It’s out there.  We’ve all heard it.  “The Saints offensive numbers look so good because they’re always falling behind and racking up yards and scores when the game has already been decided.  It’s all garbage time stats, nothing more.”  Or words to that effect.  But is it true?  Let’s run the numbers and put this myth to the test, MythBusters style.  (Buckle up, Buster, it’s crash test time.)

All data used in this analysis is courtesy of my goto site for football stats: pfref.com.

So, how to test this?  Well, my impression of “garbage time” would be when the game is out of reach on the scoreboard.  You’re down big and the other team is playing a soft defense, the goal being preventing the big plays over the top.  The opposite of this would be games where the scoreboard is tight.  If the Saints offense struggles in tight game situations, but then pours it on when down big, then the myth of the garbage time stats would be confirmed, but if the Saints offense is lighting it up even in tight games, then the myth is busted.  (The fact the Saints offense also does well when down big is irrelevant, IMO.  A stellar offense will do well in all game situations.)

This table shows the plays executed while the scoreboard differential is 7 or fewer points.  In other words, teams are either up by 7 or fewer points or down by 7 or fewer points; these are one score games.   Plays column is the number of plays that offense executed during these tight games.  ToGo is the average yardage to go for a 1st down (or in the case of goal to go, for a touchdown).  Yds is the average number of yards gained per play.  1st% is the percentage of plays that resulted in a 1st down (or touchdown), and TO% is the percentage of plays that resulted in a turnover.  TD is the total TD’s scored.  TD’s per 100 plays is self-explanatory.

Tm Plays ToGo Yds 1st% TO% TD TD’s per 100 plays
ATL 587 8.62 6.9 37.6% .9% 37 6.30
NWE 540 8.43 6.54 35.0% .2% 34 6.30
KAN 513 8.49 6.24 31.6% .4% 26 5.07
WAS 756 8.53 6.14 31.3% .9% 29 3.84
PIT 597 8.43 6.1 32.5% 1.5% 29 4.86
NOR 675 8.06 6.03 33.3% 1.2% 36 5.33
OAK 723 8.58 5.92 29.3% .8% 33 4.56
SEA 650 8.76 5.92 29.7% .3% 25 3.85
CHI 564 8.96 5.85 29.8% 1.4% 15 2.66
DAL 779 8.67 5.84 34.3% .6% 37 4.75
MIA 601 8.75 5.83 28.6% 1.3% 27 4.49
GNB 653 8.17 5.82 31.7% .3% 31 4.75
SDG 679 8.55 5.78 30.6% 2.5% 30 4.42
TEN 541 8.67 5.59 28.1% .7% 23 4.25
NYG 705 8.43 5.56 27.7% 1.8% 26 3.69
CIN 665 8.5 5.54 29.9% 1.1% 27 4.06
NYJ 622 8.54 5.47 27.3% 1.4% 20 3.22
ARI 688 8.59 5.36 28.6% 1.3% 25 3.63
IND 598 8.51 5.35 28.9% 1.5% 23 3.85
DET 772 8.62 5.35 30.1% .8% 27 3.50
BUF 627 8.77 5.34 29.2% .5% 24 3.83
DEN 582 8.4 5.29 26.5% .7% 21 3.61
CAR 562 8.73 5.23 28.8% 2.0% 21 3.74
MIN 573 8.61 5.22 28.3% .5% 18 3.14
CLE 533 9.22 5.1 26.3% .9% 13 2.44
TAM 726 9.01 5.05 28.2% 1.7% 24 3.31
BAL 731 8.84 5.01 26.5% 1.4% 18 2.46
JAX 649 8.63 4.73 24.5% 2.2% 17 2.62
SFO 511 8.73 4.72 27.0% 1.4% 17 3.33
PHI 698 8.51 4.69 28.4% 1.1% 17 2.44
LAR 658 8.57 4.67 24.3% 2.1% 17 2.58
HOU 737 8.32 4.56 25.1% 1.4% 17 2.31

ATL had the top offense in terms of yards per play when the score was within 7 points one way or the other.  (They did struggle when up by 25, but that’s neither here nor there.)  The Saints were 6th best in yards per play in these tight game situations.  If we sort by TD’s per 100 plays, the Saints were 3rd best.  Sort by 1st down percentage, and the Saints are 3rd best.  This *is* a legitimate top 10 offense.  Enough with the garbage about garbage time stats.

NFL yards per play 2016 tight games (plus or minus 7 on the scoreboard)

The NFL has long had their passer rating metric, which has come under criticism from some quarters in recent years.  The passer rating, of course, is a number we can use to compare quarterbacks to one another.  It takes into account completions, attempts, yardage, touchdowns, and interceptions.  The formula is a little bit complicated, but it’s fairly straight forward to implement in a spreadsheet or (as I have done in the past) in javascript.  I won’t go into the details of the formula hear, but if you want to know the nitty gritty details, there’s a nice article on it on wikipedia.

The passer rating metric is far from perfect, but I think it’s a terrific resource, despite it’s flaws.  Let’s consider some of the flaws: 1) It doesn’t take into account when a quarterback runs for a 1st down; 2) It doesn’t take into account when the quarterback takes a sack instead of throwing the ball away (in fact, throwing the ball away would actually hurt the passer rating while taking a sack would not); 3) It doesn’t take into account when the quarterback fumbles the ball; 4) It doesn’t take into account yards after the catch (for example, the quarterback might make a little 5 yard pass and the receiver breaks 7 tackles on the way to an 80 yard touchdown); and 5) One might reasonably quibble with the formula and the weight it gives to the various factors it does take into consideration (for example, is completion percentage more important than TD:INT ratios, and if so, or if not, what should the relative weighting be?).  This is just to name a few criticisms right off the top of my formerly fully haired head.

But the real question for me is, does this passer rating metric correlate to wins and losses?  It’s all well and good for a quarterback to have a high passer rating, but if his record as a starter is 1-10, that’s not good.  And vice versa for the quarterback who doesn’t have a great passer rating, and yet he finds a way to win the games.

Passer ratings work both ways.  You can have an offensive passer rating (your quarterback) and a defensive passer rating (cumulative passer rating of all of your opponents’ quarterbacks).  That latter defensive passer rating (in my humble opinion) is one of the more underrated stats that often goes ignored.  Typically when one of the talking heads says this is the “top rated defense” or the “best defense” in the league he’s referring to that total yardage allowed stat.  Remember 2009?  That was the year the New Orleans Football Saints won the Superbowl.  Going into that Superbowl game a lot of media experts pointed to that 25th ranking the Saints defense had in total yardage, but they ignored the #3 ranking they had in opponent passer rating.  They said the Saints had been “lucky” with all the turnovers they’d been getting that year, but the luck would run out against the living legend, Peyton Manning.  (See my twitter background pic featuring Tracy Porter celebrating his pick 6 with Manning propped up on one elbow watching.)  The Saints that year allowed 15 passing TD’s while collecting 26 INT’s.  But enough reminiscing…

So, what I’ve done is come up with what I’m calling a “net passer rating”.  This is simple enough.  It’s your team’s offensive passer rating minus its opponents’ cumulative passer rating in those games they played against your team.  In other words it’s passer rating – opp. passer rating.  Here is a table of results for the 2016 season, sorted by net passer rating:

Team net passer rating winning percentage passer rating opponent passer rating
New England Patriots 25.1 0.875 109.5 84.4
Atlanta Falcons 24.3 0.688 116.8 92.5
Minnesota Vikings 14.7 0.5 97.7 83
Denver Broncos 14.2 0.563 83.9 69.7
Kansas City Chiefs 13.4 0.75 93.2 79.8
New York Giants 10.2 0.688 86 75.8
Dallas Cowboys 8.9 0.813 103 94.1
Cincinnati Bengals 8.7 0.406 91.8 83.1
Seattle Seahawks 8.4 0.656 93.4 85
Miami Dolphins 7 0.625 95.5 88.5
Pittsburgh Steelers 6.6 0.688 93.9 87.3
Green Bay Packers 6.4 0.625 102.3 95.9
Washington Redskins 6.3 0.531 97.4 91.1
Oakland Raiders 5.5 0.75 95.3 89.8
Tennessee Titans 5.4 0.563 93.7 88.3
New Orleans Saints 4.4 0.438 102.5 98.1
San Diego Chargers 3.8 0.313 87.6 83.8
Buffalo Bills 0.8 0.438 86.7 85.9
Arizona Cardinals -1.6 0.469 83.5 85.1
Tampa Bay Buccaneers -1.8 0.563 87 88.8
Indianapolis Colts -3 0.5 94.5 97.5
Baltimore Ravens -4.3 0.5 82.6 86.9
Philadelphia Eagles -6.5 0.438 79.2 85.7
Jacksonville Jaguars -9 0.188 79.5 88.5
Houston Texans -11 0.563 73.3 84.3
Chicago Bears -11.7 0.188 81.8 93.5
Detroit Lions -13.2 0.563 93.3 106.5
San Francisco 49ers -13.5 0.125 83.4 96.9
Carolina Panthers -16.9 0.375 75.1 92
Cleveland Browns -24.4 0.063 77.4 101.8
Los Angeles Rams -26 0.25 69.5 95.5
New York Jets -30.9 0.313 67.6 98.5

You will notice the top 2 teams were the 2 teams in the Superbowl last year and the bottom few teams were the Jets, Rams, and Browns.  Need I say more?  Probably, but you know I will.

There were 18 teams with a positive net passer rating, and only 4 of the 18 had a losing record.  Of the 14 teams with a negative net passer rating only 3 had a winning record.  In other words, about 78.13% of the time the net passer rating directly correlates to the team’s record (positive net passer rating = winning record, negative net passer rating = losing record).  In the following chart you can see how net passer rating correlates to wins over .500 (or under .500):

NFL net passer rating chart

If the blue line is above zero it means a positive net passer rating.  The orange represents the number of wins (relative to 8 wins) the team had.  So, if the orange is below zero it means the team had fewer than 8 wins.

In summary, the net passer rating strongly correlates to winning and losing, but there are certainly other factors.  For example, the running game, fumbles, special teams, etc.  The Saints were one of the four teams with a positive net passer rating and yet a losing record.  You will no doubt recall 3 blocked kicks that were run back for scores (actually, one was stopped short of the end zone, but the opponent ended up deep in Saints territory and scored either on the next play or the one after that).  There were some fumbles that were returned for scores, too, as I recall (try as a might to forget).  And there were a few, let’s just say, “borderline” calls by the officials, many of which went against the Saints.  No excuses, though.  You have to be good enough to overcome those things, and the Saints, frankly, weren’t.  But hope springs eternal, and the Saints will rebound in 2017.  Believe dat!

The Saints have had good luck with undrafted rookie free agents (UDFA’s) in recent years, guys like Lance Moore, Pierre Thomas, Chris Ivory, Khiry Robinson, Junior Galette, Jonathan Casilias, JoLonn Dunbar, and Willie Snead, just to name a few.  So, the Saints have clearly done well with UDFA’s, but how do they compare with the rest of the league?  That’s the question I decided to tackle in this study.

As usual, all data is from my goto site for NFL stats: pfref.com.   It’s a terrific reference site for doing stuff like I do on this blog.  I’m discovering new stuff all the time on there.  All data is from 2006-2016 seasons.

What I did was query the database for player seasons in which an undrafted player had pfref’s AV metric of 6 or more for that season.  I then copied the information into a spreasheet, taking these player seasons, sorting them by team name, and then secondarily by AV score for that season.  Thus, it is possible for some players to appear multiple times in the list, since this is being done by the season.  Also note, it doesn’t matter if the player is on the team that “discovered” him or if he moved there in free agency, via trade, or whatever.  I would like to have only looked at the players on their original team, but there was no easy way to sort them as such.  Plus, it often happens the team that discovered the player really didn’t know what they had at the time, so it’s usually appropriate to credit the team that finally did get the most out of the player anyway.

Without further ado, here is the table of results I came up with, sorted by AV SUM:

Team # UDFA’s AV Sum AVERAGE
NE 36 330 9.17
SD 35 302 8.63
SEA 32 252 7.88
PIT 28 249 8.89
IND 30 247 8.23
PHI 26 228 8.77
NO 28 211 7.54
DAL 20 204 10.20
NYG 22 195 8.86
DEN 21 173 8.24
TB 23 168 7.30
MIA 17 159 9.35
CIN 21 158 7.52
WAS 19 154 8.11
KC 22 153 6.95
ARI 19 153 8.05
ATL 17 141 8.29
CLE 20 140 7.00
BUF 18 140 7.78
CAR 19 136 7.16
GB 16 132 8.25
NYJ 16 131 8.19
TEN 19 130 6.84
RAMS 18 124 6.89
CHI 15 111 7.40
MIN 13 103 7.92
OAK 14 100 7.14
HOU 10 94 9.40
DET 10 81 8.10
SF 10 71 7.10
JAX 9 68 7.56

If you’re not familiar with the AV metric that pfref.com has come up with, check out their site and look at their glossary for a better description than the one I will briefly give here.  Essentially, the AV score is the “approximate value” that the player had that year, the higher the better.  The number is something you can compare among different position groups, e.g. a tight end to a defensive tackle, or whatever.  The top AV score in this group of 643 players was Arian Foster’s score of 20 for his 2010 season in Houston.   The average AV was 8.08 for this group, bearing in mind it only includes those with 6+ AV scores in a season between 2006 and 2016.

The Saints came out all right, scoring 7th place with an AV SUM (the sum of all player season AV numbers) of 211.  The Saints had 28 player seasons, tying them for 5th best with Pittsburgh.  New England was tops with 36 player seasons and 330 AV SUM.  And since these charts seem to be popular:

undrafted AV sums 2006-2016

 

Everybody is always saying how the Saints love to pass the football, so I decided to see if the stats bear that out.  How does the Saints’ play selection compare with the rest of the league?  That’s the question this study attempts to answer.

Game situations do dictate play selection.  If you’re down on the scoreboard you need to pass to try to catch up.  If you’re up on the scoreboard you need to run to try to drain the clock.  But if you’re still passing more than average even when you’re up on the scoreboard, you’ve got a pass happy offense.

The following table is based on stats pulled from pfref.com for the 2016 season.  I filtered out all plays that were punts or field goals or kickoffs.  I only wanted plays that were run on 1st, 2nd, 3rd, or 4th down and that were either runs or passes.  I didn’t care about down and distance, only thing I cared about was the scoring margin at the time the play was executed.  I looked at even scores, down by 3, up by 3, down by 7, up by 7, down by 10, up by 10, down by 14 or more, and up by 14 or more.  In all but one case, the Saints had a higher percentage of passing plays.

score margin NFL pass % Saints pass %
even score 56.40% 61.79%
down by 3 62.20% 65.15%
up by 3 54.40% 64.71%
down by 7 60.00% 62.58%
up by 7 53.80% 61.25%
down by 10 65.50% 67.90%
up by 10 52.10% 60.00%
down by 14 or more 72.90% 68.97%
up by 14 or more 44.20% 46.37%

And, a picture being worth a thousand words, here’s a handy dandy chart:

saints-pass-happy-offense-2016

Data based on research done at pfref.com.

In this blog post we’re going to play a little game.  I’ll give you the down and distance, for example, 2nd and 4, and you guess whether this is a running down or a passing down.  The answer will be based upon whether there were more running plays or passing plays in that situation in the NFL in the 2016 regular season.  Don’t bother posting your answers, although comments are always welcome.  I’ll give the answers at the bottom of the post.  As usual, all data is from my goto site for NFL stats, pfref.com.

Is it a running down or a passing down?

  1. 1st and 5
  2. 1st and 10
  3. 1st and 15
  4. 2nd and 1
  5. 2nd and 5
  6. 2nd and 10
  7. 3rd and 1
  8. 3rd and 5
  9. 3rd and 10
  10. 3rd and 15+

Jot down your answers and test your football IQ.  (Note on question #10, it’s 3rd and 15+, meaning it could be 3rd and 15, 3rd and 16, 3rd and 29, whatever.)  I’ll give the answers below.  I took the quiz myself before looking up the answers.  These are my answers.

(My guesses, not the real answers.  Yet.)

  1. RUN
  2. PASS
  3. PASS
  4. RUN
  5. RUN
  6. PASS
  7. RUN
  8. PASS
  9. PASS
  10. RUN

Now we get to the real answers.

  1. 1st and 5.  RUN.  Teams ran the ball on 1st and 5 (131 runs, 79 passes).
  2. 1st and 10.  PASS.  Teams passed the ball on 1st and 10 (6592 passes, 6521 runs).
  3. 1st and 15.  PASS.  On 1st and 15 there were 151 passes and 98 runs.
  4. 2nd and 1.  RUN.  On 2nd and 1 teams overwhelmingly ran the ball: 418 runs, 184 passes.
  5. 2nd and 5.  PASS.  (My first wrong guess.)  Teams passed only slightly more than they ran on 2nd and 5: 418 passes to 407 runs.
  6. 2nd and 10.  PASS.  Teams tended to pass on 2nd and 10: 1556 passes, 952 runs.
  7. 3rd and 1.  RUN.  208 passes, 511 runs.
  8. 3rd and 5.  PASS.  521 passes, 46 runs.
  9. 3rd and 10.  PASS: 579 passes, 50 runs.
  10. 3rd and 15+.  PASS: 492 passes, 112 runs.  (My 2nd wrong guess.)  I fooled myself into thinking of times when teams basically give up on getting the first down and run a draw play on 3rd and very long.

My score was 8/10 = 80%.  How well did you do?  Probably better than I did for most of you would be my guess.  Well, that was fun for me.  Hope you had fun with it, too.  I might do some more of these quizzes in the future.

In this little study I looked at the Saints’ record between 2006-2016, which is when Sean Payton and Drew Brees arrived on the scene, breaking that record down by pass attempts in the games.  All data, as usual, is from pfref.com.

pass attempts wins losses ties percentage
60 or more 0 1 0 .000
55 or more 1 4 0 .200
50 or more 3 12 0 .200
40 to 49 31 44 0 .413
30 to 39 56 14 0 .800
35 to 39 33 13 0 .717
30 to 34 23 1 0 .958
29 or less 11 5 0 .688

So, if you’re a Saints fan you want to see the Saints attempting between 30 and 39 passes, preferably on the lower end of that scale, between 30 and 34.  That’s when they’re at their best.  Brees’ career average yards per attempt is about 7.5.  Doing a little bit of math, then, we’re looking at between 30 * 7.5 = 225 and 34 * 7.5 = 255 yards per game as the optimal stats when it comes to winning games.  At the outside, 39 * 7.5 = 292.5 yards per game would be the upper limit of what you really want to see.  A season of between 3,600 and 4,000 passing yards would really be ideal, 4,700 yards tops.  As much as I’m sure we all like to see Brees pump out those 5,000+ yard seasons, the reality is, it’s just not a winning formula for the Saints.

The focus for the Saints, if they want to get back to winning games, is a renewed emphasis on the running game.  What does it take to be a good running team?  Good running backs and a good offensive line (and a coach who will call the running plays).  Sometimes (most times) this is easier said than done, when it comes to calling running plays.  Obviously, game situations will usually dictate game strategy.  If you’re up by 2 touchdowns it’s easier to call running plays than when you’re down by 2 touchdowns.  So, defense also plays into this, too.  Plus, running the ball effectively is a huge boon to your defense since it shortens the game and limits the number of possessions they have to go out and defend.

The bottom line, let’s reign in this pass happy offense and get more balance with the run-pass mixture and get back to winning games.  The records can wait.  It’s the record that really matters.

Using data from my go to site for stats: pfref.com, I compiled a list of stats for the top 10 (non-active) running backs in NFL history (according to career rushing yardage).  I included just a couple items in the chart below: 1) career rushing attempts coming into the season; and 2) the yards-per-carry average for that season.  The running backs included in this is a  who’s who of running backs: Emmitt Smith, Walter Payton, Barry Sanders, Curtis Martin, LaDainian Tomlinson, Jerome Bettis, Eric Dickerson, Tony Dorsett, Jim Brown, and Marshall Faulk.

Top 10 NFL RB's (career rushing yards) averages yards-per-carry each season

The x-axis gives the total number of carries the player had coming into the season. The y-axis gives his yards-per-carry average in that season.

In the above chart the x-axis along the bottom from left to right gives us the total career carries the player had coming into that season.  So, every player came into his first season with 0 career carries, which is why  that first column of data is all in perfect alignment on the far left of the chart.  The y-axis, up and down from bottom to top is the yards-per-carry average the player had for that season.  No attempt has been made to distinguish one player from the other since what we’re after here is not which player was better, but rather how the number of career carries the player has already had affects his efficiency going forward in his career.

There are a few things that really stand out to me when looking at this chart.  The first is how you will notice none of these great players averaged 5+ yards per carry after hitting that 2,500 career carry milestone, and really only one of the ten was able to do this after about 2,100 career carries (2,070 carries, Jim Brown, 1965), and that was Barry Sanders who averaged 6.1 per carry at 2,384 career carries coming into the 1997 season.  So, basically, only one of these guys was able to average better than 5.0 per carry after racking up 2,100+ carries coming into the season.

Another thing to notice is after the 3,000 career carry mark, only one of these guys came anywhere close to having a 5.0 yards-per-carry average.  The rest were all basically in the very low 4’s or between 3.0 and 4.0 per carry.  After 3,500 carries only one player was able to break 4.0 yards-per-carry.

Keep in mind, these are all elite players in this list.  You see a lot of 5.0 to 6.0 averages early in their careers (prior to the 2,100 or so rushing attempts number), and even a few 6.0+ years in there.

I’m going to say we start seeing the first dropoff at around 2,100 career carries.  That’s when those 5.0+ average seasons all dry up (with one exception as mentioned above).   The next dropoff is at about 3,000 carries, after which you’re not seeing those high 4’s in the averages anymore.   After around 3,400 carries it becomes increasingly difficult even to hit that 4.0 YPC number.

The Saints just recently signed (this offseason at the time of this writing) Adrian Peterson, who is truly one of the best running backs ever to play the game.  I’ll take AD in his prime over anybody else on this list.  Seriously.  But that’s AD in his prime, not the 2017 incarnation.  He’s coming into the season with 2,418 career carries under his belt.  If he breaks 5.0 yards per carry this year he’ll do something none of these 10 greatest ever running backs were ever able to do.

For sake of completeness, here is the spreadsheet data the above chart was based on:

Emmitt Smith
Career Rushes Rushing Rushing Rushing
Year Age Tm coming into year Rush Yds Y/A AV
1990* 21 DAL 0 241 937 3.9 8
1991* 22 DAL 241 365 1563 4.3 17
1992*+ 23 DAL 606 373 1713 4.6 20
1993*+ 24 DAL 979 283 1486 5.3 20
1994*+ 25 DAL 1262 368 1484 4 17
1995*+ 26 DAL 1630 377 1773 4.7 20
1996 27 DAL 2007 327 1204 3.7 10
1997 28 DAL 2334 261 1074 4.1 9
1998* 29 DAL 2595 319 1332 4.2 12
1999* 30 DAL 2914 329 1397 4.2 11
2000 31 DAL 3243 294 1203 4.1 9
2001 32 DAL 3537 261 1021 3.9 6
2002 33 DAL 3798 254 975 3.8 4
2003 34 ARI 4052 90 256 2.8 2
2004 35 ARI 4142 267 937 3.5 5
Career Career 4409 4409 18355 4.2 170
13 yrs 13 yrs DAL 4052 17162 4.2 163
2 yrs 2 yrs ARI 357 1193 3.3 7
Walter Payton
Career Rushes Rushing Rushing Rushing
Year Age Tm coming into year Rush Yds Y/A AV
1975 21 CHI 0 196 679 3.5 6
1976*+ 22 CHI 196 311 1390 4.5 14
1977*+ 23 CHI 507 339 1852 5.5 20
1978* 24 CHI 846 333 1395 4.2 15
1979* 25 CHI 1179 369 1610 4.4 15
1980*+ 26 CHI 1548 317 1460 4.6 15
1981 27 CHI 1865 339 1222 3.6 8
1982 28 CHI 2204 148 596 4 10
1983* 29 CHI 2352 314 1421 4.5 13
1984*+ 30 CHI 2666 381 1684 4.4 16
1985*+ 31 CHI 3047 324 1551 4.8 18
1986* 32 CHI 3371 321 1333 4.2 12
1987 33 CHI 3692 146 533 3.7 6
Career Career 3838 3838 16726 4.4 168
Barry Sanders
Career Rushes Rushing Rushing Rushing
Year Age Tm coming into year Rush Yds Y/A AV
1989*+ 21 DET 0 280 1470 5.3 13
1990*+ 22 DET 280 255 1304 5.1 17
1991*+ 23 DET 535 342 1548 4.5 16
1992* 24 DET 877 312 1352 4.3 12
1993* 25 DET 1189 243 1115 4.6 10
1994*+ 26 DET 1432 331 1883 5.7 20
1995*+ 27 DET 1763 314 1500 4.8 16
1996* 28 DET 2077 307 1553 5.1 14
1997*+ 29 DET 2384 335 2053 6.1 19
1998* 30 DET 2719 343 1491 4.3 13
Career Career 3062 3062 15269 5 150
Curtis Martin
Career Rushes Rushing Rushing Rushing
Year Age Tm coming into year Rush Yds Y/A AV
1995* 22 NWE 0 368 1487 4 10
1996* 23 NWE 368 316 1152 3.6 13
1997 24 NWE 684 274 1160 4.2 13
1998* 25 NYJ 958 369 1287 3.5 13
1999 26 NYJ 1327 367 1464 4 14
2000 27 NYJ 1694 316 1204 3.8 10
2001* 28 NYJ 2010 333 1513 4.5 15
2002 29 NYJ 2343 261 1094 4.2 12
2003 30 NYJ 2604 323 1308 4 11
2004*+ 31 NYJ 2927 371 1697 4.6 14
2005 32 NYJ 3298 220 735 3.3 4
Career Career 3518 3518 14101 4 129
8 yrs 8 yrs NYJ 2560 10302 4 93
3 yrs 3 yrs NWE 958 3799 4 36
LaDainian Tomlinson
Career Rushes Rushing Rushing Rushing
Year Age Tm coming into year Rush Yds Y/A AV
2001 22 SDG 0 339 1236 3.6 10
2002* 23 SDG 339 372 1683 4.5 15
2003 24 SDG 711 313 1645 5.3 19
2004*+ 25 SDG 1024 339 1335 3.9 18
2005* 26 SDG 1363 339 1462 4.3 18
2006*+ 27 SDG 1702 348 1815 5.2 26
2007*+ 28 SDG 2050 315 1474 4.7 18
2008 29 SDG 2365 292 1110 3.8 13
2009 30 SDG 2657 223 730 3.3 7
2010 31 NYJ 2880 219 914 4.2 8
2011 32 NYJ 3099 75 280 3.7 5
Career Career 3174 3174 13684 4.3 157
9 yrs 9 yrs SDG 2880 12490 4.3 144
2 yrs 2 yrs NYJ 294 1194 4.1 13
Jerome Bettis
Career Rushes Rushing Rushing Rushing
Year Age Tm coming into year Rush Yds Y/A AV
1993*+ 21 RAM 0 294 1429 4.9 12
1994* 22 RAM 294 319 1025 3.2 8
1995 23 STL 613 183 637 3.5 4
1996*+ 24 PIT 796 320 1431 4.5 11
1997* 25 PIT 1116 375 1665 4.4 15
1998 26 PIT 1491 316 1185 3.8 6
1999 27 PIT 1807 299 1091 3.6 9
2000 28 PIT 2106 355 1341 3.8 10
2001* 29 PIT 2461 225 1072 4.8 8
2002 30 PIT 2686 187 666 3.6 5
2003 31 PIT 2873 246 811 3.3 4
2004* 32 PIT 3119 250 941 3.8 7
2005 33 PIT 3369 110 368 3.3 3
Career Career 3479 3479 13662 3.9 102
10 yrs 10 yrs PIT 2683 10571 3.9 78
3 yrs 3 yrs RAM-STL 796 3091 3.9 24
Eric Dickerson
Career Rushes Rushing Rushing Rushing
Year Age Tm coming into year Rush Yds Y/A AV
1983*+ 23 RAM 0 390 1808 4.6 15
1984*+ 24 RAM 390 379 2105 5.6 17
1985 25 RAM 769 292 1234 4.2 9
1986*+ 26 RAM 1061 404 1821 4.5 13
1987*+ 27 2TM 1465 283 1288 4.6 11
*+ RAM 1748 60 277 4.6 2
*+ IND 1808 223 1011 4.5 9
1988*+ 28 IND 2031 388 1659 4.3 19
1989* 29 IND 2419 314 1311 4.2 10
1990 30 IND 2733 166 677 4.1 6
1991 31 IND 2899 167 536 3.2 4
1992 32 RAI 3066 187 729 3.9 5
1993 33 ATL 3253 26 91 3.5 1
Career Career 3279 2996 13259 4.4 110
5 yrs 5 yrs IND 1258 5194 4.1 48
5 yrs 5 yrs RAM 1525 7245 4.8 56
1 yr 1 yr ATL 26 91 3.5 1
1 yr 1 yr RAI 187 729 3.9 5
Tony Dorsett
Career Rushes Rushing Rushing Rushing
Year Age Tm coming into year Rush Yds Y/A AV
1977 23 DAL 0 208 1007 4.8 16
1978* 24 DAL 208 290 1325 4.6 17
1979 25 DAL 498 250 1107 4.4 12
1980 26 DAL 748 278 1185 4.3 13
1981*+ 27 DAL 1026 342 1646 4.8 14
1982* 28 DAL 1368 177 745 4.2 14
1983* 29 DAL 1545 289 1321 4.6 13
1984 30 DAL 1834 302 1189 3.9 9
1985 31 DAL 2136 305 1307 4.3 12
1986 32 DAL 2441 184 748 4.1 7
1987 33 DAL 2625 130 456 3.5 5
1988 34 DEN 2755 181 703 3.9 6
Career Career 2936 2936 12739 4.3 138
11 yrs 11 yrs DAL 2755 12036 4.4 132
1 yr 1 yr DEN 181 703 3.9 6
Jim Brown
Career Rushes Rushing Rushing Rushing
Year Age Tm coming into year Rush Yds Y/A AV
1957*+ 21 CLE 0 202 942 4.7
1958*+ 22 CLE 202 257 1527 5.9
1959*+ 23 CLE 459 290 1329 4.6
1960*+ 24 CLE 749 215 1257 5.8 21
1961*+ 25 CLE 964 305 1408 4.6 19
1962* 26 CLE 1269 230 996 4.3 16
1963*+ 27 CLE 1499 291 1863 6.4 22
1964*+ 28 CLE 1790 280 1446 5.2 23
1965*+ 29 CLE 2070 289 1544 5.3 21
Career Career 2359 2359 12312 5.2 122
Marshall Faulk
Career Rushes Rushing Rushing Rushing
Year Age Tm coming into year Rush Yds Y/A AV
1994* 21 IND 0 314 1282 4.1 16
1995* 22 IND 314 289 1078 3.7 13
1996 23 IND 603 198 587 3 9
1997 24 IND 801 264 1054 4 12
1998* 25 IND 1065 324 1319 4.1 18
1999*+ 26 STL 1389 253 1381 5.5 25
2000*+ 27 STL 1642 253 1359 5.4 22
2001*+ 28 STL 1895 260 1382 5.3 22
2002* 29 STL 2155 212 953 4.5 9
2003 30 STL 2367 209 818 3.9 9
2004 31 STL 2576 195 774 4 7
2005 32 STL 2771 65 292 4.5 4
Career Career 2836 2836 12279 4.3 166
7 yrs 7 yrs STL 1447 6959 4.8 98
5 yrs 5 yrs IND 1389 5320 3.8 68
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