So to get ready for playoff chase, I took a look at each team's statistics for the past 6 weeks(weeks 7 - 12). Shown are the offense and defense statistics, the rank, and what the league average is. Then I assigned grades to the offense, defense and team as a whole. You can read all 32 team breakdowns in the full post:

NFL 2023 - Offense, Defense, Team grades for weeks 7-12

As a quick TLDR, the following chart shows NET Yards/play, NET EP, Power Ratings, and change in power rating vs post week six rating. It is sorted by NET EP. Remember, these stats are only for weeks 7 - 12, not the full season.

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NFL Team Ranks for NET Yards/Play, NET Expected Points & Power Rating weeks 7-12

Each of the 32 team capsules include the following information.

• Net Expected Points
• Net Yards / Play
• Power Rating
• Graphics Metrics Capsule showing weeks 1-6 and 7-12 in one chart for comparison
• Offense Grade & Comments
• Offensive Metrics
• Defense Grade & Comments
• Defensive Metrics
• Summary

Here is an example of the Dallas Cowboys Team Capsule for weeks 7 - 12.

Dallas Cowboys - Offense Defense Team Stats Grades Weeks 7-12

Obviously the letter grades and comments are a bit subjective, but the statistics are not. Have fun checking out the stats of your favorite team and rivals. Enjoy the football tonight!

Here are comparative ranking and ratings for NFL wide receivers and tight ends through week 11.

There were 88 wide receivers and 30 tight ends in the ESPN rankings, so I am going to stick with those same 118 players. I will post the ESPN scores in the very last columns next to the comparative grades. You can check out the ESPN rankings here: ESPN Analytics RTM

With all the grades and players this is quite a long article. So much so that I can only going to post about 1/4 of the article here on Reddit due to images, pdf links and formatting issues.

Here I will post the section about creating the rankings and ratings for all the wide receivers and tight ends while keeping math to an absolute minimum. If you are interested in any/all of the other 3 parts, you can read the entire article here:

NFL 2023 - Wide Receiver & Tight End Ratings & Rankings

As a quick sysnopsis the full article can be looked at in 4 parts:

1. Attempting to dissect the ESPN Analytics Receiver & Tight End metric scores and how they are derived.
2. The metrics & grades for all the wide receivers and tight ends compared against their fellow peers. Thus wide receivers are compared to wide receivers, tight ends to tight ends.
3. Grading all the wide receivers & tight ends as one large receiver group. This could be looked at as almost a fantasy football list(and is the way ESPN presents their list).
4. Attempting to mimic ESPN Analytics wide receiver scores by including the sub scores of OPEN CATCH & YAC.

Before starting, note that the unusual team abbreviations come from Pro-football-reference.com. I know they are a bit odd but you should be able to figure them out.

TLDR: Just look at this first chart. It shows the percentile rank of each team's wide receivers & tight ends. In this chart, wide receivers are ranked against all other wide receivers, and tight ends against all other tight ends.

NFL 2023 Wide Receiver & Tight End Percentile Ratings by Team

Top 20 Wide Receivers & Tight Ends Litmus Test

The chart below shows the NFL top 20 receivers & tight ends through 11 weeks. One list is from ESPN, the other list are these rankings. 

The players the two lists agree on are color coded.  The receiver ranking lists agree on 11 players: Brown, Aiyuk, Lamb, Moore, Kittle(TE), Allen, Collins, Dell, Hill, Evans, Metcalf.

Let’s set them aside for a moment and look at who they disagree on for Top 20 rankings.

The  9 players from the left list are: Thielen, Beckham, Bourne, Raymond, Flowers, Downs, Meyers, Andrews(TE), McBride(TE).

The 9 players from the right list are: Jefferson, St. Brown, Chase, Kelce(TE), Waddle, Nacua, Diggs, Shaheed, Samuel.

Which ranking list do you think is a more accurate, or more flawed?  It is fine to think they are equally accurate, or equally flawed.

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In this chart all WRs & TEs are in the same pool and comparatively ranked against each other like ESPN does it. You can read more about this in the linked article.

The list on the left is the ESPN Analytics Receiver Rankings.  The list on the right are the ratings and ranking you will read about here.

The Comparative WR/TE Receiving Metrics

Here is the list of metrics I chose to use for rating the wide receivers and tight ends.

• 1st Downs / Game
• Yards Before Catch / Reception
• Yards After Catch / Reception
• Average Depth of Target
• Drop % (inverse - lower drop % score higher)
• Passer Rating when Targeted
• Target % (Targets/Routes)
• Reception % (Receptions/Targets)
• Receiving Yards / Route

Now you may have read the other ratings articles I've done and noted how ratings are often done by Standard Deviation(StDev in sheets) Units.  Let's do something a little different and use Normal Distribution(normdist in sheets) instead of StDev. Just remember, like all of the ratings done here, the wide receiver & tight end ratings are COMPARATIVE. 

In comparative ratings, scores are generated by the performance of one receiver against all receivers, and same for tight ends.  Basically, each receiver reeieves a score between 0 - 0.999 for each metric, based on their position in that metric compared to their peers.  The player with the highest score in a metric may get 0.98 score, while the lowest may get a score of 0.02.  This is quite different from almost all other NFL ratings and rankings, but useful in that it shows who is the best among the position groups when compared to each other, not some standard or formula.

The Wide Receiver & Tight End Metrics & Ratings

So take a look at these charts.  One is ranking the wide receivers, the other is ranking the tight ends.  Here is the important info:

• Next to each metric is the normalized score for that stat.
• Add up the scores for each of the 9 metrics to get a final score.
• Normal Distribution is used on the Final Scores to generated a percentile for each receiver & tight end.
• For this portion of the ranking & ratings, receivers are measured against receivers, & tight ends are measured against tight ends.
• Thus the percentile score of a wide receiver is the percentile of wide receivers they fall into, and same for tight ends.
• The last 4 columns are ESPN Analytics scores and rankings for comparison.
• There will be PDFs available as some images don't scall well, particularly on mobile devices.

NFL 2023 Comparative Wide Receiver Ratings PDF

NFL 2023 Comparative Tight End Ratings PDF

NFL 2023 Wide Receiver Ratings through week 11

NFL 2023 Tight End Ratings through week 11

Let's try to go one step further and estimate the quality of each team's wide receiver unit.  To do so we are going to simply average out their wide receiver scores and compare those averages.  It would be better to try to do weighted averages that take into account share of targets or completions in some way, but it would be much more difficult and would require determining the best way to weigh each receiver's input.  So let's cheat a bit and just look at simple averages and see how accurate they are.

In this pivot table you will see each teams rated receivers, along with the team average.  I also included a table showing each team's receiver ratings based on those averages.  In this ultra simple look at it, the best receiving units are San Francisco, Miami, & Philadelphia.  The worst are the Jets 3rd from bottom, Washington, & Carolina is last.

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Average Wide Receiver Ratings by Team

Now that we have the receivers all sorted by team, let's add in the tight ends.  Some teams did not have a qualified tight end.  If this happened, then it is shown as N/A.  Other teams had 2 tight ends who qualified for rankings.  If this was the case, both are included.

To makes things easy for you to find your team and ratings, the info has be broken down by conference, by division, and by team.  This should make comparing and contrasting easy and allow you to focus on your team, division or conference as you see fit.

NFL Wide Receiver & Tight End Ratings by Team

Now let's simply change the scores into percentiles using normal distribution, then multiply by 100, so you can see where each receiver ranks against other receivers, and where each tight ranks against their fellow peers. Remember a WR is compared against all WRs, and a TE against all TEs 

The second chart just rounds off the percentiles for easier reading. The charts are broken down into conferences, divisions, and teams to make it easy to read and digest.

NFL Wide Receiver & Tight End Percentile Ratings by Team

NFL Wide Receiver & Tight End Rounded Percentile Ratings by Team

Best & Worst Receiving Units

Using the final rounded percentiles, we can see that the San Francisco 49ers have the best combination of receivers & tight end.  Aiyuk is the #1 rated WR in the 99%, Samuel is a very strong 76% and Kittle is #1 Tight End at 98%.

Other teams with strong receiving units:

• Houston: Collins 96%, Dell 86%, Schultz 81%
• Miami: Hill 96%, Waddle 80%
• Minnesota: Jefferson 98%, Addison 69%, Hockenson 87%
• Baltimore: Beckham 66%, Flower 60%, Edwards 94%
• Philadelphia: Brown 97%, Smith 69%, Goedert 62%
• Detroit: St. Brown 89%, Reynolds 54%, LaPorte 75%

The Bears are quite good with 2 of 3 places set in Moore 96% & Kmet 76% but Mooney 31% is a weak link.

Team with weak receiving units:

• Carolina: Thielen 66%, Chark 14%, Hurst 8%
• Washington: McLaurin 40%, Samuel 30%, Thomas 46%
• NY Jets: Wilson 43%, Lazard 7%, Conklin 56%
• NY Giants: Slayton 37%, Robinson 32%, Waller 70%

The Chiefs are ranked between the Jets & Giants overall but they have Kelce 93% and Rice 63% so they are thin but not hopeless.

So there you have it.  A non proprietary comparative ranking of NFL wide receivers & tight ends through week 12. I look forward to reading your thoughts & criticisms in the comments below.

I hope everyone enjoyed their Holiday weekend. Enjoy the football today!

So I have been badgering you guys for weeks now with ratings, statistics, standard deviations, etc... But just like back in middle school, during holiday weeks math teachers are too lazy to write lesson plans.

Therefore everyone gets the holiday off from any math, calculations, conceptualizing or crunching! Enjoy your turkey, personally I'd prefer an easter egg.

Instead I would like to offer the story about a player, Lester Hayes, who is now known more for his infamy, than for how good a player he was.

Imo, Hayes is a HOF player being kept out because, just like a notorious hoodie wearing coach we all know, he kind went into the grey area when it came to the rules at the time.

Maybe if enough people review Hayes' stats, the NFL Senior Selection Committee will at least take a look at his career and statistics for HOF consideration.

You can read the full story here: 1980 – The Year Lester Hayes Broke The NFL – The Stickum Saga

TLDR: Just watch the 3 min vid below and you will get the general gist of the Stickum story. However, it does not even begin to touch on how good a player Hayes was.

https://www.youtube.com/watch?v=2Bypl5bpZF8

There is more to the story, including Hayes' remarkable 1980 playoff performance and the history of Stickum in the NFL, so I hope you can find the time to read the full article.

Happy Holiday to all celebrating today. Enjoy the time with friends, family & football!

Quick Synopsis

Lester Hayes in the 1980 regular season

• 13 interceptions in the regular season - The modern NFL record that still stands.
• 7 interceptions in a 6 game stretch.
• Streaks of 6 consecutive games and 4 consecutive games with interceptions.
• Picked off at least one pass in 12 games of a 16 game regular season.
• 5 Post season interceptions.
• 18 interceptions in 20 games.

Lester Hayes Career

• Won 1980 NFL Defensive Player of the Year
• Won Two Superbowls - 1980, 1983
• 5 time Pro Bowl Selection
• All Pro 1st team once & 2nd team five times
• 39 career interceptions
• 8 career post season interceptions
• 7 fumble recoveries

In the 34 game stretch that began with the final 2 games of 1978, all of 1979, and all of 1980, Lester Hayes recorded 23 Interceptions, for 407 return yards, and 3 Touchdowns.  It is a span of modern* defensive cornerback greatness that I can only find one instance that is close to matching it.

In the first 34 games of his career, Everson Walls recorded 22 Interceptions and returned 1 for a touchdown.  I could find no other modern* NFL player who could even get close to 20 interceptions over a 34 games span.  

*Dick "Night Train" Lane had 25 INT in his first 34 games in 1952-54, and holds the record for most interceptions in a season with 14.

Lester Hayes 34 game span in which he recorded 23 interceptions. He added 5 more in the 1980 playoffs.

This has to be one of the bigger head scratching stats I have seen in a while. I was looking at the Jets Bills box score and the QBR numbers caught my eye.

Tim Boyle 7/14 33yds 0TD 1INT 1 Sack 1rush attempt for 1 yard QBR 50.2

50% completion, NFL avg 64.9%

2.4 yard/attempt average, the NFL avg is 7.0

4.7 yards per completion, NFL average is 10.8

So I decided to grab every QBR rating for Sunday(and Passer Rating to keep us all grounded in reality).

That legendary Tim Boyle performance you witnessed, according to QBR, was the 13th best qb performance on Sunday.

https://www.espn.com/nfl/boxscore/_/gameId/401547543

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QBR loves Tim Boyle

Tim Boyle for Joe Burrow? Let me think about it

Tim Boyle for Josh Allen? Maybe if you throw in a 3rd round pick.

Tim Boyle for C.J. Stroud? C.J. Stround and who else?

Tim Boyle for Tua Tagovailoa? If you toss in a 1st rounder we can talk.

Tim Boyle for Russell Wilson? Hang up the phone scoffing at the unmitigated gall for even calling me.

Whew, thank you QBR for keeping me from looking like a complete idiot as a NFL GM.

Before diving in, I just want to wish everyone a nice holiday week, and safe travels to all those doing so.

NFL 2023 - Offensive Line Rankings

If you are interested in the Math & Methodology just keep reading, or for even more: NFL 2023 - Comparative Offensive Line Ratings

If you are math adverse and just want to read the team offensive line capsules (all the charts and data are still there if you wish to review them): NFL 2023 - Offensive Line Rankings

TLDR: Just look at the last 2 columns on the main chart posted below.

Example Offensive Line Capsule

NY Giants Offensive Line Capsule

The Role & Metrics of the Offensive Line

For the offensive line ratings, we are going to assume that the offensive line's 4 main objectives are:

• Open holes for the rushing game
• Identify, adjust and negate blitzes
• Protect the quarterback for a reasonable amount of time
• Win & hold blocks as a unit

In addition, like any other player or unit on the field, they should accomplish this without drawing fouls.  Since this is basically a given for all units/players, I won't list it as a main objective, but offensive lines will be scored on their ability to avoid costly penalties.

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NFL 2023 - Offensive Line Metrics & Ratings - The main chart is listed alphabetically. The final columns show the rankings in descending order.

The List of Offensive Line Metrics

• Rushing Yards Before Contact x 2
• Blitz %
• Pressure %
• Blitz Deflection %
• Average Pocket Time
• Sack %
• Estimated Penalty Yards
• Overall Block Win%

Let's look at each objective and identify the metric(s) used to measure the line's effectiveness.

Opening Holes For The Rushing Game

Clearly one of the offensive line's main tasks is to run block effectively.  An offensive line that cannot run block and create opportunities for ball carriers is going to find itself forced into a lot of predictable pass block situations.  Without the threat of an effective running game, defensive players can sit on pass routes and pass rushers can pin their ears back.

The metric to be used to measure run block effectiveness is Rushing Yards Before Contact(YBC), and this will be the only rushing metric used..  While  the ball carrier's ability is certainly a part of the metric, the size of the hole, or the time until the first defender can make contact with a ball carrier, is primarily a result of blocking.  And while wide receivers and tight end blocking is also a factor, we can simply assume that all wr/te blocks are equal(which they surely are not), and assume these blocks are simply an extension of the line blocking(or that the wr/te in the play assume linemen status for the play).

Because the run game can in and of itself win ball games, and an effective run game compliments an effective pass game, the value of this metric will be doubled(the score each line receives for this metric is multiplied by two).  Thus the score you see in the Standardized YBC column is the sd value, and the next column shows the YBC score(its SD value * 2).

Pivot tables were needed to sum up totals like every players that has rushed the ball for each time to calculate YBC. You will see more of them below.

Pivot Table for YBC for each team. If we expanded the table you would see every player that has rushed ther ball for each team along with their respective stats.

Identifying, Adjust To, And Negate Blitzes

This is probably the most difficult and important task assigned to the offensive line.  Before providing time for a quarterback to throw, the line must identify the pass rushers, call the line protection, and still be aware of any misidentifications or additional blitzers not accounted for pre-snap.  If any of this goes wrong without a blitz, it can lead to a negative play.  When it goes wrong with a blitz, the potential for disasterous outcomes rises significantly.

We are going to assign three metrics to measuring this task:

Blitz % - An offensive line that faces a high amount of blitzing will score more higher in this metric.  The purpose of this metric is to measure the amount of blitzes the line has had to face while producing the stats it has.  It should be clear that a line facing 30% blitz % who gave up just 5 sacks, is probably more effective than a line who faced a 15% blitz % and gave up 5 sacks.  Either the blitz pickup of the latter line is not good OR they are getting beat without a blitz.

Pressure % - Pressure % is simply the amount of hurries, knockdowns and sacks as a cumulative total, changed into a percentage by dividing that sum by the amount of pass attempts, scrambles & sacks.  It assigns equal weight to a knockdown, a hurry and a sack even though they each have different Expected Point values, and affects on down/distance/outcome.

For measuring purposes, offensive lines that allow the least amount of pressure will score highest.

Blitz Deflection % - This is a metric you have never heard of because I just made it up.  I am defining Blitz Deflection % as [1 - (Pressure % / Blitz %)].  Let's look at a simple example of what it is and why it may be a valuable metric.

Let's assume a line has faced a Blitz % of 25%.  Let's also assume, that every blitz leads directly to pressure.  Thus a Blitz % of 25% should lead to a Pressure % of 25%.  Essentially, blitzes always work.  Thus if a team faces 25% Blitzes, then the average line would allow 25% pressure.

A line that could keep pressure % BELOW Blitz % would be doing a better job than a line who's Pressure % was higher than their Blitz %.  If this happens the line must be giving up pressure outside the Blitz and negating little to none of the blitzes sent.

Looking at the chart, Baltimore's offensive line has faced the blitz on 30.68% of designed passing plays.  Their pressure % is a mere 14.49%.  While this cannot show the exact breakdown of how often Baltimore's offensive line picked up the blitz and how many time they allowed pressure without a blitz, it should be obvious that line is picking up blitzes.

The ratio [1 - (14.49% / 30.68%)] = 52.78%.  Thus Baltimore's offensive line is deflecting 52.78% of blitzes.

Conversely, let's take a look at Pittsburgh's offensive line in this metric.  The Steelers Offensive line faces a blitz 18.08% of the time(by far the lowest % in the league, Cincinnati is second least blitzed at 21.61%).  However the Steeler offensive line allows a pressure % of 25.32%.

The ratio [1-(25.32 / 18.08%)] = -40.35%.  The Steeler's line is not deflecting any blitzes and giving up pressure outside of being blitzed.

Just remember Blitz Deflection is not measuring the actual amount of blitz pickups, but the theoretical amount a line is negating blitzes.

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The Blitz % Data

Protect the Quarterback for a Reasonable Amount of Time

Regardless as to whether the blitz pickup has been identified and executed properly, the offensive line is still tasked with giving the quarterback enough time to go through his reads and complete the passing motion.  It would be great if the qb is still standing and in the pocket when this is completed, but sometimes things go wrong and quarterbacks get sacked.

The two metrics being used in this portion of the offensive line ratings are fairly straightforward.

Average Time in The Pocket - The amount of time the quarterback has before contact or being flushed is average time in the pocket.  It should follow that allowing more time for the quarterback would be good, and allowing less time bad.

This is a bit of scheming that plays into this as some times have an extremely quick read system that inherently gets the ball out faster than other schemes looking for deeper, or double, routes. But it is a fairly reliable indicator on the ability of the line to pass protect and form a workable qb pocket.

Sack % - Sacks are the worst kind of pressure as they come with loss of down and yardage by the very definition of a sack.  This is an inverse metric in that it is better to have a lower sack % than a higher one.  Lines that allow a lower % of sack will score well, while porous lines will score poorly.

Minimize Penalties

Another metric in measuring offensive lines will be their ability to avoid getting in their own way.  Every penalty on each individual line is collected and the entire line is responsible for the total penalties.

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Pivot table summarizing every lineman's penalties for each team

For estimating penalty yardage, a false start is 5 yards, holding and any other penalty is 10 yards(the other penalties are a mix of 5 yard and 15 yard infractions, thus I decided to use 10 yards as the punishement for each.  Offsetting and declined penalties are still counted.  Multiplying out the types of penalties and the estimated yardage for each results in an estimated total penalty yardage total for each offensive line.  This is also an inverse metric.  Lines that have been penalized the most will score poorly, while the mistake free lines will score high.

Winning Blocks - Overall Offensive Line Blocking Win Rate

The final metric is another metric you may not have seen before, Overall Block Win Rate.   To calculate this metric, ESPN's Pass Blocking Win Rate and Rush Blocking Win Rate percentages were used for each team(which just so happened to be published this week).

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ESPN Win Block Rates for Passing and Rushing - Note how compact rush block win % is, the highest 72% is ranked 7th and lowest 70% is ranked 25th. The 7th rank Pass block win rate is 64% and the 25th best is 50%, a much bigger range.

Then the breakdown between passing and running plays for each team were taken into account.  To find the overall block win rate, the pass block win rate was multiplied by the passing play %, and the rush block win rate was multiplied by the rush play %.  Turning the resulting metric back into a percentage, leads to overall block win rate.

For example, a team has a pass block win rate of 60% and a rush block win rate of 70%.  They pass 60% of the time and run 40% of the time.  What is the overall block win %?

Overall Block Win % = [(0.60*60)+(0.70*40)]/100 = 64%

You can see all the data and calculation in the main chart.  Perhaps you think everything before this section is nonsense and overall block win rate % is the true measure of offensive lines.  In that case, here is the ranking based solely on Overall Block Win Rate %

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Overall Block Win Rate when pass/run ratio is factored in.

Final Offensive Line Ratings & Rankings

Summing up the score from the 8 metrics(and doubling the YBC value), we arrive at a final rating for each of the 32 offensive lines.  Like any rating system there are sure to be disagreements and niggles in the methodology. 

The Offensive Line Ratings see Baltimore, Philadelphia, Miami, & the LA Rams as the having the best offensive lines.   It sees Houston, Pittsburgh, Carolina, and the extremely woeful NY Giants as having the worst performing offensive lines thus far in 2023.

When it comes to luck in the NFL we can boil it down to two old addages:

• It’s better to be lucky than good.
• Good teams make their own luck.

So which is it?  Let’s try to use some statistics and metrics to see which NFL teams have been the luckiest and unluckiest, and see if there is an addage that fits the 2023 season.

To keep the reddit post as short as possible, the metrics methodology part has been cut out. If you are interested in the thought process and methodology behind the luck quotient, you can read the entire article here: In the NFL, it's better to be lucky than good. Or is it?

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NFL 2023 - Luck Quotient

The Luck Quotient

The Luck Quotient will be a measurement of how lucky or unlucky each NFL team has been thus far in 2023.  The one luck component I could not add was the effect of injuries.   Clearly it would be unlucky to lose your starting QB for the year, while remaining relatively injury free would be lucky for any team.

Unfortunately, I could not find a free source that listed all injuries by all teams in terms of man games lost.  I know the stats exist, but NFLLINES always limits statistics and metric to publicly availble stats.  If it were possible to add in the injuries metrics, we could do something where we assign value for starters, substitute and partial game injuries.  Unfortunately this will have to wait until such stats become available to all.

Luck Quotient metrics will either count for their full value, 1/2 their value, 1/4 of their value, or a flat 0.50 or 0.25 StDev units.  If you are interested in the how/why of the metrics, use the link above to read the full post. With that in mind, here is the list of metrics I chose for the Luck Quotient:

Full Value Metrics

• FG %
• Opponent Fumble Recovery %
• Interceptions thrown

Half Value Metrics

• Punt return avg
• Kick return average

0.50 StDev units per occurance

• Returned Fumble for TD
• Returned Interception for TD
• Recorded a Safety

Quarter Value Metric

• Extra Point %

0.25 StDev units per occurance

• Punt return TD
• Kick return TD

The Luckiest & Unluckiest  NFL Teams in 2023

After we total up the scores for each metric, we are left with the final Luck Quotient for each team.  The 3 luckiest teams are the only 3 teams that scored over 3.0: 

• Dallas(3.74)
• Houston(3.16)
• Tampa Bay(3.06)

Dallas scored 2.5 of their 3.74 luck points from defensive returns for TD and a safety.  Houston has no defensive scores and Tampa has a Interception return for TD.  If we eliminated luck points for defensive scores, Houston would be the luckiest team(3.16), followed by Tampa bay(2.56) and LA Chargers (2.46).

At the other end of the luck spectrum, the three unluckiest teams are the only 3 teams that scored lower than -2.0:

• New England(-3.67)
• Buffalo(-2.70)
• LA Rams(-2.28)

If we eliminated defensive scores, New England(-3.17) would still be the unluckiest, but the Rams(-2.28), would flip spots with the Bills (-2.20), and the Vikings(2 defensive scores) would drop & tie for 3rd unluckiest(-2.20).  Both the Patriots & Bills have 1 defensive score, while the Rams have zero.  So their unluckiness extends to their defensive scoring prowess as well.

One statistical oddity, note the Denver Broncos Punt and Kick return units.  Punt return avg of 20.7 yds and kick return avg of 33.6 yds with a TD.  Surely that kick return average is inflated due to the TD return, but the punt return average is also off the charts.  Gold Stars to the Denver kick/punt return unit and coach for their performance in 2023 so far.

The other unusual tidbit, Green Bay's opponents only recovering 18.75% of fumbles so far. The lowest value for that I could find since 2018 was the 2021 Arizona Cardinal's opponents recovered only 30.51% of fumbles & 2019 New Orleans Saints' opponents recovered only 30.77% of fumbles. The ball is bouncing the Packers way so far.

Is It Better To Be Lucky Than Good, Or Do Good Teams Make Their Own Luck?

The record for each team is listed in the final columns of the Luck Quotient chart.  And the answer at least for 2023 is pretty clear.

• The 8 Luckiest NFL teams in 2023 have a combined record of 36 – 36 (.500).
• The 8 Unluckiest NFL teams in 2023 have a combined record of 29 – 50 (.367).
• If we combine the 8 luckiest and 8 unluckiest teams, those 16 teams have a combined record of 65 – 86 (.4305).
• The 16 teams with average luck have a combined record of 86 – 65 (.5695).

Thus, good teams make their own luck, at least in 2023.

A few weeks ago I posted a new quarterback rating system called QB Score or QBS. Using the feedback from Reddit, here is QB Score v2.0 and a midseason grade for every NFL starter using QBS as the measuring stick. Note all stats/score are through 9 weeks and DO NOT include yesterday's games.

For the TLDR types: Just look at the charts and you should have enough ammunition to flame the idiot who wrote this nonsense. You will find QB Score, Passer Rating & QBR scores and ranks for each quarterback within. The following to links will take you to the full article about QB Score and Quarterback Grades.

QB Score Explained

NFL 2023 QB Midseason Grades

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NFL 2023 QB Scores (QBS) Through Week 9

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NF: 2023 QB Score & Midseason Grades

Why QB Score?

QB Score, QBS, is derived from comparing the stats of all quarterbacks to each other and then scoring each QB in 14 categories.  To do the scoring, QBS uses Standard Deviation units.  Essentially the better a QB is compared to all his fellow QBs in that metric, the higher the score he receives for that metric.

The argument for using QBS is pretty clear:

1. It is the most intuitive of the QB rating scales with an average of virtual zero and the smallest range.
2. QBS is the easiest QB rating metric to calculate
3. QBS is the only comparative QB rating system that takes into account the QB’s performance compared to their peers.
4. Quantifying the QBS score to a descriptive adjective on the QB play is simplest due the inherent ranges in its scoring system.

QB Score Metrics

Here is the process for calculating QBS.  All NFL QBs are scored in 11 statistics:

• Completion %
• Passing Yards / Game
• Intended Air Yards / Pass Attempt
• Completed Air Yards / Game
• Completed Air Yards / Pass Attempt
• Intended Air Yards/ Pass Attempt – Completed Air Yards / Pass Attempt (Inverse)
• On Target %
• Touchdown %
• Interception % (Inverse)
• 1st Down Success %
• Sack % (Inverse)
• Pressure % (Inverse)
• Rushing Yardage
• Rushing 1st Downs

You’ll notice that 4 statistics have (Inverse) next to them.  This simply means when calculating, a lower value is better.  It is better to have a low INT% and Sack% so the stat/score is inverted.  At the bottom of every metric you can see the average and the size of 1 unit SD range.  The 3 new QBS v2.0 metrics are in bold italics at the bottom of the list.

Upon the release of the first version of QBS, there was suggestion that it was not rewarding more mobile quarterbacks for their play extending, and play creating talents.  Essentially that QB Score was too focused on the actual throwing of the football as opposed to scoring the position of quarterback.  A good way to think of it is that QBS would measure and rate all of Tom Brady, but only 3/4 of Lamar Jackson.

This is a fair criticism and something that needed to be tweaked if QBS was going to rate quarterbacks, and not just the ability of quarterbacks to throw the ball.   However, it had to be limited.  Even in seasons when Lamar Jackson ran for 1000 yards, he was still passing for about 3000 yards and these are the most exteme cases of rushing yds vs passing yds for quarterbacks.  A fair estimate is probably more like 500 yards rushing per 3000 yards passing is the sign of a mobile qb. As a ratio this means about 1/7 (500/3500) of the QB’s production is rushing, 6/7(3000/3500) is passing.  1/7 translates into roughly 14.3%, and for extremely mobile quarterback it could range as high as 25%(Jackson in 2019 & 2020).

Thus the ability to rush and avoid pressure should count for about 15%-20% of a quarterbacks value.  There are now 2 out of 14 metrics strictly dedicated to a quarterbacks rushing ability, or 1/7.  Considering the Pressure % metric is intended to reward quarterbacks under pressure, it is also recognizing the value of a mobile quarterback.  Thus we come to that 15%-20% area.  Ideally, QB Score would be flexible and robust enough to identify the best all around quarterback of that year whether the qb was a statuesque Tom Brady, or a Tasmanian Devil like Lamar Jackson.

New Metrics in QB Score

Pressure % (Inverse)

The Pressure % metric has been added to balance out how much time each quarterback has had to produce their statistics.  This is an INVERSE metrics so QBs who are facing a high % of pressure will score higher, and quarterbacks facing minimal pressure will score lowest.

The logic for including this revolves around protection scheme and line play.  If a qb faces pressure a smaller % of the time, they should, all other things held equal, produce better statistics.  They are not being rushed, or running for the lives as much.  They are sitting in a clean pocket, scanning the field, and can step into throws.

Likewise, a quarterback that is under pressure a high % of the time is most likely having to make quicker reads, scramble, and work from dirtier pockets.  Again, all other things being equal, a qb facing a high % of pressure will typically produce worse stats than a qb facing a low % of pressure.

A modern mobile quarterback is going to be helped by this metric as they will be more capable of producing positive stats after being flushed.  They simply deal with pressure better than a statuesque type quarterback.

If a team wants to Max Protect a quarterback to mimizize pressure %, that is fine, but the quarterback will be expected to produce better stats when Max Protected then when not Max Protected.  Simply put, if a qb is not performing better with extra blockers, it would be better to send the blockers out as receivers.   Their value as extra protection is zero.

One of the reasons Tom Brady is Tom Brady is because he often faced a small % of pressure.  Take an exceptional qb, add in a bit more time in the pocket via more protection(which increases his production), and you end up with a GOAT.

And while I don’t think Zach Wilson is Tom Brady, I am not sure Zach Wilson is as bad as Zach Wilson IF Zach Wilson wasn’t facing an inordinately high amount of pressure.

Rushing Yardage

This one is as straightforward as it gets.  Quarterbacks who rush the ball effectively will score high in this metric.  Tom Brady will not.

This metric has nothing to do with throwing the football, but has something to do with playing modern QB in the NFL.  The only small issue with this metric is the large rushing yardage range between the best of the running QBs and the Pocket Passers.  But using StDev units, the damage of a single metric with an unusual range is always limited.

Rushing 1st Downs

This metric is a double barrel for rushing quarterbacks.   By choosing rushing 1st downs as a metric I also included rushing touchdowns.  How?  In the NFL every touchdown scored by rushing or passing, regardless of the distance covered, is awarded a first down Guide for NFL Statisticians.

For example, Jalen Hurts gets Tush Pushed from the 1 yard line in for a touchdown.  Hurts would get credit for 1 yard rushing, a rushing td, and a rushing 1st down.  So as you can see by using the rushing first down metric, we can give credit for qb rushing touchdowns without adding the extra metric.

Intended Air Yards – The Gunslinger Metric

Every metric you see above you may have seen before or know already with the exception of two: the metrics involving Intended Air Yards.  First, Intended Air Yards is simply the measure of how far the QB threw the ball on all attempts, whether complete, or incomplete.

For example, a QB attempts a 10 yard pass but it is incomplete.  Intended Air Yards is 10, but Completed Air Yards is zero.  If the pass was complete and the receiver ran for 6 yards after the catch: Intended Air Yards is 10, Completed Air Yards is 10, YAC is 6, and Passing Yards are 16.

I am calling this the Gunslinger metric, and here is why it is included.  Ideally you would love to have a QB willing, and able, to push the ball downfield.  So let’s reward the ones who do in QBS.  All other metrics being equal, we would love it if our QB threw for 9 intended air yards every attempt as opposed to 6, because all other things being equal(including completion %), we would move down the field faster.

But all other things are not equal…Completion % decreases as intended air yards increase(its harder to complete a longer pass than a shorter one in most cases).  The ball literally takes longer to travel 9 yards as opposed to 6 yards giving defense more time to react.  Most importantly, most NFL defenses are set up to minimize long pass completions in exchange for shorter ones.  So a gunslinger QB who is always trying to go deep needs to be kept in check in QBS by making sure they are not just flinging it willy nilly downfield.

The way this is done is with the second metric, (Intended Air Yards / PA – Completed Air Yards / PA), a metric I made up.  I call this metric, The Take What The Defense Is Giving You Metric.  This is how it works…By taking IAY/PA and subtracting CAY/PA we are seeing if the QB is trying to go deep too often.  Essentially, NOT taking what the defense gives them.

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NFL 2023 - QB Score Gunslinger Metric Chart

The Case for QB Score – QBS

For scoring, all we have to do is take the actual StDev value.  Do that for all 14 metrics, add them all up, and you get QB Score, or QBS.  The major difference being that, in QBS each QB is scored in each metric based on their performance AGAINST ALL OTHER QUARTERBACKS in that metric.  While it does matter what the quarterback did in the game on Sunday, it is also dependent on what all other QBs did on Sunday as well.

The second thing that makes QBS easier to understand and calculate, is that the average QBS score is literally 0.00 through 9 weeks.  That is pretty easy to remember compared to avg Passer Rating of 89.99 and an average 53.16 for QBR.  A quarterback with a positive QBS is performing above average, one with a negative QBS is performing below average.  Again pretty simple to use.

The third thing that makes QBS the better QB metric is that it has the smallest range of values.  The current range for QB is -10.80 to 11.07  Through Week 9, the current range for Passer Rating is 70.5 – 106.4, and the range for QBR is 32.3 to 75.3.  With QBS, using StDev of the QB Scores themselves, we can easily assign grades or performance buckets to the range.

The avg QB Score is 0.00, and the StDev is 6.73.

QB Score Interpretation

13.47+ = Exceptional6.74 – 13.46 = Good to Excellent0.00 – 6.73 = Slightly above average to Good0.00 – -6.73 = Slightly below average to Bad-6.74 – 13.46 = Bad to Horrible-13.47 or lower = WTF?!

QB Score is a lot easier and clearer than either Passer Rating or QBR when it comes to figuring out what the number translates into with regards to summarizing the QB’s performance.  The chart below will help crystalize it.

QB Score vs Passer Rating vs QBR

The chart shows QB Score, Passer Rating, & QBR scores and ranks for every quarterback.  The extra column shows how many SD above or below the average for the rating each QB happens to be.  We are converting Passer rating and QBR into quasi-QBS in order to compare them.  Thus trying to measure/compare them Apples to Apples to Apples.

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NFL 2023 - QB Score vs Passer Rating vs QBR

Converting Passer Rating & QBR Into Standard Deviation Units

QBS has a range of 1.65(Hurts) down to -1.60(Tannehill)

Passer Rating has a range for 1.61(Tagovailoa) down to -1.71(Tannehill)

QBR has a range of 1.64(J. Allen) down to -1.55(Z. Wilson)

Thus both Passer Rating and QBR show the same StDev range and characteristics as QBS.  However they are murkier and more confusing in both the calculation and interpretation.

Since we are only looking at half a year stats in 2023, I ran QB Scores for both 2022 and 2021.  I found it interesting that QBS has Tom Brady #1 for 2021, & Patrick Mahomes #1 for 2022.  You could not find two more opposite quarterbacks in the way they play the position, but QB Score allowed each to be the best in a given season.  This a sign of hope that QB Score could be a metric that allows comparison between typical pocket passers and modern mobile quarterbacks without being overally biased against either type.

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NFL 2022 QB Scores

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NFL 2021 QB Scores

Calculating Grades, Strengths & Weaknesses For Each Quarterback

Let's look at how grades, strength & weaknesses are identified statistically.  This is the little bit of math part but it is something you are already familar with if you ever had a teacher grade on the curve.

The unit of measure for QB Score is Standard Deviation units (StDev).  Very simply, StDev units measure how unusually good or bad a statistic is compared to the range it is in.  In mathematics:

• 68.26% of the data should fit within +/- 1 StDev unit
• 95.44% of a data range should fit within +/- 2 StDev units,
• 99.72 % within +/- 3 StDev units.

Remember the old Bell Curve that your teacher would use to adjust test scores?  The Bell Curve is simply a graphical representation of normal probability distribution.  That is a lot of mathematical jargon that boils down to the Bell Curve is showing Standard Deviation in picture form.  The greek letter sigma σ is the mathematical symbol for STDev Units.

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https://preview.redd.it/by2f4235e40c1.png?width=746&format=png&auto=webp&s=f125f97d416444f2e5805ba1247fd7701eadfe91

So it should make sense that a statistic that is close to +2.0 StDev is unusually high, while a statistic that measures -1.95 StDev is unusually low.  Normally any measurement that results in an StDev between +2 - +3 or -2 to -3 is so unusual compared to the other data, it is called an Outlier.   This just means that data point, or outlier, is worth investigating because being able to replicate positive outliers is like statistical gold.  Maybe even platinum when applying it to something like e-commerce or an NFL quarterback skill.

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Letter Grade Scale

A = 1.51+ StDev units

B = 0.51 thru 1.50 StDev

C = -0.50 thru -0.50

D = -1.50 thru -0.51

F = Below -1.51 StDev units

The grade scale simply uses the Overall QB Score StDev units for grading purposes.  A quarterback who's overall QB Score is 1.51 or more StDev above average will grade out an A. Remember, this is the overall score StDev units, not each particular metric's StDev units. 

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Strengths & Weaknesses Scale

For individual metrics, the following scale was used to categorize performance in the metric.  It is simply using the standard deviation ranges to quantify metric into a simple adjectives.

Real Strength = 1.01+

Strength = 0.00 thru 1.00

Weakness = 0.00 thru -1.00

Real Weakness = -1.01 or below 

You can see the value for each metric in the QB capsule. QB Score is COMPARATIVE.  This means all strengths & weaknesses are in comparison to all other quarterbacks in that statistic/metric.  Thus the scoring is essentially a Net Zero system.  For one QB to get +1.5 StDev score in a metric, another quarterback must score roughly -1.5 StDev to balance the range.

This is the huge difference between QB Score vs Passer Rating or QBR. QB Score measures the quarterbacks against each other, Passer Rating & QBR rate quarterbacks against a set standard.

Each quarterback is listed with all their metrics scores.  QB Score, Passer Rating & QBR are shown.  Each quarterback is assigned a letter grade for their overall score, and a list of strengths and weaknesses for each metric.  Remember, strengths & weaknesses are in comparison to other quarterback, essentially where they gained and lost points.

Strength & Weakness Symantics

If there is ever a metric listed as a strength or weakness that could be misleading, it is normally followed with an * and then a note at the bottom of the QB capsule explaining the possible confusion.  Simply apply the same note if you see the same potentially misleading metric in a similar spot further down.

For example, Pressure % listed as a Real Strength means the quarterback has been under the most pressure compared to all other quarterbacks, NOT that the quarterback is good at dealing with pressure.  It is there to indicate that the stats and score the quarterback have produced thus far have been under abnormally high pressure % compared to other QBs on the list.

Similarly, Pressure % listed as a Real Weakness DOES NOT mean the quarterback cannot deal with pressure.  Rather that they have produced their stats while facing far less pressure than their fellow quarterbacks thus far in 2023.

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A QB Score Quaterback Capsule

NFL 2023 - Jalen Hurts QB Score Capsule

Everything in QB Score is comparative. So the list of strengths and weaknesses define which metrics and stats Hurts is excelling in(gaining points), and suffering in(losing points) COMPARED TO THE OTHER 31 STARTING QUARTERBACKS. You can find all 32 grades in the article linked at the top of the post.

I hope everyone had an enjoyable day of football yesterday, and let's get ready for some football and a Monday night party.

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In this article, we are going to look into the influence referees and penalties have on a typical NFL game and season.  First, all the penalty data comes from nflpenalties.com.  If you would like to reveiw any of the data here, or data going back 10 years, you can do so on their site.

Let's break this article down into 2 parts:

• What influence do penalties have on the game?
• What penalties are being called this season in comparison to pervious seasons?

If you would like to read more about the penalty research issues & fixes, the full article is posted here:

NFL 2023 - Referees & Penalties Midseason Report

NFL 2023 Penalties by team

What influence do penalties have on an NFL Game?

First we should try to use the data to determine the amount penalties influence the outcome of NFL games.  To do that we are going to look at two charts:

• Win % by Penalty Calls Differential
• Win % by Penalty Yardage Differential

Let's start with Win % based on the difference of total penalties called against each team.  In the chart below you will see the penalty differnces , amount of  times a difference occured, team records, & Win %.

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Win % by Penalty Amount Difference

Look at the range from 8 Fewer to 8 More in the win % column.  You will see almost a direct relationship between penalty difference and Win %.  The less penalties called against a team, the higher its chances of winning.  Outside the 8 Fewer to 8  More range we get into smaller sample sizes, so we are going to see more chaos in the records & Win % numbers

How about the relationship between Penalty Yardage and Win %, will we see the same thing there?

We have many small ranges in this chart so we are going to see a bit of chaos, but again if you look from 60-64 Fewer to 60-64 More range, you will again see a strong correlation between Win % and penalty yardage differential.

Win % by Penalty Yardage Difference

Therefore, the amount penalties called against a team, and/or the more penalty yardage called against a team relative its opponent, can swing Win % about 10% in either direction.   Thus this +/- 10% influence is about the influence referees can have on any single game, assuming they dont go completely flag crazy against one team.

What penalties are being called this season in comparison to previous seasons?

The following chart will show NFL Penalties over the past 5 years broken down by quarter, offense, defense, ST, amount of penalties and penalty yardage.  As you can see, if we project out the 2023 penalties, we are headed for the most penalties called in a season since 2019, and the most penalties called on the defense since 2020.  So it is fair to say, based on the projections, that referees are having more of an influence in 2023 than they have had since at least 2020.

NFL Penalties 2019 - 2023

If they are calling more penalties, what kind of penalties are the calling more of & when are they calling them?

This is the sticky wicket.  Different penalties have different punishments.  All are punished by yardage, but some grant automatic first downs.  However,  automatic 1st down penalties are the drive changers.  When they are taking place late in a game, it is going to appear as though, and in fact it actually may be, a game that is unduly influenced by penalties.

Look a the amount of penalties called in the 4th quarter thus far in 2023(445).  This projects out to about 900 4th quarter penalties in 2023, which again would be the most in the 4th quarter since 2019.

The real damning information comes in form of the following charts. The first is Automatic First Down Passing Penalties FOR each team.  In this chart the team listed is the beneficiary of an automatic 1st down penalty via the 4 main types of defensive passing penalties: Defensive Holding, Defensive Pass Interference, Illegal Contact, & Roughing the Passer.

As we can see, Tennessee has benefitted the most and Chicago has benefitted the least.  And there is a large difference between teams that benefitted most vs teams that have benefitted least.

Automatic 1st Down Penalties FOR

Here is the same chart but now we are looking at automatic 1st penalties AGAINST each team

Automatic 1st Down Penalties AGAINST

Below is a chart showing NET automatic 1st down penalties by team(FOR - AGAINST).  It is sorted from team most punished to most helped.  Since all these penalties come with auto 1st down, the Total column shows the amount of free 1st downs a team has given away(negative#) or gained(positive #).

NFL 2023 NET automatic first down penalties

Now I am simply going to repost one chart with 2022 and extrapolated 2023 data. This should allow us to see changes in amount/type of calls between 2022 & 2023.

Automatic First Down Penalty Calls 2022 vs 2023

So in 2022, there were 610 of these types of penalties called against the defense for a total of 6529 yards.

In 2023, there are projected to be 695 types of these penalties called for a total of 7348 yards.

The changes:

• Total calls - up from 2.24 calls to 2.56 calls, an increase of 13.95%
• Defensive Holding calls - Down 10.87%
• Defensive Pass Interfence calls - Up 27.98%
• Illegal Contact calls - Up 26.30%
• Roughing the Passer calls - Up 27.82%

So while one of the 4 calls is showing a decrease of just under 11%, it is the least damaging penalty(along with Illegal Contact) among the four.  Meanwhile, the most damaging types of calls, Pass Interference & Roughing the Passer are both up nearly 28%(as is illegal contact).  Essentially all the referees have done is changed a few of the defensive holding calls into illegal contact calls.  While at the same time throwing a fairly massive increase of supremely damaging defensive penalties.

And if we simply combine this information, with the information about 4th quarter penalties being up, it means the referees are throwing more of the most damaging types of defensive passing penalties in 2023 than they have since at least 2020.  By doing this they are going to put there influence on games at the very edges of that +/- 10%, as opposed to having less influence over outcomes this year.

Enjoy your football Sunday & best of luck to your team. They may need it.

Trade deadline grades. One A, for a non trade, and one F, for a repeat offender. If you would like to read the entire post: NFL Trade Deadline Grades - Winners & Losers

TLDR:

Las Vegas Raiders Fire Head Coach McDaniel & GM Ziegler

Raiders – A +++

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Bills get CB Rasul Douglas from Green Bay in a swap of 3rd and 5th round picks

Green Bay – B+

Buffalo – B-

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Lions get WR Peoples-Jones from the Browns

Lions – C+

Browns – B

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49ers get Chase Young – Bears get Montez Sweat from the Commanders

49ers – B+

Commanders – B+

Bears – F

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Vikings get Joshua Dobbs from Cardinals for a bag of peanuts

Vikings – B

Cardinals – C-

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Seahawks get Leonard Williams from the Giants for 2nd & 5th round picks

Seattle – B

NYG – B

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Jaguars get OG Cleveland from the Vikings for a 6th round pick

Jags – B

Vikings – C

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Falcons get Kentavious Street from Eagles for 6th 7th round swap

Eagles – B

Falcons – C+

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So last Sunday we did grades for every NFL team through week 6. This Sunday, all 32 starting quarterbacks are rated using a new stat called QB Score, or QBS. What makes QBS different from QB Rating or QBR is that each quarterback's rating is dependent on how their statistics compare to their fellow QBs.

This is another grab your coffee and donut kind of deep dive read, so if you do not have time for it, below you will find a chart with QBS, QB Rating & QBR scores and ranks for all 32 starters.

The average score for QBS is essentially zero (-0.05). Thus positive scores are QBs providing positive play, and negative scores show QBs providing less than average play. The further from zero, the better, or worse, the QB play has been.

If you like this kind of stuff you can learn all about QBS, how it is calculated, and why it may be a more useful way of measuring qb performance here: QB Score - Ratings all 32 NFL quarterbacks comparatively.

After week 9, I will re-run all the data and use it to hand out midterm QB grades for every team. The data below ranks QBs through week 7 stats, so a little preview of what to expect.

Since this is a brand new metric, it is open for modification to fine tune it. Please feel free to offer comments, suggestions or criticisms on this thread and they will be taken into account for the QBS calculations done post week 9.

Best of luck to your team today and enjoy the football.

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QBS vs QB Rating vs QBR (Avg of QB Rating & QBR shown in last column)

For the deep dive this week, I put together a matrix using the Expected Points stats from Pro-football-reference.com for Week 8. The matrix looks at the EP for the Passing game for each team against the opposing teams' passing defense, and likewise for Rushing offenses vs rushing defenses. The first 2 columns show net Passing EP, the last 2 columns net Rushing EP.

The results should help forecast how much, and by which method, teams can move the ball against each other.

A = Away
H = Home
P = Passing
R = Rushing
D = Defense
O = Offense
ex. APO = Away Passing Offense

Full explanation about EP and the matrix using tonight's Thursday Night Game - Bucs @ Bills in the article: NFL Expected Points Matrix - Week 8

Enjoy the game tonight!

nfllines.com NFL Expected Points Matrix - Week 8

Without posting the full article here, the Bucs should have slightly above average success passing against the Bills. The Bills should have an easy time passing against the Bucs.

In the running game, the Bills should have around average production against the Bucs rushing defense. The Bills have a good rushing offense, but it is countered by an excellent Bucs rushing defense. Meanwhile the Bucs have real difficulty running the ball, and against an average Bills rushing defense, they probably cannot rely on rushing the ball to carry the night.

The Bills should hope for good passing weather as such conditions would allow them to play to their biggest advantage, passing against the Bucs defense. Since the Bucs haven't shown the ability to run the ball effectively, if the weather is good, look for a high % of passing from both teams.

If this holds true, this could be relatively high scoring from the Bills side of things. Something like Bills 31 Bucs 17 sounds about right.