This is something I’ve wanted to put together for a while, and I finally got around to it.  Below is an illustration showing the Eagles’ 2012 performance, relative to long-term league averages, in a variety of statistics.  The format is far from perfect.  Ideally, I’d put this into a Tableau pop-out.   Unfortunately, that software is not available for Mac.  If someone has it and is interested in putting that together, please email me and I’ll give you the necessary data.

For today, though, we’ve got two charts.  I apologize for the small size, you might want to zoom.  Just getting it in this format took about 5 times as long as actually putting the data together.

I’ve standardized all the data using standard deviations and ordered it so that the left side is bad and the right side is good.  Please note that not all of these statistics are necessarily normally distributed.  However, this is the easiest way to get everything on one chart, which allows us to quickly identify where the team’s weaknesses and strengths were last season.  Additionally, we can quickly identify the areas for which we can expect significant improvement purely as a result of mean reversion.

In particular, you should focus on the stats for which the Eagles were more than two standard deviations WORSE than long-term league average.  All averages and standard deviations were computed using 10 years of NFL data (except for Net Field Position and FO Adjusted Games Lost, which uses 5 years of data).  The right side of the chart shows you the actual statistical measure for the 2012 Eagles for each stat (i.e. Average Net Field Position was -6.67 yards).

Above, we can see a number of areas where the Eagles were more than 2 standard deviations worse than the long-term average.  More importantly, those areas are either predominantly luck-based, or show no year-to-year persistence.  Specifically:

– Fumble Recovery Rate

– Fumbles Lost

– Net Field Position

– T/O Differential

Eagles fans can expect significant improvement in each of these areas (obviously they’re all interrelated to a degree).

This next chart isn’t as severe, but gives a good view of just how good/bad the Eagles’ performance was last season.

Of particular note is the last one (bottom of the chart).  That’s Football Outsiders’ measure of injury loss per team.  It’s a weighted statistic that attempts to account for the relative importance of the players lost to injury as well as the overall number of games lost.  The 2012 Eagles, while hit hard by injuries, are not outside the expected range.  The concentration of injuries along the O-Line may mean that statistic underrates the degree to which injuries hurt the team, but the point remains, health is likely not an area in which to expect dramatic improvement (already losing Maclin already stopped much of that conversation anyway).

If you haven’t read yesterday’s post about 4th and 1 strategy, please do.  It’s important and uses concepts that I’ll be revisiting very soon (looking at other scenarios).

For today, I’m going to give you a taste of what’s featured in the Eagles Almanac.  If you haven’t done-so already, I strongly encourage you to purchase the PDF version (only $10). The paperback is also available now.  Both can be found here.

I made two contributions, one of which is a brief synopsis of the case in favor of starting Nick Foles this year.  My other article covers in-depth what I will discuss briefly today.  Basically, I’ve created a new formula for evaluating the professional potential of college quarterbacks.

You’ll have to read the Almanac for the complete breakdown, but here are the basics.  First, a couple of key charts:

For all QBs who were drafted between 1999 and 2012 and have at least 200 NFL pass attempts:

The correlation value is -0.289.  While many “analysts” have expounded on the importance of college completion percentage (we’ll look at that next), Wonderlic scores, or games started, very few (if any) have highlighted College Interception Rate as a statistic to use as an indicator of professional success.  I looked at a lot of statistics for this article, and found very few that had the predictive value of Interception Rate.

Now, with the same sample, college completion percentage to NFL Rating:

The correlation value here is 0.35.

As you can imagine, we can use both of those stats (with apparently predictive value) to create a new formula for predicting QB success.  You can see the complete formula in the Almanac, but here are some of the results.  As far as scale goes, all you need to know is that receiving a negative score is bad.  How bad?

Here are the QBs who received a negative score:

Depending on your definition of a good QB, there are potentially a few “false negatives” (most notably Donovan McNabb).  However, regardless of your definition, there aren’t many.  Conversely, I think it’s safe to say that, if they could do it over again, teams would not use 1st round picks on Kyle Boller, Joey Harrington, Cade McNown, J.P. Losman, Akili Smith, and Brady Quinn.

Similarly, though they’ve had good careers, have Michael Vick and Carson Palmer lived up to #1 pick status?  Maybe, again depending on your personal opinion, but the point is it’s very debatable.

Here is the complete correlation chart for “Formula Score” and NFL Rating:

The correlation value is .363.  That doesn’t sound like much, but given what we’re tackling here (predicting human development), it’s very good.  Additionally, in the Almanac I test this formula against the popular “26-27-60” rule, with encouraging results.

Lastly, I’ll leave you with a few specific points:

– Both Nick Foles and Matt Barkley registered positive scores.

– Robert Griffin the Third had, by far, the highest score in the sample (you can see him in the far top right of the chart above).

– Geno Smith registered the highest score overall (he wasn’t in the sample).

For more detail and specific scores, get the Almanac!  If you do, you’ll also get (among other things):

– An insider’s look at Chip Kelly’s time at Oregon (perhaps the best contribution in the entire Almanac)

– Diagrammed breakdowns of a few key “Oregon Offense” plays.

– A great reflection on the Andy Reid era.

In other words, everything you need to be ready for the start of the Chip Kelly era.

Anyone who has looked at the 4th down strategy chart above knows that going for it on 4th and 1 (trying to convert) is ALMOST ALWAYS the optimal play.  While the multi-part series of posts (Part 1 can be found here) that culminated in that chart explained the thinking behind it, it occurred to me that we didn’t actually lay out the numbers.

So here is the theory, using the concept of expected points, of why it’s usually best to go for it on 4th and 1, from nearly ANY spot on the field.  Remember that when I use expected points, I’m piggybacking off the work done by Brian Burke at AdvancedNFLStats.com  (expected points).

The overall thesis is: Possession in an NFL game is EXTREMELY valuable, and NFL coaches voluntarily surrender it far too often.  With just 1 yard to gain, the odds are heavily in the offense’s favor of gaining a first down and keeping the ball.  Despite this, “common” strategy calls for giving the ball away in these cases.  This is wrong.

Basically, we are combining what we know about the probabilities of converting 4th and 1 with the expected point values of each yard line.  By doing so, we can come up with the actual expected point trade-off for each punt/go-for-it decision.  Put more simply, just how valuable is “field position” gained by punting on 4th and 1?

Before I get to the good stuff, I want to make one caveat very clear.  I’m using NFL averages to compute the following values.  Obviously, most teams deviate from the league average to some degree.  However, if I can show that all NFL teams, in aggregate, should be more “aggressive” on 4th and 1, then it’s a fairly small step to then apply it to the Eagles specifically.  I just have to acknowledge that there is, in fact, another step there.

First, we need an expected success rate.  Using this site, which I cited for our 3rd down play-selection/game-theory discussion, we can see that over the past 10 years, all 4th and 1 plays have been successful 66.5% of the time.  Below is the output.  The 66.5% is simply the weighted average success rate.

Second, we need to know just how much field position can be expected to be gained by a punt.  Using ESPN’s stats, we can see that last year, the median NET punting average was approximately 41 yards (between 41 and 42).

So we have our building blocks:

– Teams are successful at converting 4th and 1 yard 66.5% of the time.

– By choosing to punt, teams can be “expected” to gain approximately 41 yards of field position.

Now let’s look at expected points and put those two things in context.  Here is a graph showing the expected value of a first down at each yard line.

Unsurprisingly, the expected value of a first down increases towards 6 points as you get closer to the goal line.  By itself, though, this chart isn’t overly helpful.  However, we can use this chart to gauge the value of an average punt in each spot.

Let’s look at the scenario of a 4th and 1 at the offense’s own 9 yard line (the worst possible field position at which this can occur).  Simplifying things, there are 3 potential outcomes.

– Punting, which we will assume results in the opposing team taking possession at the 50 yard line (41 yard kick).

– Going for it and converting.  Here, to keep things easy, we’ll assume the offense gains just 1 yard, the minimum needed to gain a 1st down.

– Going for it and failing, the result of which gives the opposing team the ball at the 9 yard line.

Applying the success rate and expected points we saw above, we come to the following values for each scenario:

– Punting is worth -2.04 points, which is the expected value of a 1st down at the 50 yard line (for the other team, hence the negative).

– Going for it and gaining 1 yard is worth -0.21 points, which is the value of a 1st down at the 10 yard line.  However, this only has a 66.5% chance of happening, which we’ll adjust for in a moment.

– Going for it and failing is worth -4.83 points, which is the value of a 1st down for the OTHER team at the 9 yard line.

Using the 66.5%/33.5% success odds, we can calculate the expected value of going for it, that is the expected value WITHOUT KNOWING if you will succeed or fail.

Converting: -0.21 * .665 = -0.14

Failing: -4.83 * .335 = -1.62

Combined: -1.62 + -0.14 = -1.76

See why that’s a big deal?

Given a 4th and 1 at your own 9 yard line, an average punt is “worth” -2.04 points, while going for it (with average success) is “worth” -1.76.

Going for it is worth 0.28 points MORE than punting.

Hopefully one example was enough, so rather than continue, I’m just going to give you a chart.  Here is the expected value of both punting and going for it at each yard line (between the 9 and 50), assuming a 41 yard punt, a 1 yard gain if converting, and league average success rate when going for it.

So there you have it.  As you can see, going for it is more valuable than punting regardless of field position.  As I said at the top, with just 1 yard to gain, the odds heavily favor the offense, yet they don’t seem interested in taking advantage of it.

Giving up possession of the football, regardless of whether it’s the result of a TO or punt, is bad.  It looks like teams are underrating the degree to which punting the football is a negative play.  They also seem to be under-appreciating the odds of converting in 4th and 1 situations.  As a result, “common” NFL strategy is far from optimal, leaving an opportunity for a forward thinking team to gain a significant advantage over the rest of the league.

Obviously each of these assumptions needs to be tweaked for individual teams.  However, if the league, overall, should be going for it a lot more often in 4th and 1, then by definition, many teams should going for it more often.  Here are some quick adjustments that result in “going for it” more often, with the reciprocals being adjustments that should result in punting more often:

Bad Punter – Go for it more often (lower net punting average)

Good Offense – Go for it more often (higher expected value of a first down)

Bad Defense – Go for it more often (value of OPPOSING team’s possession after a kick is higher)

Someday, we’ll see a team take advantage.  I think Chip Kelly will be more aggressive than average (closer to optimal), but far from as  “aggressive” as he should be.  Hopefully, after developing a successful track record and some credibility, he’ll have the stones to implement strategy like this more fully.

Note: Only two teams today.  Let me know if you’d like to see more. Since I’m nominally Eagles focused, I’m hesitant to spend too much time on other teams.  If everyone is interested though, I’ll parse the projections for more teams.

Yesterday I showed the most “underrated” teams heading into the 2013 season, with Carolina and Washington emerging as two to keep an eye on.  I think the FO projections for both are a bit aggressive, but I still come down higher than the Bovada lines.  Today, naturally, we’re going to other way and looking at the most OVERrated teams in the league.

Here are all of the teams for which the Bovada O/U lines are higher than the FO projected wins.

Most obvious is the number of “overrated” teams and the relative magnitude of the differences.  Simply, compared to what we say yesterday, it seems there are a lot more overrated teams than underrated.  Before we get to the specific teams, I want to illustrate a very important point about gambling lines. 

Remember what I said about the Cowboys (on Tuesday)?  I expect the O/U lines for the Cowboys to usually be artificially high as a result of the number of “homer” bets placed on the team each year.  While there are only a few teams I suspect of having such serious distortions, it’s logical to think that, throughout the entire league, lines are artificially high.

basically, fans are optimistic.  This, in turn, makes them terrible gamblers.  What’s the upshot?

If we add up all the O/U lines from Bovada, we get 262.5 wins.

So what?

There is a maximum of 256 wins available.

The Football Outsiders projections, of course, add to 256.1.

This means that, just as the chart above shows, teams are naturally more likely to be overrated than underrated.

Now let’s look at specific teams.

Atlanta

The Falcons stand out as the most significantly overrated team in the league, with a O/U 2.4 wins higher than the FO projection. The Falcons were very good last year (won 13 games).  The team kept most of its roster intact, and added Steven Jackson.  Matt Ryan is still the QB, and should be entering his prime.

In that light, expecting the team to win just 10 games this year (a decline of 3 from last season) seems very reasonable.  What gives?

– The Falcons point differential from last year points to an 11 win team.  When projecting improvements/declines for each team, its important to focus on the “true” value for the previous year, rather than the actual W/L.

– The 2012 Falcons faced the 27th toughest schedule in the league (according to FO).  In 2013, the team looks to be facing one of the top five toughest.

– Last year, Atlanta recovered 64.29% of all fumbles, including more than 72% of the opposing teams’ fumbles.  Both those measures are likely to regress.

– In the same vein, the team lost just 4 fumbles last year.  The long-term NFL average is 11.

– The division is likely to be much tougher this year.  Sean Payton is back.  Carolina, as we saw yesterday, is likely to improve substantially.  Tampa Bay, while being a bit of a wildcard, certainly appears to have made substantial roster improvements.

All in all, I’m inclined to agree with FO here.  This looks like an 8-8 team, with the potential for a serious implosion.

Minnesota

The Vikings won 10 games last year, still feature Adrian Peterson, and have a young QB that should be expected to improve.  And yet, the O/U is 7.5 and FO projects the team to record just 5.5 wins.

Using point differential, the “true value” of this team last year was actually pretty high.  Using a 2.67 exponent and the Pythagorean formula, the 2012 Vikings were a 9 win team.

So what’s the case against?  And more importantly, just how much regression should we expect?

– Christian Ponder is the “young QB”.  I’m not a fan.  I’m not going to delve into Ponder-specific stats here, but take my word that things aren’t looking good for the “Ponder is a franchise-QB” crowd.  If you’re interested but don’t want to do the research, buy the FO Almanac, they’ve got more in there.

– Adrian Peterson had a HISTORICALLY good year in 2012.  He is unlikely to replicate that this season.  He will still likely be very good, but “very good” won’t be enough to carry the team like he did last year.

– The team faced the 7th toughest schedule last season (Pro-Football-Reference), which would normally be a good sign.  However, the schedule this year looks to be even tougher.  It’s always hard to project team strength before the season, but consider the team’s non-division schedule includes games against the following teams (and Cleveland):

Seattle (@), Baltimore, Cincinnati (@), Pittsburgh (U.K), Carolina, the Giants (@), the Redskins, and the Eagles.

Not all of those teams will be as good as expected (Giants and Pittsburgh would be my picks for disappointment), but it will almost definitely be an incredibly difficult run of games.  Meanwhile, the Vikings still have to play two games against Green Bay.

– Minnesota was middle-of-the-pack in turnovers last season, and it’s recovery rate was right around 50%.  That means we should expect regression, but it also means that Turnover Luck isn’t a likely source of improvement either.

– Lastly, the team lost Percy Harvin.

Putting it all together, this could be a very ugly season for the Vikings.  As far as a personal projection goes, I have the Vikings in the 4-5 win range, which is even lower than FO.  While there are a number of explanations (including the points above), it really comes down to Christian Ponder versus a very tough schedule.  I think it’s likely to be a train wreck.

Lastly, I said yesterday that it might be instructive to simply take the average between the Bovada O/Us and the FO projections and use that as a projection for the year.  I’m still doing research regarding the relative accuracy of each, but the average looks promising.  Regardless, here are the values (remember that they’ll be slightly inflated due to the optimism distortion I mentioned at the top).

Yesterday I compared the FO win projections for every team against the O/U lines from online bookmaker Bovada.lv.  I was light on analysis, so today I’ll focus more deeply on a few teams that carry the largest deviations.  After writing the UNDER-rated section, it was apparent that this post needs two parts.  So the OVER-rated teams will have to wait until tomorrow.

Reminder – The Bovada line isn’t meant to be a prediction, but in theory, should function as a measure of what the general (betting) public thinks of each team.  So when the Bovada line is HIGHER than the FO projection, I’m calling that team OVERrated.

First, let’s look at the UNDER-rated teams.  Here they are:

Above are all of the teams that have a higher FO projection than Bovada O/U.  I’m going to focus on the teams with the largest differential, for obvious reasons.

Carolina

A difference of 2.5 wins is HUGE.  If betting we legal (and if I had data on FO’s predictive accuracy), I’d be very tempted to take the over here, figuring that if the “true” value of the Panthers team is 2.5 wins above its O/U, then the team can suffer some bad luck and still hit the over.  Why the big difference?

The Panthers won 7 games last year, the same number as the current 2013 O/U.  That makes things fairly easy from a projection standpoint.  All we need to do is answer: Why will the team be better this year than last?

The main factor in the FO projections (i think, I don’t now the formula) is the team’s 0-7 record in close games.  Typically, that record in close games (<7 Points) is close to .500.  Just going 2-5 last year in such situations would have given the team 9 wins.  FO is careful to note that this may, however, be the result of terrible coaching (Ron Rivera).

Looking at the team’s statistical performance, the 2012 Panthers offense (Points Scored) was just 2% worse than average.  Meanwhile, the teams was exactly average on defense.  Put together, you’ve got the definition of an average team.

The biggest plus on offense is the assumed development of Cam Newton.  Newton is entering just his 3rd year in the league and has obvious “elite” talent.  While it’s reasonable to expect a player like this to improve, I do wonder how much “upside” is left.  Cam Newton had an 86.2 QB rating last season, already a very strong performance.  Additionally, compare the stat line from the last two years:

Notice anything?

The lines are close to identical.  It’s possible that Cam Newton’s rookie year was actually a very good representation of his “true” ability.  The biggest difference above is the significant decline in Interception Rate, which is obviously a big step forward (if it’s not a one year anomaly).  However, the overall lack of improvement from year one to year two, combined with the fact that he’s ALREADY very good, tells me people might be overlooking the possibility that Cam is as good as he’s going to get (or at least close to it).  In short, there’s not much higher he can go (and I don’t think he’ll ever challenge for the Brady/Manning/Rodgers level).

Before you ask, his rushing stats also show the same consistency from year one to year two.

On defense, the team returns a very strong DL backed by Luke Kuechly, who had an incredibly strong rookie year.  The team, in the draft, added Star Lotulelei.  Readers who followed my draft projections will know that Star ranked, according to the TPR system, as one of the biggest “steals” in the first round.  If he is as good as those projections suggest, the Carolina defense will be strong (certainly stronger than last year).

The biggest issue is the Secondary, which was/is terrible.  However, since the team managed league-average status last year with a similar group, I don’t see that costing them  more this year.  If anything, the stout front 7 should allow the team to scheme around its issues (a bit).

There aren’t a statistics that immediately jump out to me as “mean-regressors”, so not much adjustment to do there.  The 2012 schedule strength wasn’t out of whack, so no potential there either.

Overall, I’m leaning more towards Bovada here than FO.  All things considered, I’d put the Panthers at 8 wins, which is still higher than the Bovada line.

Washington

The Redskins are the other team that qualifies as significantly underrated, according to our comparison.  FO projects the team to register 10.3 wins, which is 1.8 games higher than the Bovada O/U.  Putting that projection in context, 10.3 wins is the 3rd HIGHEST FO projection (behind New England and Green Bay), tied with Denver and Seattle.

Raise your hands if you had the Redskins as a member of the “SB favorites” group.

Essentially, the FO argument for the Redskins is: RG3 is awesome.  It’s a very valid point.  a healthy RG3 and an average defense may be good enough to get you to 10 wins (it’s easily good enough for playoff contention).  That’s the upside to having a Superstar QB.

Once again, I have to raise a few red flags regarding the FO projection.

– The 2012 Redskins had a TO differential of +17.  Needless to say, that’s unlikely to repeat.  In my database (last ten years) I can find just ONE team that registered a TO differential of +17 and managed to avoid a significant decline the next season, the 2011 Patriots (+17 followed by +25 last year).

– Despite having the league’s top rushing attack, the Redskins lost just 6 fumbles last year, with an overall recovery rate of 67%.  Again, neither measure is likely to be as beneficial this season.

On the plus side for the team (minus if you’re an Eagles fan) is the recovery of Brian Orakpo, who missed most of last season with a pectoral tear.  The defense was -7% last season in points scored, and adding Orakpo is a pretty big addition.  Assuming the Redskins finish 2013 around the 0% mark on defense, the team merely needs to duplicate last season’s offensive performance to finish in the +70 to +80 point differential range.

That puts the team at around the 10 win mark (Pythagorean using a 2.67 exponent).  However, given the TO stats I mentioned above, I think that’s the HIGH end of the potential range.

That’s slightly below the FO projection (10.3), meaning even if things go well luck-wise for the Redskins, I don’t expect the team to hit that mark (though 10 wins is essentially equal).

Regardless, Washington is likely to the best team in the NFC East, meaning Eagles fans need to pay attention.  However, I’d say 9 wins is much more likely.  Similar to the Carolina projections above, that leaves me in between the Bovada and FO lines.

Naturally, I just realized that we should take the average of the two measures to create a separate projection, so I’ll include that tomorrow, when we take a look at the most OVERRATED teams.

We’re close enough to the season for win projections to have some validity.  For the most part, rosters are set (the important pieces anyway).  A big injury or two will obviously sway our expectations, but I thought it would be interesting to take a look at expected performance today so that we can gauge the relative importance of any injury from here on in.

I’m going to use two sources for expected wins: Bovada (a proxy for Vegas) and Football Outsiders.  The reason I’ve chosen these two is because their projections are readily available (free on Bovada.lv and included if you buy the FO Almanac), and, in my opinion, represent two different viewpoints.

Basically, Bovada is a proxy for “general sentiment” while FO is a proxy for “analytical projecton”.  The FO viewpoint is straightforward.  Regarding Bovada, remember that gambling lines are directed at the general public.  The idea, for the bookmakers, is to get as close to 50% of the bets to land on either side of the over/under line.  That’s why you see gambling lines move as people place their bets.

Therefore, gambling lines are essentially a reading of the “consensus” opinion of the general public (gambling public at least) for each team.

That’s how I’m getting to over or underrated.  Below are charts for each division in the NFL.  Listed are the teams, their Bovada over/unders, and their FO mean win projections.  Also included is a column showing the difference between the two expected values (FO – Bovada).  In the difference column, RED numbers are “overrated” teams and BLACK numbers are “underrated”.  The absolute value of each numbers tells you the magnitude of the difference.

Today I’m going to break it out by divisions, with minimal comments for each.  Tomorrow I’ll look at the most over and underrated teams and see what the difference is telling us.

Let’s start, naturally, with the Eagles.

Within the NFC East, the Redskins stand as the most “underrated” team.  FO has them nearly 2 full wins higher than Bovada.  I’m not sure of the full explanation, but we can assume it has A LOT to do with RG3 and the difficult in projecting recovery from an ACL tear.  The Eagles, meanwhile, are technically “underrated”, though we have to acknowledge that Bovada only deals in .5 win increments, so 7.8 is nearly the same as 7.5.  I’ve said before that I currently have the Eagles at 8-9 wins, but I’ve also showed that the team has one of the highest ranges of potential performance for this season (i.e. riskiest).

The Cowboys, perhaps not surprisingly, are significantly overrated.  This may reflect the optimism and size of the Cowboys fan base. A lot of “homer” bets could push the gambling line up.  I don’t have data to confirm that, but my guess is the Cowboys O/U lines are frequently distorted due to that factor (as are a few other popular teams, perhaps even the Eagles).

Apparently, the entire NFC North is overrated.  Minnesota shows the biggest discrepancy, 2 full wins.  Detroit is a “chic” pick for surprise team this year, but FO isn’t as confident as the public.

This is perhaps the most interesting division, since FO and Bovada almost could not disagree more.  FO has Carolina as the best team in the division, while Bovada (the public) has them as the worst.  Conversely, the reverse is true with Atlanta.  Clearly, there are some severe distortions at work here.  I’ll get into it more tomorrow, but this is likely the result of the type of seasonal “luck” we’ve talked about in the past.  Atlanta won 13 games last year, and has kept the bulk of its roster intact.  However, the Falcons had one of the easiest schedules in 2012.  The team also fell on the “lucky” side of stats like fumble recovery rate (which is likely to regress).

There are some big differences here as well, but the overall outlook for the division doesn’t change.  It’s a two-horse race between the 49ers and the Seahawks.  St. Louis, despite getting a lot of press as an “under-the-radar” team will probably struggle to reach mediocrity.

No big surprises here, outside of the fact that Bovada has Miami at 8 wins.  That seems high to me, and FO agrees.  Buffalo and the Jets are interesting because they both have potential rookie starting QBs.  Typically that means a poor season, but given the terrible QB play each team has had recently, we might actually see a surprise here if either EJ Manuel or Geno Smith is legit.

Projected by FO to be the tightest division, the AFC North shows no clear favorite.  Pittsburgh is a bit overrated, and might be subject to the same distortion as the Cowboys.  Baltimore, though, despite winning the Super Bowl, comes in as significantly UNDER-rated.

The AFC South looks like a pretty weak division.  I like Andrew Luck, but the Colts are a prime contender for regression this year.  I think the FO projection for Jacksonville is high.  The rest looks reasonable.  Houston as a 10.5 win team seems aggressive.

Denver, barring an injury to Manning, is going to be among the best teams in the league.  Still, that’s a tough over to hit (12 wins or better).  I’m more bullish on Kansas City than FO is, and lean towards Bovada here at 7-8 wins.  San Diego is the only team in the league for which the FO and Bovada projections agree completely.

As I said at the top, I’ll have some more detailed analysis tomorrow, I just didn’t want this post to end up at 2000+ words.  For now, this is a good cheat sheet for anyone trying to get their bearings on the upcoming season.