54-39)DeShone Kizer (21, 52nd)Ben Roethlisberger (35, 135-65)
Ryan Mallett (29, 3-5)A.J. McCarron (26, 2-2)Cody Kessler (24, 0-7)Landry Jones (28, 3-2)

Jeff Driskel *B (24, 0-0)Kevin Hogan (24, 0-1)Joshua Dobbs (22, 135th)
AFC South
HoustonIndianapolisJacksonvilleTennessee
Tom Savage (27, 2-2)Andrew Luck *C (27, 46-30)Blake Bortles (25, 11-34)Marcus Mariota (23, 11-16)
Deshaun Watson (21, 12th)Scott Tolzien (30, 0-3)Chad Henne (32, 19-37)Matt Cassel (35, 37-46)

Jacoby Brissett (24, 1-1)
Alex Tanney *A (29, 0-0)
AFC West
DenverKansas CityLos Angeles ChargersOakland
Trevor Siemian (25, 8-6)Alex Smith (33, 80-58)Philip Rivers (35, 98-85)Derek Carr (26, 22-25)
Paxton Lynch *C (23, 1-1)Patrick Mahomes (21, 10th)Cardale Jones (24, 0-0)E.J. Manuel (27, 6-10)
Brock Osweiler (26, 12-9)Tyler Bray (25, 0-0)
Connor Cook (24, 0-1)
Chad Kelly *D (23, 253rd)


NFC East
DallasNew York GiantsPhiladelphiaWashington
Dak Prescott (24, 13-3)Eli Manning (36, 116-94)Carson Wentz (24, 7-9)Kirk Cousins (29, 20-23)
Cooper Rush (23, undrafted)Geno Smith (26, 11-19)Nick Foles (28, 21-18)Colt McCoy (31, 8-17)

Davis Webb (22, 87th)

NFC North
ChicagoDetroitGreen BayMinnesota
Mike Glennon (27, 4-14)Matthew Stafford (29, 52-57)Aaron Rodgers (33, 99-50)Sam Bradford (29, 32-44)
Mitchell Trubisky (23, 2nd)Jake Rudock (24, 0-0)Brett Hundley (24, 0-0)Case Keenum (29, 9-15)
Mark Sanchez (30, 40-39)

Teddy Bridgewater *E (24, 16-12)
NFC South
AtlantaCarolinaNew OrleansTampa Bay
Matt Ryan (32, 87-62)Cam Newton (28, 54-44)Drew Brees (38, 137-105)Jameis Winston (23, 15-17)
Matt Schaub (36, 48-46)Derek Anderson (34, 21-27)Chase Daniel (30, 1-1)Ryan Fitzpatrick (34, 49-67)



Ryan Griffin *B (27, 0-0)
NFC West
ArizonaLos Angeles RamsSan FranciscoSeattle
Carson Palmer (37, 89-85)Jared Goff (22, 0-7)Brian Hoyer (31, 14-16)Russell Wilson (28, 64-27)
Drew Stanton (33, 9-7)Sean Mannion (25, 0-0)C.J. Beathard (23, 104th)Austin Davis (28, 3-8)
Blaine Gabbert (28, 9-29)


Preseason Prodigies

There’s some buzz in Cleveland because the Browns won all four of their preseason games. This coming off a 1-15 season and just 38 wins in the nine seasons since they last posted ten wins.

Is this buzz rational?

It’s easy to dismiss the preseason. Established starters see about 4-5 quarters’ worth of action in four weeks. Playbooks remain vanilla. Youngsters are fighting for jobs and a third of the players won’t play a single down during the regular season. Wins and losses aren’t that important.

I’ll also point out that the 2008 Detroit Lions, the only 0-16 team in NFL history, were 4-0 during that preseason.

Studying the issue going back to the beginning of the eight-division format, 30 teams have gone undefeated in the preseason and 32 teams have gone winless. How have they done?

The undefeated teams are more-or-less average during the regular season, with 7.97 wins per team.

How did they fare the previous season? These teams averaged 8.29 wins. So there was a slight decline – nothing too exciting given the small sample size.

What about teams that won six or less games the previous season? They averaged 1.8 wins more, on average. The Lions even made the playoffs in 2011 after an undefeated preseason following a 6-10 mark in 2010.

I’m not convinced Browns fans should be ecstatic about their 4-0 preseason, but it’s certainly not a negative.

The flip side of this argument is more interesting. Of the 0-4 preseason teams, their average record was only 7.34 wins that season. That’s a bit concerning. It gets even more concerning when you consider that the average wins for these teams the previous season was 8.77. While I’m not certain this is significant with the sample size, either, that’s potentially a study.

The average decline, season-to-season, of teams with ten or more wins the previous season that went winless in the preseason, is 3.9.

Atlanta and Oakland fans, maybe there is something there to worry about this year.