Showing posts with label Football. Show all posts
Showing posts with label Football. Show all posts
Wednesday, June 26, 2013
Longest-Tenured NFL players
Chase Stuart at footballperspective.com had a blog post this week listing the longest-tenured player for each NFL team. I usually find it interesting to visualize things like this. So here's a chart showing the timeline for each team's longest-tenured player, as of 6/25/13.
Tuesday, February 26, 2013
Last NFL Playoff Win
This chart shows the last season that each NFL team won a playoff game. (updated through 2012 NFL season)
Friday, April 27, 2012
Grading the 2005 NFL Draft Grades
Every year the experts like to immediately grade each teams' NFL draft. I've always thought these are useless, because the experts really have no idea which players are going to be good.
So I thought I would grade a past draft.
I randomly picked 2005. It's long ago enough that we have a good idea which players turned out good or not. It's also near enough that I found some draft grades online. I decided to compare to SI's Dr. Z 2005 draft grades.
I figure that for each draft a team can only do as well as the players that are available, so each draft is its own entity. I took a look at the Approximate Value* from Pro-Football-Reference.com 's 2005 Draft summary. The top picks that year were guys like DeMarcus Ware, Aaron Rodgers, Roddy White, Logan Mankins and Frank Gore. I am going to give any of the top-32 AV players a grade of "A". Any player who is 33-64 in career AV (through 2011) gets a "B". 65-96 gets a "C". 97-128 gets a "D". Anybody ranking lower gets an "F".
* One note about AV: PFR doesn't calculate AV for punters or kickers. There were 5 of those drafted and are classified as "F's" in my study, but aren't necessarily. So teams like Jets (Mike Nugent) and Chiefs (Dustin Colquitt) are graded a bit lower than they should be.
I totaled up the GPA for each team. Here's how that shakes out:
Team GPA Grade
DAL 2.75 C+
NYG 2.50 C
NWE 2.29 C-
SDG 2.29 C-
CHI 2.17 C-
MIA 2.17 C-
ATL 2.00 C-
PHI 1.64 D
TEN 1.64 D
SFO 1.45 D
NYJ 1.38 D
PIT 1.38 D
STL 1.36 D
WAS 1.33 D
JAX 1.25 D-
SEA 1.22 D-
DEN 1.17 D-
ARI 1.14 D-
BAL 1.14 D-
OAK 1.14 D-
CAR 1.10 D-
CIN 1.00 D-
CLE 1.00 D-
GNB 1.00 D-
NOR 0.86 F
DET 0.83 F
HOU 0.83 F
TAM 0.83 F
IND 0.70 F
MIN 0.57 F
KAN 0.56 F
BUF 0.50 F
Lots of bad grades here. This is because with 7 picks per team (before any trades), only a few end up being NFL players, so all the guys who never play in an NFL game really drag down the average. So in order to get a fair grade, we really need to compare actual GPA to expected GPA. In a perfect draft, we would expect every team to get an "A" player in the first round, a "B" player in the second round, etc. But then teams trade draft picks around, so their expected GPA's will all be different. Kansas City had the lowest expected GPA because they had no pick at all in the second round. Minnesota had the highest ExGPA because they had 2 first-round picks, and no fifth-round picks (to bring the average down).
Here are the expected GPAs for all teams:
Team ExGPA
MIN 2.00
SDG 1.71
ARI 1.71
MIA 1.67
DAL 1.63
BAL 1.57
OAK 1.57
NYG 1.50
WAS 1.50
DEN 1.50
DET 1.50
CIN 1.43
NOR 1.43
CHI 1.33
SEA 1.33
NWE 1.29
PHI 1.27
TEN 1.27
ATL 1.25
PIT 1.25
JAX 1.25
CLE 1.25
CAR 1.20
STL 1.18
HOU 1.17
NYJ 1.13
IND 1.10
GNB 1.09
SFO 1.00
TAM 1.00
BUF 1.00
KAN 0.78
The next step is to compare these numbers. Which teams did the best (or worst) compared to their expected values? I subtracted the actual GPA from the Expected GPA, and here's what we get:
Team Var
DAL 1.13 A
NYG 1.00 A
NWE 1.00 A
CHI 0.83 A
ATL 0.75 A
SDG 0.57 A
MIA 0.50 B
SFO 0.45 B
PHI 0.36 B
TEN 0.36 B
NYJ 0.25 B
STL 0.18 B
PIT 0.13 B
JAX 0.00 B
GNB (0.09) C
CAR (0.10) C
SEA (0.11) C
TAM (0.17) C
WAS (0.17) C
KAN (0.22) C
CLE (0.25) C
DEN (0.33) C
HOU (0.33) C
IND (0.40) C
BAL (0.43) C
OAK (0.43) C
CIN (0.43) C
BUF (0.50) C
ARI (0.57) C
NOR (0.57) C
DET (0.67) D
MIN (1.43) F
Jacksonville had a GPA exactly equal to what we expected them to do! Minnesota had those 2 picks in the first round, but Troy Williamson (D) and Erasmus James (D) never contributed much in the NFL. They were 2 of the 3 worst players picked in the first round. The third guy David Pollack picked by Cincinnati.
Dallas scored big with DeMarcus Ware (A) and Marcus Spears (B) in the first round. They had 4 other picks that were A's or B's! Out of 8 draft selections, 6 of them earned A's or B's.
Using the standard deviation for these grades (0.57), any team who had a variance above 0.56 gets an A. (-0.2) to .55 gets a B, etc.
Dr. Z was a little vague in some of his grades, giving teams a B-/C+ (Conditional), etc. But I count 23 teams that he awarded a B or an A. I only awarded 14 such grades. He didn't give out any F's and only gave Denver a D. There are 27 teams which he graded within one grade of their actual grade, and 9 teams that graded out exactly as he predicted. Overall, it looks like he didn't do too bad a job of grading the draft. The biggest discrepancy was with Minnesota. He gave them an A and rated them with the best draft, when they actually had the worst draft. None of the Vikings' picks earned higher than a D. DT C.J. Mosley was their best pick with a career AV of just 10. Here was Dr. Z's summary for the Vikings:
I randomly picked 2005. It's long ago enough that we have a good idea which players turned out good or not. It's also near enough that I found some draft grades online. I decided to compare to SI's Dr. Z 2005 draft grades.
I figure that for each draft a team can only do as well as the players that are available, so each draft is its own entity. I took a look at the Approximate Value* from Pro-Football-Reference.com 's 2005 Draft summary. The top picks that year were guys like DeMarcus Ware, Aaron Rodgers, Roddy White, Logan Mankins and Frank Gore. I am going to give any of the top-32 AV players a grade of "A". Any player who is 33-64 in career AV (through 2011) gets a "B". 65-96 gets a "C". 97-128 gets a "D". Anybody ranking lower gets an "F".
* One note about AV: PFR doesn't calculate AV for punters or kickers. There were 5 of those drafted and are classified as "F's" in my study, but aren't necessarily. So teams like Jets (Mike Nugent) and Chiefs (Dustin Colquitt) are graded a bit lower than they should be.
I totaled up the GPA for each team. Here's how that shakes out:
Team GPA Grade
DAL 2.75 C+
NYG 2.50 C
NWE 2.29 C-
SDG 2.29 C-
CHI 2.17 C-
MIA 2.17 C-
ATL 2.00 C-
PHI 1.64 D
TEN 1.64 D
SFO 1.45 D
NYJ 1.38 D
PIT 1.38 D
STL 1.36 D
WAS 1.33 D
JAX 1.25 D-
SEA 1.22 D-
DEN 1.17 D-
ARI 1.14 D-
BAL 1.14 D-
OAK 1.14 D-
CAR 1.10 D-
CIN 1.00 D-
CLE 1.00 D-
GNB 1.00 D-
NOR 0.86 F
DET 0.83 F
HOU 0.83 F
TAM 0.83 F
IND 0.70 F
MIN 0.57 F
KAN 0.56 F
BUF 0.50 F
Lots of bad grades here. This is because with 7 picks per team (before any trades), only a few end up being NFL players, so all the guys who never play in an NFL game really drag down the average. So in order to get a fair grade, we really need to compare actual GPA to expected GPA. In a perfect draft, we would expect every team to get an "A" player in the first round, a "B" player in the second round, etc. But then teams trade draft picks around, so their expected GPA's will all be different. Kansas City had the lowest expected GPA because they had no pick at all in the second round. Minnesota had the highest ExGPA because they had 2 first-round picks, and no fifth-round picks (to bring the average down).
Here are the expected GPAs for all teams:
Team ExGPA
MIN 2.00
SDG 1.71
ARI 1.71
MIA 1.67
DAL 1.63
BAL 1.57
OAK 1.57
NYG 1.50
WAS 1.50
DEN 1.50
DET 1.50
CIN 1.43
NOR 1.43
CHI 1.33
SEA 1.33
NWE 1.29
PHI 1.27
TEN 1.27
ATL 1.25
PIT 1.25
JAX 1.25
CLE 1.25
CAR 1.20
STL 1.18
HOU 1.17
NYJ 1.13
IND 1.10
GNB 1.09
SFO 1.00
TAM 1.00
BUF 1.00
KAN 0.78
The next step is to compare these numbers. Which teams did the best (or worst) compared to their expected values? I subtracted the actual GPA from the Expected GPA, and here's what we get:
Team Var
DAL 1.13 A
NYG 1.00 A
NWE 1.00 A
CHI 0.83 A
ATL 0.75 A
SDG 0.57 A
MIA 0.50 B
SFO 0.45 B
PHI 0.36 B
TEN 0.36 B
NYJ 0.25 B
STL 0.18 B
PIT 0.13 B
JAX 0.00 B
GNB (0.09) C
CAR (0.10) C
SEA (0.11) C
TAM (0.17) C
WAS (0.17) C
KAN (0.22) C
CLE (0.25) C
DEN (0.33) C
HOU (0.33) C
IND (0.40) C
BAL (0.43) C
OAK (0.43) C
CIN (0.43) C
BUF (0.50) C
ARI (0.57) C
NOR (0.57) C
DET (0.67) D
MIN (1.43) F
Jacksonville had a GPA exactly equal to what we expected them to do! Minnesota had those 2 picks in the first round, but Troy Williamson (D) and Erasmus James (D) never contributed much in the NFL. They were 2 of the 3 worst players picked in the first round. The third guy David Pollack picked by Cincinnati.
Dallas scored big with DeMarcus Ware (A) and Marcus Spears (B) in the first round. They had 4 other picks that were A's or B's! Out of 8 draft selections, 6 of them earned A's or B's.
Using the standard deviation for these grades (0.57), any team who had a variance above 0.56 gets an A. (-0.2) to .55 gets a B, etc.
Dr. Z was a little vague in some of his grades, giving teams a B-/C+ (Conditional), etc. But I count 23 teams that he awarded a B or an A. I only awarded 14 such grades. He didn't give out any F's and only gave Denver a D. There are 27 teams which he graded within one grade of their actual grade, and 9 teams that graded out exactly as he predicted. Overall, it looks like he didn't do too bad a job of grading the draft. The biggest discrepancy was with Minnesota. He gave them an A and rated them with the best draft, when they actually had the worst draft. None of the Vikings' picks earned higher than a D. DT C.J. Mosley was their best pick with a career AV of just 10. Here was Dr. Z's summary for the Vikings:
VIKINGS -- Where do we start? Top pick Troy Williamson goes deep and doesn't walk off the field while the game's going on. The other first-rounder, Erasmus James, should have been the first outside rusher selected. Instead the Vikes got lucky and he was the fourth. Marcus Johnson is a serious mauler at either guard or tackle. Dustin Fox -- a cornerback or safety, take your pick -- vertically jumped 43 1/2...His biggest misses in the other direction were the Giants and Bears who he graded out as "C" drafts, while they turned out to be "A" drafts behind picks such as: Kyle Orton, Cedric Benson, Chris Harris, Justin Tuck, Corey Webster and Brandon Jacobs. He said the Bears blew it by not helping their offensive line. He mainly downgraded the Giants because they only had 4 picks (due to the Eli Manning trade the year before), and not having much faith in Justin Tuck.
Wednesday, September 1, 2010
Can Brandon Marshall Succeed in Miami?
A couple of months ago on the BS Report, Bill Simmons and Matthew Berry were discussing the 2010 fantasy prospects of Brandon Marshall. Simmons made a comment that he didn't think WR's who changed teams usually did very well, with the exception of Randy Moss. He repeated this theory this week with Mike Lombardi. At first glance, this seems fairly accurate. Guys like Carl Pickens and Alvin Harper jump to mind as guys who did very little after changing teams.
But how many players really compare to Brandon Marshall? Marshall has played for 4 seasons and 2010 will be his age 26 season. Marshall has over 100 receptions and 1,000 yards in each of the past 3 seasons. It's not often that a player with as much success, and still as young as Marshall, changes teams. There have been 36 players to gain 500+ receiving yards at age 25 or younger and then change teams the following season. If we stretch that out to include guys who were 26 or younger, the count increases to 77 players.
Of those 77 players, eight of them had 1,000+ receiving yards before changing teams, and all eight of them had fewer receiving yards with their new team:
Out of the 77 players who changed teams, only 16 had more yards in the first year with their new team than they had in the last year with their old team. The most successful of these was Santana Moss who had 1,483 yards receiving for Washington at age 26 - which was 645 yards better than his previous season with the Jets. On average, these players had 225 yards fewer with their new team than they had with their old team. If we expand the pool to include all players with 500+ yards, regardless of age, we have a pool of 249 players, and the average only increases to a 258-yard dropoff in production. In all, 47 of the 249 receivers had better seasons with their new teams.
Because of regression to the mean we know that most players who have a good season, will naturally follow those up with less successful seasons. So how did the guys do who had 500+ yards and stayed with the same team? First, let's take a look at the young guys. There have been 922 receivers to catch 500+ yards in a season, and play for the same team the following year. 326 of those had a yardage increase in year N+1 with an average decrease of 111 yards. Once again, the old guys were a little less successful. Disregarding age, there were 1,971 receivers with 500+ yards who stayed with the same team. 593 of them increased their yardage total, with an average decrease of 149 yards.
In summary:
These numbers reflect what we would think intuitively: younger receivers are more likely to improve on a good (500+ receiving yards) season and players who stay with their team are more likely to improve on a good season. This is because the team that has the receiver on a team knows him best and knows if he still has more good seasons left in him. Also, if a player stays with his team, he and his teammates are more familiar with each other.
But this still doesn't tell us a whole lot about whether Brandon Marshall will have success in Miami or not. Marshall has had a much better start to his career than the average receiver. Let's see if we can narrow down some comparable situations to Marshall. Marshall has averaged over 1,200 yards per season over the past 3 seasons. There are 109 other receivers who have averaged over 1,000 yards during at least one 3-year span in their careers. Only 46 of those achieved that feat by their age 26 season. There are only 2 players besides Marshall to meet this criteria and then play for a different team the following season: David Boston and Buddy Dial.
David Boston had 1,156 yards at age 22, 1,598 yards at age 23 and then 512 yards in just 8 games at age 24. Then he went to San Diego at age 25 and gained 880 yards in 14 games and that was basically the end of his career. Boston had injury problems, and was never the same player again.
Buddy Dial came into the league in 1959 with the Pittsburgh Steelers. From 1960 through 1963 while playing with Bobby Layne he had yardage totals of 972, 1,047, 981 and 1295 before being traded to the Dallas Cowboys in 1964. He played just 3 more seasons in the NFL and due to injuries never topped 283 yards in a season.
Like Marshall, there are 3 players who met these criteria for the first time last season. These are Santonio Holmes, Greg Jennings and Calvin Johnson. I'm going to remove them from the analysis. Also, Braylon Edwards, Andre Johnson and Larry Fitzgerald have yet to play their age 29 season, so I am going to remove them also. Edwards was traded to the Jets during his age 26 season after averaging 1,000+ yards his previous 3 seasons - only one of which went over 1,000 yards.
We now have a list of 39 players who had sustained success at WR prior to age 27, and have already played their age 29 season (or have retired). These 39 players went on to average 863 yards per season for their age 27 through 29 seasons. 12 of them averaged over 1,000 yards per season over that span.
The full list:
Name Yards
Torry Holt 1,466
Chad Johnson 1,414
Jerry Rice 1,397
Michael Irvin 1,391
Sterling Sharpe 1,285
James Lofton 1,271
Isaac Bruce 1,247
Gary Clark 1,227
Herman Moore 1,191
Lance Alworth 1,108
Art Powell 1,062
Hines Ward 1,047
Anquan Boldin 972
Plaxico Burress 967
Laveranues Coles 964
Andre Reed 960
Antonio Freeman 935
Steve Largent 930
Tony Hill 926
Santana Moss 881
Mark Clayton 849
Bob Hayes 825
Carl Pickens 818
Andre Rison 794
Dwight Clark 793
Randy Moss 775
Mike Quick 746
Stanley Morgan 719
Al Toon 677
Darrell Jackson 645
Mark Carrier 630
Frank Sanders 589
Cris Collinsworth 582
Joey Galloway 481
John Jefferson 400
Harlon Hill 242
Buddy Dial 238
George Sauer 170
David Boston 27
Conclusion: Obviously, there is no way to predict how things will turn out for Brandon Marshall. There haven't been many other players with similar success to Brandon Marshall who changed teams during his successful run. The closest comps are David Boston, Buddy Dial and Braylon Edwards. Boston and Dial were derailed by injuries, and Braylon Edwards who has played enough to use as a predictor for Marshall. When comparing Marshall to other players who came off 500+ yard seasons we see that generally those players will decrease productivity the following season. But when we compare Marshall to other receivers who had sustained success at a young age, we see that these players generally continued to play well through their 20's and is a who's who list of the best WR's in NFL history.
But how many players really compare to Brandon Marshall? Marshall has played for 4 seasons and 2010 will be his age 26 season. Marshall has over 100 receptions and 1,000 yards in each of the past 3 seasons. It's not often that a player with as much success, and still as young as Marshall, changes teams. There have been 36 players to gain 500+ receiving yards at age 25 or younger and then change teams the following season. If we stretch that out to include guys who were 26 or younger, the count increases to 77 players.
Of those 77 players, eight of them had 1,000+ receiving yards before changing teams, and all eight of them had fewer receiving yards with their new team:
| Player | Year | Age | Team | Yards | N+1 Yards |
| John Jefferson | 1980 | 24 | SD | 1340 | 632 |
| Jeff Graham | 1995 | 26 | Pit | 1301 | 788 |
| Laveranues Coles | 2002 | 25 | Was | 1264 | 1204 |
| Peerless Price | 2002 | 26 | Buf | 1252 | 838 |
| Harold Jackson | 1972 | 26 | Phi | 1048 | 874 |
| Rob Moore | 1994 | 26 | NYJ | 1010 | 907 |
| Derrick Alexander | 1998 | 26 | Bal | 1009 | 992 |
| Antonio Bryant | 2005 | 24 | Cle | 1009 | 733 |
Out of the 77 players who changed teams, only 16 had more yards in the first year with their new team than they had in the last year with their old team. The most successful of these was Santana Moss who had 1,483 yards receiving for Washington at age 26 - which was 645 yards better than his previous season with the Jets. On average, these players had 225 yards fewer with their new team than they had with their old team. If we expand the pool to include all players with 500+ yards, regardless of age, we have a pool of 249 players, and the average only increases to a 258-yard dropoff in production. In all, 47 of the 249 receivers had better seasons with their new teams.
Because of regression to the mean we know that most players who have a good season, will naturally follow those up with less successful seasons. So how did the guys do who had 500+ yards and stayed with the same team? First, let's take a look at the young guys. There have been 922 receivers to catch 500+ yards in a season, and play for the same team the following year. 326 of those had a yardage increase in year N+1 with an average decrease of 111 yards. Once again, the old guys were a little less successful. Disregarding age, there were 1,971 receivers with 500+ yards who stayed with the same team. 593 of them increased their yardage total, with an average decrease of 149 yards.
In summary:
| Type | Number | Number Improved | Pct Improved | Average Improvement |
| Changed Teams - All Ages | 249 | 47 | 18.9% | -258 yards |
| Change Teams - 27 or younger | 77 | 16 | 20.8% | -225 yards |
| Same Team - All Ages | 1971 | 593 | 30.1% | -149 yards |
| Same Team - 27 or younger | 922 | 326 | 35.4% | -111 yards |
These numbers reflect what we would think intuitively: younger receivers are more likely to improve on a good (500+ receiving yards) season and players who stay with their team are more likely to improve on a good season. This is because the team that has the receiver on a team knows him best and knows if he still has more good seasons left in him. Also, if a player stays with his team, he and his teammates are more familiar with each other.
But this still doesn't tell us a whole lot about whether Brandon Marshall will have success in Miami or not. Marshall has had a much better start to his career than the average receiver. Let's see if we can narrow down some comparable situations to Marshall. Marshall has averaged over 1,200 yards per season over the past 3 seasons. There are 109 other receivers who have averaged over 1,000 yards during at least one 3-year span in their careers. Only 46 of those achieved that feat by their age 26 season. There are only 2 players besides Marshall to meet this criteria and then play for a different team the following season: David Boston and Buddy Dial.
David Boston had 1,156 yards at age 22, 1,598 yards at age 23 and then 512 yards in just 8 games at age 24. Then he went to San Diego at age 25 and gained 880 yards in 14 games and that was basically the end of his career. Boston had injury problems, and was never the same player again.
Buddy Dial came into the league in 1959 with the Pittsburgh Steelers. From 1960 through 1963 while playing with Bobby Layne he had yardage totals of 972, 1,047, 981 and 1295 before being traded to the Dallas Cowboys in 1964. He played just 3 more seasons in the NFL and due to injuries never topped 283 yards in a season.
Like Marshall, there are 3 players who met these criteria for the first time last season. These are Santonio Holmes, Greg Jennings and Calvin Johnson. I'm going to remove them from the analysis. Also, Braylon Edwards, Andre Johnson and Larry Fitzgerald have yet to play their age 29 season, so I am going to remove them also. Edwards was traded to the Jets during his age 26 season after averaging 1,000+ yards his previous 3 seasons - only one of which went over 1,000 yards.
We now have a list of 39 players who had sustained success at WR prior to age 27, and have already played their age 29 season (or have retired). These 39 players went on to average 863 yards per season for their age 27 through 29 seasons. 12 of them averaged over 1,000 yards per season over that span.
The full list:
Name Yards
Torry Holt 1,466
Chad Johnson 1,414
Jerry Rice 1,397
Michael Irvin 1,391
Sterling Sharpe 1,285
James Lofton 1,271
Isaac Bruce 1,247
Gary Clark 1,227
Herman Moore 1,191
Lance Alworth 1,108
Art Powell 1,062
Hines Ward 1,047
Anquan Boldin 972
Plaxico Burress 967
Laveranues Coles 964
Andre Reed 960
Antonio Freeman 935
Steve Largent 930
Tony Hill 926
Santana Moss 881
Mark Clayton 849
Bob Hayes 825
Carl Pickens 818
Andre Rison 794
Dwight Clark 793
Randy Moss 775
Mike Quick 746
Stanley Morgan 719
Al Toon 677
Darrell Jackson 645
Mark Carrier 630
Frank Sanders 589
Cris Collinsworth 582
Joey Galloway 481
John Jefferson 400
Harlon Hill 242
Buddy Dial 238
George Sauer 170
David Boston 27
Conclusion: Obviously, there is no way to predict how things will turn out for Brandon Marshall. There haven't been many other players with similar success to Brandon Marshall who changed teams during his successful run. The closest comps are David Boston, Buddy Dial and Braylon Edwards. Boston and Dial were derailed by injuries, and Braylon Edwards who has played enough to use as a predictor for Marshall. When comparing Marshall to other players who came off 500+ yard seasons we see that generally those players will decrease productivity the following season. But when we compare Marshall to other receivers who had sustained success at a young age, we see that these players generally continued to play well through their 20's and is a who's who list of the best WR's in NFL history.
Thursday, January 7, 2010
NFL Parity
(Originally posted 10/21/09)
It seems like every year - especially early in the season - you hear lots of people talking about parity in the NFL. Some years the talk is about how even all the teams are (high parity) and some years the talk is about how many bad teams there are (low parity). This year seems to be a year where there is quite a bit of talk about how parity has disappeared.
After just 6 weeks (some teams have only played 5 games), it is really not reasonable to make a determination about parity. The apparent parity (or lack thereof) this early in the season is going to be strongly related to the NFL schedule. For instance, the New York Giants have played 2/3 of their games against some of the worst teams in the league (Was, TB, KC and Oak) - so their 5-1 record might make the Giants look like a better team than they really are.
So I thought I would take a quick look and see how parity this year compares to other years. I only looked at NFL seasons since the AFL-NFL merger in 1970.
For simplicity's sake, I calculated parity by determining the average games over .500 that each NFL team finished in a given year. For instance, if one team finished 12-4, they were 8 games away from .500. If another team finished 7-9, they were 2 games away from .500. I did this for every team, added them up and then divided by the number of teams. I also normalized the values to a 16-game season for all seasons in which fewer than 16 games were played.
Here are the all-time parity rankings. 1975 comes in as the year with the least amount of parity. In 1975 there were 26 teams in the league and they each played a 14 game schedule. 19 of the 26 teams either won or lost 10+ games that year. There were 3 other teams that either won or lost 9 games (meaning if they played a 16-game schedule that year, there was a decent chance that 22 of the 26 teams would have won or lost 10+ games!).
Here is a graph of the parity trend over time:
Click the image for a larger version.
Now the question is: How does 2009 (so far) compare? If I use the same method to calculate parity for 2009, I will get a parity rating of 7.2 through Week 6, which would tie the 1975 rating. But that's not a fair rating. Right now the NFL sports 9 teams that are either undefeated or winless. A straight extrapolation of records to 16 games means we'd end the season with 9 teams undefeated or winless - we know that won't happen. Instead, I calculated each team's pythagorean record through 16 games to come up with an expected W-L record for each team. A perfect-parity season would be if every team finished 8-8, and the parity rating would be 0. A perfect un-parity season would be if half the teams finished 16-0 and half finished 0-16 (which could probably never happen due to the schedule) and that provide a parity rating of 16.
At the top of the standings, Pythagorus says that the Saints will win 14 games, while the Colts and Broncos will win 13. It also says that the Rams will go 1-15 and the Titans, Browns and Raiders will go 2-14. These seem like reasonable approximations of what could happen - though I'd guess that there will be fewer than 4 teams that win fewer than 3 games.
Using these figures, I come up with a parity rating of 6.3 for 2009 through Week 6, which would be the 4th most un-parity season of all time. It wouldn't surprise me if the actual parity rating for 2009 is fairly high (remember, high rating means low parity), but I suspect it won't be as high as 6.3.
Updates:
Update:
With a full season of data, 2009 finishes with an actual rating of 5.0 (using actual W-L instead of Pythag. The Pythag rating was 5.1) That puts 2009 approximately in the center of the all-time rankings. Also, the all-time average is a parity rating of 5.1 which means that 2009 ends up finishing with a less varied league than average.
Even if the Colts had gone on to a 16-0 season, that would have only bumped 2009 up to 5.1 - right at the all-time average.
So in conclusion, the early-season perception that the league had lots of really bad teams and lots of really good teams was not accurate. It probably had more to do with the way the schedule worked out early on, and maybe a higher than usual number of hot and/or cold teams early.
It seems like every year - especially early in the season - you hear lots of people talking about parity in the NFL. Some years the talk is about how even all the teams are (high parity) and some years the talk is about how many bad teams there are (low parity). This year seems to be a year where there is quite a bit of talk about how parity has disappeared.
After just 6 weeks (some teams have only played 5 games), it is really not reasonable to make a determination about parity. The apparent parity (or lack thereof) this early in the season is going to be strongly related to the NFL schedule. For instance, the New York Giants have played 2/3 of their games against some of the worst teams in the league (Was, TB, KC and Oak) - so their 5-1 record might make the Giants look like a better team than they really are.
So I thought I would take a quick look and see how parity this year compares to other years. I only looked at NFL seasons since the AFL-NFL merger in 1970.
For simplicity's sake, I calculated parity by determining the average games over .500 that each NFL team finished in a given year. For instance, if one team finished 12-4, they were 8 games away from .500. If another team finished 7-9, they were 2 games away from .500. I did this for every team, added them up and then divided by the number of teams. I also normalized the values to a 16-game season for all seasons in which fewer than 16 games were played.
Here are the all-time parity rankings. 1975 comes in as the year with the least amount of parity. In 1975 there were 26 teams in the league and they each played a 14 game schedule. 19 of the 26 teams either won or lost 10+ games that year. There were 3 other teams that either won or lost 9 games (meaning if they played a 16-game schedule that year, there was a decent chance that 22 of the 26 teams would have won or lost 10+ games!).
| Year | Average |
| 1975 | 7.2 |
| 1976 | 7 |
| 1973 | 6.4 |
| 2005 | 6 |
| 1972 | 5.9 |
| 1977 | 5.7 |
| 1991 | 5.7 |
| 1992 | 5.7 |
| 1970 | 5.6 |
| 1986 | 5.6 |
| 1982 | 5.5 |
| 1998 | 5.5 |
| 1990 | 5.4 |
| 2003 | 5.4 |
| 1984 | 5.3 |
| 2000 | 5.3 |
| 2001 | 5.3 |
| 2008 | 5.2 |
| 1971 | 5.1 |
| 2007 | 5.1 |
| 1980 | 5 |
| 1985 | 5 |
| 1974 | 4.9 |
| 2004 | 4.9 |
| 1997 | 4.8 |
| 1979 | 4.6 |
| 1988 | 4.6 |
| 1987 | 4.5 |
| 1996 | 4.5 |
| 1989 | 4.4 |
| 1994 | 4.4 |
| 1999 | 4.4 |
| 1978 | 4.3 |
| 1981 | 4.3 |
| 2002 | 4.3 |
| 2006 | 4.3 |
| 1993 | 4.1 |
| 1983 | 3.9 |
| 1995 | 3.9 |
Here is a graph of the parity trend over time:
Now the question is: How does 2009 (so far) compare? If I use the same method to calculate parity for 2009, I will get a parity rating of 7.2 through Week 6, which would tie the 1975 rating. But that's not a fair rating. Right now the NFL sports 9 teams that are either undefeated or winless. A straight extrapolation of records to 16 games means we'd end the season with 9 teams undefeated or winless - we know that won't happen. Instead, I calculated each team's pythagorean record through 16 games to come up with an expected W-L record for each team. A perfect-parity season would be if every team finished 8-8, and the parity rating would be 0. A perfect un-parity season would be if half the teams finished 16-0 and half finished 0-16 (which could probably never happen due to the schedule) and that provide a parity rating of 16.
At the top of the standings, Pythagorus says that the Saints will win 14 games, while the Colts and Broncos will win 13. It also says that the Rams will go 1-15 and the Titans, Browns and Raiders will go 2-14. These seem like reasonable approximations of what could happen - though I'd guess that there will be fewer than 4 teams that win fewer than 3 games.
Using these figures, I come up with a parity rating of 6.3 for 2009 through Week 6, which would be the 4th most un-parity season of all time. It wouldn't surprise me if the actual parity rating for 2009 is fairly high (remember, high rating means low parity), but I suspect it won't be as high as 6.3.
Updates:
| Through | W-L | Pythag |
| Week 7 | 7.3 | 6.9 |
Update:
With a full season of data, 2009 finishes with an actual rating of 5.0 (using actual W-L instead of Pythag. The Pythag rating was 5.1) That puts 2009 approximately in the center of the all-time rankings. Also, the all-time average is a parity rating of 5.1 which means that 2009 ends up finishing with a less varied league than average.
Even if the Colts had gone on to a 16-0 season, that would have only bumped 2009 up to 5.1 - right at the all-time average.
So in conclusion, the early-season perception that the league had lots of really bad teams and lots of really good teams was not accurate. It probably had more to do with the way the schedule worked out early on, and maybe a higher than usual number of hot and/or cold teams early.
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