FOF 2007 - More 20-Year Career Musings

[CraigSca]

While Skydog looked at talent levels as a whole (and also brought up the fact that some players seem to be retiring a bit too early), I thought I'd quick-sim 20 years and see how the leaderboards are doing to see if there's a need for any tweaking.

For the test, I used the default player file that came with the game. I probably should have used a completely random start, but I was about 10 years into my quick-simming when I thought about doing it that way. Hopefully, there are no statistical anomalies because I chose this method.

Initially, I wanted to check attempts leader boards for rushing and passing to see if, indeed, players were retiring too early - especially runningbacks as they are now aging much quicker than they were in 2004. I compared the 20-year career with the lifetime NFL records and here's what I came up with.

Quarterbacks

Front Office Football 2007
Passing Statistics
 
  Player              Pos Strt End  GP  GS  Att  Cmp  Pct   Yards Avg/C Avg/A Lg  
Leinart, Matt         QB  2006 2022 270 270 9642 5836 60.5  71064 12.18 7.37  92    
$$Cochrane, Fernando  QB  2009 2025 257 256 8937 5644 63.2  64771 11.48 7.25  88    
Cutler, Jay           QB  2006 2022 254 251 8040 5168 64.3  57090 11.05 7.10  96    
Garner, Vince         QB  2007 2022 238 234 8004 4634 57.9  53550 11.56 6.69  91    
$$Knight, Marvin      QB  2010 2025 224 217 8024 4605 57.4  52603 11.42 6.56  90    
Palmer, Carson        QB  2006 2017 186 186 6775 4115 60.7  50929 12.38 7.52  96    
Young, Vince          QB  2006 2020 224 224 7435 4743 63.8  47754 10.07 6.42  95    
Manning, Eli          QB  2006 2018 195 195 6392 3862 60.4  45707 11.84 7.15  83    
$$Kitchen, Howard     QB  2012 2025 216 212 6652 4054 60.9  45646 11.26 6.86  80    
Rodgers, Aaron        QB  2006 2019 196 191 7006 4296 61.3  45604 10.62 6.51  80 

In real life, Dan Marino is the all-time leader with 61,361 yards. Having 2 guys above that number is no big deal. Notice how Matt Leinart had 9642 attempts in his career - Marino tops the real list with 8358 and he's the only guy in NFL history to top 8000. In the career, I have 5 guys who threw that much. Overall, I'm happy with quarterbacks - they may start too many games, but again I think it's a happy medium between COMPLETELY realistic injuries and settings that make the game playable. Btw, notice the lengths of the careers. I don't think QBs are retiring too early.

EDIT: Forgot to state - using all defaults in this league, including default injuries.

[CraigSca]

Now let's take a look at runningbacks:

Front Office Football 2007
Rushing Statistics
   
  Player              Pos Strt End  GP  GS  Att  Yards Avg   Lg  TD   RZAtt Yards  
$$Allen, Nolan        RB  2016 2025 148 148 2924 11872 4.06  55  74   463   1209    
$$Tharp, Marshall     RB  2016 2025 155 154 2887 11411 3.95  76  53   343   865     
Cameron, Korey        RB  2014 2023 160 159 2816 11038 3.92  63  69   408   1209    
Benton, Gino          RB  2009 2018 148 148 2552 10867 4.26  80  81   390   1033    
Compton, Neil         RB  2009 2018 160 158 2788 10843 3.89  44  67   451   1205    
Coleman, R.J.         RB  2008 2018 176 173 2708 10667 3.94  80  78   427   1114    
Williams, DeAngelo    RB  2006 2015 159 157 2713 10602 3.91  62  69   346   827     
Upshaw, O.J.          RB  2008 2018 173 124 2426 10486 4.32  88  98   365   984     
Collier, Zack         RB  2011 2021 167 148 2695 10473 3.89  56  56   359   998     
$$Walker, Anthony     RB  2017 2025 142 140 2346 10285 4.38  80  59   320   925     
$$Guersch, Joe        RB  2016 2024 140 123 2630 10279 3.91  60  57   390   1113    
Huntley, Blaine       RB  2010 2019 160 152 2390 9940  4.16  67  65   360   871     
Calhoun, Brian        RB  2006 2016 176 157 2607 9747  3.74  80  53   364   829     
McGahee, Willis       RB  2006 2014 143 130 2399 9397  3.92  76  49   302   799     
$$Helm, Ollie         RB  2018 2025 128 125 2242 9397  4.19  62  51   285   715  

On the real-life leaderboards, Emmitt Smith and Walter Payton lead with 17,162 and 16,726 yards, respectively. In the replay, I don't get anywhere near that figure. My leader, Nolan Allen, had 11,872 yards, which would rank him 9th all-time in the real NFL. His 2900+ carries, which leads my league, is over 1000 carries less than Emmitt Smith had in his career. This sounds alarming, but it's really not - only Smith, Walter Payton and Barry Sanders carried the ball 3000+ times in the history of the NFL (and even then Sanders carried the ball "only" 3062 times). Taking Smith and Payton out of the picture, it seems that careers for RBs in general max out at about 2900 carries. In the all-time NFL leaders in rushing yardage, there a 7 guys in the 2800-2900 range. In the book, "The Hidden Game of Football" there are countless others who end their careers in that same range (those not good enough to make the career yardage list). Let's disregard, for a moment, that I haven't had that rare Emmitt Smith or Walter Payton in my FOF career (obviously, an argument could be made that those guys only come around once every 20 years anyway - so I'm 0 for 1, big deal), why then are rushing yardage totals so low when rushing attempts seem pretty good? The real disparity between the FOF league and the career list is yards per carry. On the all-time list, there's not a single runningback in the top ten who averages < 4.0 ypc (in fact, Barry Sanders and Jim Brown averaged over 5.0). In the FOF league, 6 of the top ten all time rushers are < 4.0.

Is this a problem? Are top runningbacks not doing as well as they should? Do they need to be tweaked? This has massive MP implications if this is the case.

[SunDevil]

http://www.footballoutsiders.com/200...eep-zone/4506/

Too Deep Zone: Two Yards at a Time

11/10/2006

by Mike Tanier

It’s first-and-10 in the first quarter. The home team breaks the huddle. Their first play from scrimmage is a handoff to the running back. He’s hit at the line but dives forward. Gain of two yards.

You grumble. Two yards just doesn’t cut it on first-and-10. The running back should be able to do better; after all, he averages over four yards per carry, and the league rushing average is around four yards per attempt. Even average runners gain yardage in four-yard chunks. Why can’t your favorite halfback be more consistent?

It turns out that the problem isn’t with the running back, but with our perception of how that league rushing average is achieved. We may expect four yards per attempt, but a two-yard gain is the most common result for a running play, and no-gainers are almost as common as four-yard runs. We think of running plays as a way to generate consistent yardage with minimal risks. In fact, running plays, like passes, carry a high risk for a non-positive result.

To illustrate how rushing yardage is actually generated, we’re going to analyze every rushing play over a two-and-a-half year period. We’ll examine how many yards were gained on each play. Then we’ll look at specific down-and-distance situations to determine the actual results for rushing on first-and-10 or second-and-long. Finally, we’ll break down the statistics of some individual players so we can learn more about the differences between “big play” running backs and more consistent runners.
One or Two Yards and a Cloud of Dust

The NFL rushing average has hovered around 4.0 yards per carry for so long that I refer to the number as “Planck’s Constant” in Pro Football Prospectus 2006. That number has colored our perception of what running backs should do on a play-by-play basis. Unfortunately, it’s a misleading figure.

Last season, the official yards-per-carry average crept up to 4.1. The Football Outsiders figure was 4.17: 13,903 carries for 58,043 yards. Our data is always slightly different from the official data because we remove quarterback kneel plays (as well as spikes and Hail Marys) and make other minor changes to the official data. Either way, there’s no indication that the modest increase is anything but year-to-year fluctuation.

The 4.0-4.1 yard average is an arithmetic mean: add up all the yards, divide by the attempts. The arithmetic mean is easily skewed by extremes in data. A 75-yard run can increase a starting running back’s rushing average by several tenths of a point by the end of a season. This skewing always increases rushing averages: there are several 50+ yard rushes every year, but no 50+ yard losses on running plays.

We all know that a few big plays can make a mediocre running back’s rushing average look great. But how much effect do long gains have on the league rushing average? The best way to see this is to break down every running play by distance. Table 1 shows the distribution of yardage gained on every rushing play in the NFL in three years: 2000, 2005, and the first six weeks of 2006. The three seasons were chosen so that the data would be current, but would also reflect any changes in the distribution over the last half decade. The table reveals a surprising fact: the mean carry may yield four yards, but the median carry yields only three yards, and the data distribution is centered at two yards.
Table 1: Rushing Yardage Distribution
Yards Gained 2006 2005 2000 Overall
-4 0.8% 0.7% 0.8% 0.8%
-3 1.6 1.4 1.5 1.5
-2 2.5 2.6 2.5 2.5
-1 4.3 4.0 4.5 4.3
0 9.5 8.8 8.6 8.8
1 11.7 12.3 11.9 12.1
2 13.8 14.3 12.4 13.5
3 12.0 12.2 11.3 11.8
4 9.3 9.5 9.2 9.3
5 7.5 7.3 6.8 7.0
6 5.3 5.4 5.1 5.2
7 3.8 4.1 3.8 4.0
8 3.3 3.1 3.1 3.1
9 3.0 2.8 2.8 2.8
10 1.4 1.5 1.5 1.5

Almost 90 percent of all runs fall into the range shown in the table. Over 20 percent of running plays gain zero or one yards. Factor in losses, and over one-fourth of all runs result in negative or negligible yardage. The rushing average for the plays in the -4-to-10 yard range in 2005 was 2.95 yards per attempt. Long runs make up only about nine percent of all rushing plays, but they increase the league rushing average by over 40 percent.
Second and Wrong

The percentages you see in Table 1 aren’t broken down by down or field position. Obviously, some of those one-and-two yard runs are positive plays: first downs or touchdowns. But not many. Only about 1.7 percent of one-yard runs and 2.0 percent of two-yard runs yield first downs or touchdowns. Still, there are pollutants in the data which we should address. Are the distributions in Table 1 distorted by short-yardage carries or other factors?

Let’s break the data down. We’ll start by isolating one of the most basic situations in football: first quarter, first-and-10, in what Football Outsiders calls the “back zone” (between your own 20- and 39-yard lines). The offense is probably working though its pre-game script, and there’s nothing about the score of the game or the field position to force the offense’s hand or to tip off the defense about what to expect. Table 2 shows the gain distribution in these first down, early-game situations as compared to the overall distribution:
Table 2: First-and-10, Back Zone vs. All Runs
First-and-10 Overall
-4 0.9% 0.8%
-3 1.9 1.5
-2 2.8 2.5
-1 4.1 4.3
0 8.1 8.8
1 10.5 12.1
2 14.3 13.5
3 12.5 11.8
4 10.4 9.3
5 6.3 7.0
6 5.5 5.2
7 4.0 4.0
8 2.6 3.1
9 3.5 2.8
1 1.2 1.5

Pretty similar, right? The “on the chart” mean (the average of all rushes represented in the table) for first-and-10 situations is actually 2.66, lower than the overall overage, and it represents 88.6 of all rushes.

The overall Success Rate for rushing plays hovers around 40 percent. But on first down in the first quarter, the Success Rate was 31 percent in 2005 and the start of 2006 and 35 percent in 2000. For comparison’s sake, let’s look at the passing data. We don’t usually use Success Rate in our analysis of the passing game, but we can compute it, and the Success Rate on first-down, first-quarter, back zone passing plays was 49 percent in 2005, 45 percent in 2000, and 57 percent in a small (188 play) sample of the first few games of 2006.

Now let’s analyze the second down data. We’ll use full-game, full-field data, but we’ll break the carries down by the distance situation: 10+ yards to go, 7-9 yards to go, 4-6 yards to go, and 1-3 yards to go. Table 3 contains all of the data, plus the overall yardage distribution for easy comparison. For the record, the percentages in the chart represent nearly 10,000 rushing plays across three seasons.
Table 3: All Second Downs
10+ 7-9 4-6 1-3 Overall
-4 0.9% 0.8% 1.1 0.7 0.8
-3 1.7 1.9 1.4 0.9 1.5
-2 2.0 3.1 3.0 2.6 2.5
-1 3.7 4.7 4.1 4.8 4.3
0 7.7 7.4 6.8 13.4 8.8
1 10.8 10.6 12.1 14.9 12.1
2 12.6 12.2 13.7 14.3 13.5
3 11.6 10.6 14.5 12.0 11.8
4 10.0 9.8 9.9 9.3 9.3
5 7.5 7.7 7.4 6.2 7.0
6 5.9 7.2 4.2 5.3 5.2
7 4.7 3.6 4.5 3.3 4.0
8 3.3 3.5 3.0 2.4 3.1
9 3.5 2.7 2.1 1.5 2.8
10 1.5 2.5 1.4 1.2 1.5

Before we really crunch the numbers, let’s get some John Madden wisdom out of the way. Madden is fond of saying that teams often follow up an incomplete pass on first down with a run on second-and-10. Our data shows that teams run on second down and 10 or more yards about 36.2 percent of the time. The data includes all manner of 2nd-and-long situations, some of which may have occurred after sacks or penalties. If we skimmed away all of these situations, the run percentage on 2nd-and-10 would probably creep up to around 40 percent. So teams don’t run “all the time” on 2nd-and-10, but give Madden the benefit of the doubt: teams do run a lot on a down that many of us would associate with passing.

In fact, teams probably run more than they should, considering the 24 percent Success Rate on second-and-very long. The “in-the-box” mean on second-and-10+ is 3.12, indicating that teams are getting some benefit from running against a defense that is anticipating a pass. But the modest increase in yards-per-carry doesn’t offset the high likelihood that the team will face a third-and-long situation. Even in “unpredictable” down-and-distance combinations like second down with 4-6 yards to go, the in-the-box mean, covering 89.2 percent of all carries, is just 2.85.

On early downs, the data is very stable and predictable. An offense’s chance of gaining three or fewer yards on a running play hovers around 50-55 percent, even on first down in the first quarter or on 2nd-and-10. Only about 17 percent of runs gain the 4-5 yards we would hope to get when a good running back is getting the ball in favorable circumstances. And of the 35-40 percent of runs that gain more than six yards, most are 6-8 yard gains that, when averaged with all of the losses and no gainers, don’t get us anywhere near four yards per carry.

The rushing distributions clearly explain why teams throw so often on early downs. Fans may wish that teams would “establish the run” more early in games, but there are good reasons why they don’t. That league average of four yards per attempt suggests that teams would face a lot of favorable third-and-two situations if they just plowed ahead with the running game. But working through the charts, we discover that the team that hands off on first and second down has about a 33 percent chance of getting caught in third-and-7 and nearly a 15 percent chance of ending up in a third-and-8 or worse scenario. The rewards for running the ball are often so low that teams are willing to assume the increased risk of a turnover and pass more frequently.
Power Runners and Big-Play Runners

Rushing distributions tell us a great deal about how the modern NFL running game really works. The distributions may also tell us something about the merits of individual running backs. The data samples are smaller, and of course the overall quality of each running back’s team is a huge, unaccounted for variable when making comparisons. As a way of negating the importance of team strength as well as studying the contrasts between rushing styles, let’s examine a pair of teammates from 2005.

Last season, Tatum Bell gained 920 yards and averaged 5.3 yards per carry. Mike Anderson gained 1,014 yards but averaged just 4.2 yards per carry. Despite the wide disparity in yards per carry, DVOA and DPAR ranked Anderson as the better back. Anderson was 37.0 points above replacement level, Bell 16.4. Anderson was 20.3 percent better than the average back, Bell just 7.6 percent.

Bell’s rushing average was inflated by several long runs: he had a 68, 67, and 55 yard run in 2005, plus several 35-yard runs. Anderson’s longest carry of the season was 44 yards, and that was his only run longer than 25 yards. We all know that Bell is a “home run threat” while Anderson is more consistent. But is it really fair to downgrade Bell because of his long runs? We’re inclined to downgrade Bell somewhat because so much of his value is contained in a few plays. But is that really fair? After all, gaining four yards at a time is great and all, but big plays are pretty important, too.

If we look at the rushing breakdowns for Anderson and Bell (Table 4), we can clearly see the contrast in their contributions. Anderson’s yardage distribution is centered in the 2-3 yard range, while Bell’s is centered in the 1-2 yard range, giving Anderson a full yard-per-play advantage on carry after carry. Bell’s advantage, of course, is on runs of more than 10 yards. All but 6.5 percent of Anderson’s runs gain from -4 to 10 yards, while 10.5 percent of Bell’s runs are outside the chart (he only lost five yards on one play last season). Give them both 200 carries, and Bell will have eight more long runs than Anderson, and those runs will be longer than what Anderson can usually muster. But Anderson will gain an extra yard that Bell couldn’t on dozens of other
runs.
Table 4: Denver Yard Distributions, 2005
Mike Anderson Tatum Bell Overall
-4 0.0% 0.6 0.8
-3 0.8 0.6 1.5
-2 1.3 2.9 2.5
-1 1.7 4.0 4.3
0 7.5 9.2 8.8
1 10.0 11.6 12.1
2 16.7 21.4 13.5
3 18.0 8.7 11.8
4 11.2 8.7 9.3
5 7.1 6.4 7.0
6 7.1 6.9 5.2
7 3.8 3.5 4.0
8 2.5 2.3 3.0
9 4.2 0.6 2.8
10 1.6 1.1 1.5

Anderson’s in-the-box mean was 3.36 yards per attempt, noting again that his “box” is larger. Bell’s was just 2.67. What’s interesting is that we tend to think of backs like Anderson as “ordinary” while backs with Bell’s big-play potential are held in higher esteem. But Bell’s rushing distribution is more in line with the league norms than Anderson’s. He’s very good, but his contributions are typical of what backs around the league provide. Anderson, at least in 2005, was the unique player, providing hard-to-get, down-in, down-out production.

The difference between Bell and Anderson suggests that “cloud of dust” backs are more valuable than “boom or bust” backs, but we must be careful when using cheesy labels. Our perception of a back’s production profile are often way off. How would you classify Marshall Faulk in his prime? Probably as a boom-or-bust back, albeit one with lots of boom and only a little bust.

But Faulk’s running distributions show that in his prime he was much more than a big-play machine. Table 5 shows Faulk’s distributions from 2000. For comparison, let’s also take a look at James Stewart’s breakdowns from that season.
Table 5: Marshall Faulk vs. James Stewart, 2000
M. Faulk J. Stewart
-4 0.8% 0.0
-3 0.8 0.9
-2 1.9 2.9
-1 3.2 3.2
0 4.3 10.0
1 10.7 14.2
2 13.4 14.2
3 14.2 15.6
4 9.5 12.1
5 8.7 5.6
6 5.9 5.6
7 3.6 3.5
8 2.8 3.5
9 3.6 1.8
10 1.9 1.2

Faulk averaged 5.2 yards per carry and finished first in the NFL in DPAR. His longest run from scrimmage that year was just 38 yards; unlike Bell, his rushing average wasn’t pumped up by a few huge gains. Stewart averaged 3.5 yards per carry. Despite gaining 1,184 yards, he posted a negative DVOA, and his DPAR of 3.6 ranked him 26th in the league.

Faulk’s in-the-box mean was 3.37, a very good figure. What’s more, his “box” only included 86 percent of his runs. Faulk had seven 12-yard runs, six 16-yard runs, and three 18-yard runs in 2000, giving him a very high percentage of 11-20 yard runs. But what’s most remarkable about his production was his ability to avoid no-gainers and his above-average totals in the 3-5 yard range. Fast, shifty Faulk was just as good at using his skills to gain a yard or two as he was at burning defenses for long gains.

By contrast, Stewart’s ability to avoid losses and pick up two or three yards couldn’t offset his complete lack of big-play potential. At first glance, Stewart’s distribution looks similar to Andersons. But his in-the-box mean of 2.8 is over a half-yard lower. The differences are subtle — Anderson is a little more likely to gain five or six yards and a little less likely to lose yardage — but they add up over a few hundred carries. And Stewart, like Anderson, concentrated 95 percent of his carries in the -4-to-10 yard range, so he had few 10-20 yard bursts to increase his productivity. Stewart, like Anderson, was providing a unique skill, which is why he was able to stay in the league for several years. Unlike Anderson, he wasn’t a great exemplar of that skill, and the Football Outsiders metrics took him to task for it.

These players were carefully selected to illustrate certain points. If we analyzed dozens of backs, we may find common distribution patterns. If we studied the same back from year-to-year, we could determine if those patterns are stable and predictive. Some of that research is incorporated in the calculations for Adjusted Line Yards and other stats. The rest, unfortunately, is outside the scope of this little article.
Conclusions

Teams don’t generate rushing yards in three-, four-, or five-yard bursts. They gain it through punctuated equilibrium, waiting through dozens of minimal gains for a few big plays per game.

And those big plays aren’t that big. We’ve focused on gains of ten or less in this article, ignoring the 10.5 percent or so of plays that yield more yardage. The vast majority of those runs gain 11-20 yards: 6.9 percent overall. Almost 25 percent of the rushing yardage gained in the NFL is generated on runs of 11-20 yards. There were 960 such runs last year: 30 per team, or just over two per team per game. Amazingly nearly 10 percent of all rushing yardage is generated on runs of 30 or more yards, plays which occur about four times per year for a typical team.

These distribution breakdowns are so interesting that they might seduce us into making some wacky conclusions. Keep in mind that all of these averages and distribution patterns are situation dependent. We might look at the data and suggest that teams stop running the ball altogether on second-and-10, but of course the Success Rate on passing plays would dip sharply if teams stopped threatening to run. These league-wide averages don’t necessarily apply to individual teams, so teams with a quality running game may have different distributions that would suggest different optimal strategies. The Bell and Anderson data, for example, indicates that the Broncos have a more versatile running game than the average team, and observation (i.e. actually watching games instead of craning over spreadsheets) bears this out.

Without further study, we shouldn’t leap to grand conclusions. But we know this much: if we expect to gain four or five yards on every running play, we’re going to be disappointed most of the time. No wonder passing totals have been creeping up for decades. If all a handoff gets you is two yards and a cloud of dust, you might as well throw the ball.

[Warhammer]

I haven't played around with it, but does the AI optimize the holes that the RBs are running in? Or are they pounding the line behind that 38/38 C?

[CraigSca]

Wide Receivers

Front Office Football 2007
Receiving Statistics
   
  Player              Pos Strt End  GP  GS  Targ Ctch Pct   Yards Avg/C Avg/T YAC  
$$Spencer, Cornelius  WR  2015 2025 176 155 1348 812  60.2  10991 13.54 8.15  1820   
Molnar, Bruce         WR  2011 2023 196 195 1340 777  58.0  9954  12.81 7.43  1417   
Kolodzik, Leland      WR  2008 2018 168 168 1309 759  58.0  10155 13.38 7.76  1772   
$$Price, Rufus        WR  2012 2025 213 159 1258 748  59.5  9932  13.28 7.90  1730   
$$Polk, Terry         WR  2014 2025 191 154 1155 727  62.9  10583 14.56 9.16  2556   
Jones, Matt           WR  2006 2017 191 185 1232 721  58.5  9775  13.56 7.93  1308   
Jennings, Greg        WR  2006 2017 188 168 1239 720  58.1  9964  13.84 8.04  1636   
Anthony, Derek        WR  2010 2023 223 173 1159 720  62.1  9119  12.67 7.87  1499   
Newman, Dwight        WR  2013 2024 176 159 1174 716  61.0  10308 14.40 8.78  2496   
Williams, Demetrius   WR  2006 2018 193 108 1120 689  61.5  9836  14.28 8.78  2160

Again, my top ten wide receivers in total catches is above. On the real NFL all-time list Jerry Rice leads with an astronomical 1,456 all-time catches. Let's toss that freak out .

Below him on the top ten list is Cris Carter (1,101), Tim Brown (1,018), Andre Reed (951), Art Monk (940), Irving Fryar (851), Steve Largent (819), Henry Ellard (814), Larry Centers (808) and James Lofton (764).

My all-time leader would qualify for 8th on this list. My second-best would qualify for 10th. It should be noted that my leader has yet to retire, so he may have a few catches in him. Looking at the stats, I'm not too sure what to think of this one. It seems catches and yardage are a BIT low, but there isn't as much of a "problem" as there is with yards per carry from runningbacks. I'll give this a "wait and see", since some of these guys are still active. Certainly there are no Jerry Rices or Cris Carters, but maybe I haven't given it as much time as I need to.

[highfiveoh]

What injury setting are you using?

[CraigSca]

SunDevil,

I don't understand your point. While I understand the majority of rushes are 2 yards and a cloud of dust, I'm talking about all-time averages, not their distribution. The data I have seems to show that the average yards per carry for the all-time leaders in FOF2007 is a little low, that's all.

[highfiveoh]

Originally Posted by Warhammer

I haven't played around with it, but does the AI optimize the holes that the RBs are running in? Or are they pounding the line behind that 38/38 C?

I would think so being that I thought the AI teams adjusted run directions and pass distances in 2004 (just not the run percentages).

[CraigSca]

Originally Posted by highfiveoh

What injury setting are you using?

Whoops - forgot about that. I'm using the defaults on all settings (and have added that to my first post).

[highfiveoh]

Originally Posted by CraigSca

Whoops - forgot about that. I'm using the defaults on all settings (and have added that to my first post).

Heh, I missed the bottom part of your first post. I got the drift that you were using default stuff after reading that.

[SunDevil]

Originally Posted by CraigSca

SunDevil,

I don't understand your point. While I understand the majority of rushes are 2 yards and a cloud of dust, I'm talking about all-time averages, not their distribution. The data I have seems to show that the average yards per carry for the all-time leaders in FOF2007 is a little low, that's all.

If you read the article, it says that the league average of 4 ypc is mostly based on runningbacks breaking for big runs, which happen 9% of the time, which is about 1 or 2 times a game. So I thought I would say that maybe individual runners are not getting as many big running gains as the historical real players have gotten.

And those big plays aren’t that big. We’ve focused on gains of ten or less in this article, ignoring the 10.5 percent or so of plays that yield more yardage. The vast majority of those runs gain 11-20 yards: 6.9 percent overall. Almost 25 percent of the rushing yardage gained in the NFL is generated on runs of 11-20 yards. There were 960 such runs last year: 30 per team, or just over two per team per game. Amazingly nearly 10 percent of all rushing yardage is generated on runs of 30 or more yards, plays which occur about four times per year for a typical team.

The 4.0-4.1 yard average is an arithmetic mean: add up all the yards, divide by the attempts. The arithmetic mean is easily skewed by extremes in data. A 75-yard run can increase a starting running back’s rushing average by several tenths of a point by the end of a season. This skewing always increases rushing averages: there are several 50+ yard rushes every year, but no 50+ yard losses on running plays.

[CraigSca]

Ah, ok. Perhaps. Either that or guys aren't getting their requisite two yards when they go the "cloud of dust" route.

[CraigSca]

More Wide Receiver Musings

According to the data posted above, QBs seem to be "okay" when it comes to yards, attempts, etc., while the people they're throwing to seem to underperform.

WARNING: POSSIBLE ANECDOTAL EVIDENCE ALERT

In 2025, I looked at the top wide receivers to see if the disparity in career receptions and yardage is caused by a tendency of the game to spread the wealth among too many receivers. I looked at the top scouted wide receivers (yes, I'm aware there could be scouting issues here that muddy the data) and found Bo Grier of the Green Bay Packers. He's a 9th year guy, 3rd pick overall, all-pro in 2018, but has averaged about 60 catches a year. In 2025, he was injured for 4 games (which will muddy the data further), but caught only 33 passes during that time. Pro-rating those catches to 16 games, we have 44 catches. With that amount, he would be 3rd on the team. Hardy Coleman (85) and Arnie Lelie (51) would have more, yet they are rated 44/44 and 39/39 while Grier rates a 74/74. My scout is average in the receiving category.

I realize this is a severely small sample size (see my above warning), but shouldn't Grier be getting the majority of touches in the game? How can Coleman (a 44/44) be thrown to 122 times during the season while Grier gets thrown to 61 times (pro-rated to 81). To me, it seems there are just too many receivers getting the ball (?). As evidence of this, Jerry Rice, all-time has more RECEPTIONS than my #1 all-time receiver's TARGETED PASSES.

[SunDevil]

It is a known bug in the bug report thread.

[CraigSca]

I guess you're referring to playing time percentages? Yes, I guess that could answer the receivers problem.

[kcchief19]

Originally Posted by CraigSca

EDIT: Forgot to state - using all defaults in this league, including default injuries.

IMHO, which I think most of the hardcore FOFers would agree, injuries must be at max for a fair comparison of simmed stats vs. real life stats. I have no doubt that with injuries on max, those career numbers would be slightly lower.

Your mentioning that you QBs are not retiring too early in your test sparks a throught on my end taking into consideration SkyDog's observations that players may be retiring earlier in his test leagues -- we know injured players take their injury into consideration when deciding whether to retire, but could it be that players now take their injury HISTORY into consideration? Or could injuries have a compounding effect, in essence shortening a player's career?

Obviously that data is now stored, and if there is a difference between player careers with injuries 100 vs. 200, that's a variable to take a look at. I may have to test that when I get home tonight.

The very thought makes me all tingly inside.

[SunDevil]

CraigSca,

I think what you are doing is a good thing. Sorry if I came off curt earlier its been a long day.

[CraigSca]

Originally Posted by SunDevil

CraigSca,

I think what you are doing is a good thing. Sorry if I came off curt earlier its been a long day.

Oh no, not at all. I should have checked the bug thread more thoroughly before even bringing up receivers. I'd still like to see why elite runningbacks don't seem to have the great yards per carry averages that one would expect.

[Ben E Lou]

Per Craig's request, my rushing leaders:

  Player              Pos Strt End  GP  GS  Att  Yards Avg   Lg  TD   RZAtt Yards  
Maticic, Moe          RB  2008 2019 186 186 3624 14841 4.10  69  64   466   1316    
Farmer, Wendell       RB  2014 2024 171 169 3261 14646 4.49  67  86   387   1191    
Rhea, Andy            RB  2012 2022 176 176 3282 13688 4.17  59  97   521   1611    
King, Earl            RB  2006 2016 174 174 3424 12690 3.71  80  78   401   1112    
Ellison, Danny        RB  2006 2016 171 170 3070 12372 4.03  70  82   398   1127    
Henselman, Eddie      RB  2018 2027 160 96  2612 11640 4.46  64  62   340   1158    
Irwin, Kurt           RB  2006 2015 155 121 2638 11581 4.39  73  79   413   1227    
Sutton, Fred          RB  2006 2016 173 173 2761 10995 3.98  80  76   406   1039    
$$Perry, Preston      RB  2020 2029 155 155 2654 10868 4.09  70  86   360   1018    
Morrison, Wesley      RB  2006 2015 156 125 2633 10562 4.01  70  49   332   1027    
Steed, Antoine        RB  2006 2016 175 125 2607 10399 3.99  64  58   348   883     
Oliver, Joey          RB  2006 2014 137 137 2584 10358 4.01  51  67   363   1114    
$$Boyer, Cary         RB  2019 2029 173 165 2563 10292 4.02  60  68   314   813     
Gatlin, Barry         RB  2012 2021 150 150 2615 10114 3.87  65  55   361   865     
Saba, Louie           RB  2015 2024 160 147 2414 10044 4.16  78  53   332   1068    
Forsberg, John        RB  2010 2019 153 139 2384 9959  4.18  72  63   348   1071    
Grier, Mark           RB  2014 2022 135 126 2539 9907  3.90  79  51   333   802     
$$Busofsky, Eddie     RB  2022 2029 121 121 2334 9854  4.22  99  43   299   867     
Tornberg, Harry       RB  2012 2021 159 113 2355 9547  4.05  69  70   348   1029    
Lang, Rickey          RB  2006 2016 144 140 2370 9253  3.90  95  57   348   979     
Swank, Tim            RB  2018 2026 131 114 2391 9173  3.84  55  54   263   686     
Picton, Fernando      RB  2015 2022 114 112 2169 8813  4.06  91  53   269   731     
Shepard, Ray          RB  2015 2023 143 143 2280 8800  3.86  65  40   302   852     
Ioane, Leon           RB  2013 2022 138 118 2285 8767  3.84  73  47   307   836     
Bruce, Wayne          RB  2006 2016 173 141 2284 8732  3.82  60  60   326   867     
Collins, Fred         RB  2009 2017 133 129 2108 8692  4.12  80  49   286   821     
$$Wagoner, Leonard    RB  2022 2029 127 127 2064 8692  4.21  65  46   255   710     
Starks, Deion         RB  2009 2018 158 126 2110 8691  4.12  68  66   308   1006    
Kennedy, Blaine       RB  2006 2014 141 132 2365 8644  3.65  65  34   303   810     
Gantt, Matthew        RB  2012 2021 145 143 1994 8452  4.24  75  65   287   879     
Hitchcock, Dustin     RB  2007 2014 127 124 2099 8262  3.94  83  53   315   750     
Luethje, Wayne        RB  2009 2017 138 131 2034 8250  4.06  50  51   334   1100    
Francis, Billy        RB  2016 2025 155 103 1950 8154  4.18  63  68   346   1033    
Benitez, Christian    RB  2010 2018 142 109 1801 8088  4.49  70  54   275   745     
Cote, Shawn           RB  2009 2017 139 139 1877 7939  4.23  51  42   269   745     
$$Doggett, Clyde      RB  2022 2029 117 116 1837 7872  4.29  57  40   193   476     
Bratcher, Shawn       RB  2019 2025 111 95  1855 7777  4.19  65  54   261   801     
Carpenter, Martin     RB  2015 2023 131 115 1845 7756  4.20  77  44   232   698     
Collins, Charles      RB  2009 2015 111 110 1855 7698  4.15  64  22   220   601     
Fortney, Dale         RB  2014 2021 122 117 1859 7107  3.82  63  43   270   738     
$$Kemp, Eugene        RB  2021 2029 135 70  1758 7107  4.04  91  29   212   536     
Friesz, Austin        RB  2009 2017 144 117 1753 7058  4.03  51  30   282   779     
Hartman, Vince        RB  2007 2015 141 93  1864 6814  3.66  79  35   221   560     
Olpin, Todd           RB  2008 2017 157 91  1885 6774  3.59  64  44   254   663     
Blake, Curtis         RB  2018 2026 135 109 1706 6729  3.94  47  53   243   689     
$$Wilcox, Greg        RB  2023 2029 112 111 1711 6656  3.89  48  34   228   595     
$$Rhodes, Albert      RB  2024 2029 93  93  1487 6449  4.34  68  40   185   497     
$$Hamer, Billy        RB  2020 2029 148 39  1500 6448  4.30  70  36   201   566     
$$Flynn, Doug         RB  2020 2028 143 42  1519 6414  4.22  50  33   193   612     
D'Herde, Brant        RB  2006 2014 135 64  1471 6381  4.34  58  36   241   774     
$$Clinton, B.J.       RB  2024 2029 95  78  1553 6341  4.08  40  37   234   682     
$$Foster, Dwight      RB  2023 2028 91  75  1512 6332  4.19  59  50   234   675     
$$Baek, Brent         RB  2022 2029 123 64  1550 6331  4.08  71  31   188   533     
$$Copeland, Brady     RB  2024 2029 80  80  1364 6276  4.60  59  33   192   521     
Swift, Earl           RB  2018 2023 92  65  1398 6265  4.48  63  31   171   465     
Duffy, Deon           RB  2010 2017 113 70  1613 6039  3.74  40  42   223   616     
Stone, Marvin         RB  2006 2012 98  64  1542 6000  3.89  72  34   186   507     
Hansen, Jerry         RB  2012 2021 160 68  1489 5921  3.98  66  40   215   584     
Burke, Sherman        RB  2006 2011 96  73  1461 5797  3.97  68  29   189   495     
$$Hicks, Neal         RB  2021 2028 88  87  1417 5768  4.07  80  24   175   459     
$$Hall, Alex          RB  2025 2029 80  78  1470 5742  3.91  57  33   184   532     
Nelson, Mario         RB  2006 2010 80  65  1506 5732  3.81  53  36   210   525     
Sullivan, Nolan       RB  2006 2014 140 47  1547 5730  3.70  49  42   262   677     
Lyle, Byron           RB  2013 2019 106 80  1490 5704  3.83  80  38   207   532     
$$Macklin, Derrick    RB  2024 2029 91  89  1276 5639  4.42  76  42   170   477     
Blue, Harvey          RB  2014 2020 112 64  1386 5503  3.97  63  53   237   636     
Henry, Donovan        RB  2015 2022 127 60  1509 5462  3.62  47  47   250   646     
$$Darnick, Richard    RB  2024 2029 89  89  1310 5461  4.17  57  36   179   499     
Craver, Alex          RB  2018 2024 109 66  1418 5335  3.76  39  28   198   502     
Perkins, Allen        RB  2019 2024 93  60  1336 5306  3.97  82  46   192   501     
Mears, Oliver         RB  2017 2024 117 67  1317 5218  3.96  88  34   206   534     
$$Winger, Aaron       RB  2020 2028 130 58  1295 5080  3.92  54  33   197   535     
Barlow, Harvey        RB  2017 2022 94  64  1265 4996  3.95  58  27   155   389     

Lucas, Roy RB 2011 2016 96 56 1245 4928 3.96 80 37 177 465

[Ben E Lou]

Oh....

1. Of course, this is with Injuries=200.
2. This league was started with a random roster set.
3. Full info is at: http://www.younglifenorthdekalb.com/fofc/rushing.txt

[JeffW]

Originally Posted by CraigSca

Is this a problem? Are top runningbacks not doing as well as they should? Do they need to be tweaked? This has massive MP implications if this is the case.

Isn't this how it was in FOF 2004 as well? RBs since 2k1 seem to perform poorly in yards/carry. As far as the FBO stuff goes, I don't think it's worthwhile to compare since we don't have the same metrics within the FOF interface.

[Ben E Lou]

Originally Posted by JeffW

RBs since 2k1 seem to perform poorly in yards/carry.

R.J. Ellard sure doesn't agree with that.

[AlexB]

For reference, I've simmed 1970-2006

QBs - 2 QBs have thrown for 60000 plus yards, 6 50000 plus, 16 14000 plus

RBs - 6 have rushed for 13000+ yards, 3 for 12000+, 5 for 10000 plus

WRs- 2 has 900+ receptions, 4 have 800+, 19 have 700 receptions. One has 150000+ yards (925 catches), in order next yards = 13,476; 12,627; 7 have have 11000+ yards...

[CraigSca]

JRS - of your top 10 career rushers, how many have a < 4.0 ypc?

[AlexB]

Originally Posted by CraigSca

JRS - of your top 10 career rushers, how many have a < 4.0 ypc?

When sorted by career yardage, I have one guy at 3221 rushes for 12569 at an average of 3.90 YPC, and one guy at 2164 rushes for 12650 yards (4.00 exactly). The other eight over 12000 yards average 4.06 - 4.64 YPC.