Arrests of NFL Players This Off-Season Are Up 75% From 2012

The shocking news that Patriots star tight end Aaron Hernandez was arrested for the murder of Odin Lloyd has once again raised the question – does the NFL have a crime problem?  Hernandez’ arrest, the tragic murder of Kassandra Perkins by Kansas City Chiefs linebacker Javon Belcher, and the arrest of Dallas Cowboys player Josh Brent, for manslaughter (for the death of his teammate Jerry Brown) are disturbing to all fans.  While these crimes are horrific and disturbing, all NFL players should not be painted with a broad brush.  NFL players are arrested much less often than men age 22 to 34 in the general population.  Nonetheless, the 35 arrests of NFL players in the 2013 off-season are the most in the past decade and represent an increase of 75% relative to the 2012 off-season.

Over the past ten and a half years there have been 534 arrests of NFL players for offenses more serious than speeding (and lesser traffic violations).  These data are based on the San Diego Union Tribune’s arrests database for NFL players and information reported by Fox Sports.  Arrests of NFL players are much more likely to occur (36% higher) in the offseason.  In other words, NFL players are more likely to be arrested between the beginning of February and the end of June than during summer training camps and the NFL season.

On average 0.78 NFL Players are arrested per team per offseason.  The annualized arrest rate for NFL players (during the offseason) has averaged about 3.5% since 2003 compared to 9.9% for all men age 22 to 34 (based on FBI crime data).  However, Commissioner Roger Goodell has reason to be concerned.  As the graph below indicates arrests of NFL players were increasing when Goodell became NFL Commissioner in 2006.  Between 2006 and 2012 off-seasons arrests fell by 37.5%.  It is troubling that off-season arrests in 2013 were 75% higher than in 2012.  NFLCrimes2

All players are not equally likely to be arrested.  There are clear differences in arrests by position:

  • Wide Receivers accounted for more than 1 out of 6 arrests
  • Cornerbacks accounted for about 1 out of 7 arrests
  • Linebackers accounted for 1 out of 8 arrests
  • Punters and Kickers accounted for 1 out of 67 arrests
  • Offensive Guards accounted for only 1 out of 107 arrests

There are also clear differences in arrest rates by team.  Four teams had substantially more arrests than the NFL average of about 1.5 arrests per year.  Arrest rates for the Minnesota Vikings, Cincinnati Bengals and Tennessee Titans are about double the NFL average.  Arrests rates for the New York Jets and San Francisco 49ers are about half of the NFL average.

The distribution of arrests is also skewed across players.  Since 2003, Adam “Pac Man” Jones and Kenny Britt (both of the Tennessee Titans) were arrested 7 times, while Chris Henry (of the Cincinnati Bengals) was arrested 6 times.  16 other players were arrested at least 3 times since 2003.

The arrests of NFL players fell between 2006 and 2012 as Roger Goodell made the reduction of bad off-the-field behavior by players a priority.  It is therefore disappointing to the NFL and its fans that arrests of NFL players are up 75% in the past year.  However, NFL players still have a much lower arrest rate than men of a similar age in the general population.  The horrific crimes allegedly committed by a handful of NFL players since last fall are shocking and disturbing but most players are arrested for much less serious crimes.

Note: For NFL players (and all persons arrested), an arrest is only an arrest and does not mean that the player was guilty of the crime for which he had been arrested.  Many of the charges facing NFL players who were arrested were subsequently dropped.

Note: The FBI reported 2.64 million arrests of men age 22 to 34 in 2011 for offenses more serious than speeding and traffic violations (but including drunk-driving).  The Census Bureau reports that the civilian population of men age 22 to 34 was about 26.6 million in 2010.

What Happened to Defense in the NFL Playoffs?

The NFL has held Divisional Playoffs since 1970.  The playoffs match the top four teams in each Conference.  Until this year the average score in these games has been 28 to 15.  This year the average score was 38.5 to 30.5.  This means that, on average, teams combined to score 69 points per game in  compared to the historic average of 43 points.  In recent years the most successful NFL teams have had strong offenses but weaker defenses.  The past three years have seen three of the four highest scoring Divisional Playoff weekends in history.  In 2010-2011 the 8 teams playing in this round of the playoffs set the previous record by scoring a combined 232 points in four games.

This year the eight teams combined for 276 points.  No team scored fewer than 28 points (the Texans and the Seahawks scored exactly 28).  The San Francisco 49ers scored more points (45) than both teams combined typically score in a playoff game.  The scoring total this year is about 60% higher than the historic average and 19% higher than the previous record set in 2010-2011.

I am not longing for a return to 1970, when both the Cowboys and Colts shut out their opponents (the Bengals and Lions) and a total of 88 points were scored by all teams in the four playoff games.  This weekend’s games were no doubt more entertaining than the Cowboys 5-0 victory over the Lions in 1970.  The rules have changed since 1970 to favor offenses in general and the passing game in particular.  If the best teams in each conference are unable to hold their opponents to under 28 points, perhaps the pendulum has swung too far in favor of NFL offenses.

How Much Parity is there in the NFL? Or Why have the Detroit Lions been such a Bad Team for so Long?

The NFL Divisional playoff games are being played this weekend.  We are down to four teams out of 16 in each Conference.  This is the 43rd year of NFL playoffs in which there were Divisional playoffs leading to a Conference Championship game.  For 41 straight seasons, the “final four” in each Conference differed by at least one team from the previous year.  This year, for the first time, the four teams representing the AFC (Broncos, Patriots, Ravens and Texans) are the same ones that advanced to the AFC Divisional playoffs last year.   Every NFL franchise has advanced to the Divisional playoffs at least once since 1970.  These facts make it appear that there is tremendous parity in the NFL.  Despite the changes in the top four teams in each conference from one year to the next, there is no doubt that some franchises are much more successful than others.

If all 25 of the NFL teams who played every NFL season from 1970-2012 were equally successful, they each would have appeared in the Divisional playoffs 11.9 times.*  The following tables list the six most successful teams in each conference, as measured by appearances in the Divisional playoffs.  The Steelers are the most successful franchise with 22 appearances, closely followed by the 49ers and Cowboys with 21 appearances.  The least successful NFC franchise is the Detroit Lions, who advanced to the Divisional playoffs only three times.  The least successful franchises in the AFC are the Kansas City Chiefs and Cincinnati Bengals, who each advanced to the Divisional playoffs only six times each.

Team Number of Appearances in AFC Divisional Playoffs % of Seasons that Team Appeared in AFC Divisional Playoffs
Pittsburgh Steelers

22

51.2%

Baltimore Ravens

8

47.1%

Miami Dolphins

17

39.5%

Oakland Raiders

16

37.2%

New England Patriots

15

34.9%

Indianapolis Colts

14

32.6%

Team Number of Appearances in NFC Divisional Playoffs % of Seasons that Team Appeared in NFC Divisional Playoffs
Dallas Cowboys

21

51.2%

San Francisco 49ers

21

47.1%

Seattle Seahawks

5

41.7%

Minnesota Vikings

19

39.5%

Washington Redskins

15

34.9%

St. Louis Rams

14

32.6%

The Cowboys and 49ers have advanced to the final four seven times as often as the Lions.  The Steelers have advanced to the Divisional playoffs about 3.7 times more often than the Bengals or Chiefs.  If all franchises were equally matched (on average), each would have advanced to the Divisional playoffs from 10 to 13 times over 43 years.  The vast difference in the success rates of the Steelers, Cowboys and 49ers on one hand, and the Lions, Chiefs and Bengals on the other hand, is far too large to be explained by random chance, or the difference between good luck and bad luck.

Another way to measure NFL parity is from one season to the next.  The following table indicates how often final four teams in each conference repeated from the previous season and compares this distribution to what would be expected if there was complete parity in the NFL.   

Number of final four NFL teams repeating from last season Number of times this many final four teams repeated from last season Fraction of times this many final four teams repeated from last season Fraction of times this many final four teams would repeat with complete NFL parity

0

5

5.8%

29.0%

1

26

30.2%

44.6%

2

34

39.5%

23.2%

3

20

23.3%

2.8%

4

1

1.2%

0.4%

Typically two teams in each conference repeat in the Divisional playoffs from last year but with complete parity it would be much more likely that only one team would repeat in the Divisional playoffs from the previous year.  Thus, even though all four teams have returned to the Divisional playoffs in consecutive seasons only one out of 84 possible times (42 years each for the AFC and NFC) the NFL is far from complete parity.

In my view, the biggest deviation from parity in the NFL is that some franchises, such as the Detroit Lions, have been much less successful than top franchises over more than four decades.  If teams were equally matched, on average, I would expect the top franchises to have about 30% more Divisional playoff appearances than the franchises with the worst records over 40 decades.  The NFL shares most revenue equally, and gives advantages to the teams with the weakest record in each year (better selections in the player draft and play weaker opponents in the following season).  Thus, as opposed to other professional sports, long-run differences in the average success of NFL franchises is due primarily to talent differences among  owners, coaches and general managers rather than differences in payroll across teams.

*Note: Complete parity in the NFL occurs when all 16 teams in each conference are evenly matched and there is no correlation in a team’s performance from one year to the next.   Although there were 26 teams in the NFL in 1970, the Cleveland Browns did not play for three seasons in the late 1990’s after their team moved to Baltimore and became the Ravens.

Does the NFL Have a Crime Problem?

The horrific crimes committed by NFL players in the past ten days have prompted many to ask a logical question: Does the NFL have a crime problem?  The tragic murder of Kassandra Perkins by Kansas City Chiefs linebacker Javon Belcher, who committed suicide in front of coaches and team personnel, cast a pall over last weekend’s games.  This weekend Josh Brent was arrested for drunk-driving and manslaughter for a car accident that killed Cowboys teammate Jerry Brown.  While police are still investigating why Belcher killed the mother of his young daughter and took his own life, Brent had been arrested in college for drunk-driving making the tragic accident that killed Brown even more senseless and depressing.  All NFL players should not be painted with a broad brush, despite the inexcusable actions of Belcher and Brent.  NFL players are arrested about one-fourth as often as men age 22 to 34 in the general population.

Over the past decade there have been 489 arrests of NFL players for offenses more serious than speeding (and lesser traffic violations).  These data are based on the San Diego Union Tribune’s arrests database for NFL players that I update with a recent story by Fox Sports.  On average this amounts to one arrest per 35 players per year, or about 1.5 arrests per team per year.  The arrest rate for NFL players has averaged about 2.9% compared to 10.8% for men age 22 to 34 (based on FBI crime data by age for men in 2009).  Commissioner Roger Goodell is not satisfied with an arrest rate that is merely below the average for men in the U.S.  As the graph below indicates arrests of NFL players were increasing until Goodell became commissioner in 2006.  Since then the number of NFL players arrested per year has fallen by about 40%.

NFL_Crimes

All players are not equally likely to be arrested.  A simple analysis of the arrest data establish a clear difference in arrests by position:

  • Wide Receivers accounted for more than 1 out of 6 arrests
  • Cornerbacks accounted for about 1 out of 7 arrests
  • Linebackers accounted for 1 out of 8 arrests
  • Punters and Kickers accounted for 1 out of 82 arrests
  • Offensive Guards accounted for only 1 out of 98 arrests

There are also clear differences in arrest rates by team.  Four teams had substantially more arrests than the NFL average of about 15 arrests every 10 years.  Over the past decade 36 Minnesota Vikings, 29 Tennessee Titans and 28 Cincinnati Bengals and Denver Broncos have been arrested.  The Arizona Cardinals, New York Jets and San Francisco 49ers had less than half as many arrests as the typical NFL team since 2003.

It should  be emphasized that for NFL players (and all persons arrested), an arrest is only an arrest and does not mean that the player was guilty of the crime for which he had been arrested. 

The serious and tragic crimes committed by NFL players in the past 10 days are shocking and disturbing to sports fans.  However, a closer look at arrests of NFL players shows that they have a much lower arrest rate than men of a similar age in the general population.  Moreover, the arrests of NFL players have fallen by 40% in the past six years as Roger Goodell has made it a priority to reduce bad behavior off the field.  NFL players should not all be judged based on the serious crimes committed by two players.

Note: In 2009 the FBI reported 2.88 million arrests of men age 22 to 34 for offenses more serious than speeding and traffic violations (but including drunk-driving).  the Census Bureau reports that the civilian population of men age 22 to 34 was about 26.6 million in 2010.

The Assignment of Bye Weeks in the NFL

There are 10 NFL Teams that had a bye week, or week off, in the first six weeks of the NFL season.  If bye weeks were allocated at random by the NFL one would expect one-half of the teams to have a winning record in their first five games and one-half to have a losing record.  The Chicago Bears are the only team, however, that has a winning record through five games among these teams to receive an early bye week.  The odds of this occurring at random is about one in one hundred.

Another manifestation of this odd outcome is the excessive parity among the 22 teams that did not have a bye week before this weekend.  Eleven of these teams have three wins and three losses.  Again if bye weeks were allocated at random, only about seven of the teams would be expected to have a .500 record.

The pattern observed this year is not apparent in other NFL seasons and is most likely due to the “luck of the draw” or sampling variation.  It does not seem that the NFL deliberately allocates bye weeks early in the season to weaker teams.  If anything, interest in the NFL is likely to grow during the season so it might make more sense to have the weaker teams take their bye weeks later in the season.

 

Measured Properly, Bears Kicker Robbie Gould is Most Accurate Kicker in NFL History

The National Football League ranks kickers in terms of their field goal accuracy.  All field goal attempts are not equally difficult, however.  An attempt from 52 yards is much less likely to be successful than an attempt from 22 yards.  Fortunately the NFL also maintains records on field goal attempts and successes from distances of 10-19 yards, 20-29 yards, 30-39 yards, 40-49 yards and 50-59 yards.  Using these data it is possible to calculate a measure of field goal accuracy that adjusts for differences in the lengths of the field goals attempted by each kicker.  I have computed these rates for the 12 most accurate kickers of all time and then re-ranked them in terms of “adjusted accuracy”.  The kicker that benefits the most by such an adjustment is the Bears’ Robbie Gould.  Using this preferred measure of field goal accuracy it is clear that Robbie Gould is the best kicker in NFL history.

On average, top kickers attempt roughly equal numbers of field goals from 20-29, 30-39 and 40-49 yard distances (about 30% from each group), 2% from inside the 20 yard line and 8% from 50 yards or beyond.  Gould’s adjusted accuracy moves him above Nate Kaeding and Mike Vanderjagt because the Bears have been less successful than other top teams at getting into the Red Zone since he has been on the team.  Only 26.4% of Gould’s field goals were attempted from inside the 30 yard line compared to 32.0% for Vanderjagt and 36.7% for Kaeding.   The ineffectiveness of the Bears’ offenses over the years means that Gould has attempted more lengthy field goals than his peers.  Gould has NEVER missed a field goal from inside the 30 yard line in his NFL career (now in its 8th season).   Had Gould been able to attempt field goals more similar in length to his peers, he would be considered the most accurate kicker in NFL history.

Oddly, 7 weeks into the 2012 season, Gould and Rob Bironas of the Titans have both attempted 231 field goals and made 199 of them.  Bironas’ adjusted accuracy is 1.2% lower than Gould’s because Bironas has attempted easier field goals than Gould.  Bears fans should petition the NFL to change the way in which field goal accuracy is computed.  Quarterbacks are rated based on completion percentages, yards and other measures of passing proficiency.  There is no reason why NFL kickers should only be evaluated by their completion percentages.

Adjusted Rank Kicker Adjusted Accuracy Unadjusted Rank
1 Robbie Gould 86.96% 3
2 Nate Kaeding 86.86% 1
3 Mike Vanderjagt 86.67% 2
4 Shayne Graham 85.84% 4
5 Rob Bironas 85.76% 5
6 Connor Barth 85.08% 6
7 Garrett Hartley 84.14% 8
8 Ryan Longwell 83.76% 12

Brees, Unitas, Yaz and Cabrera: Comparing Great Performances Across Generations

Last week Miguel Cabrera earned baseball’s Triple Crown, the first one in 45 years, by leading the American League in home runs, runs batted in and batting average.  Within days of that feat Drew Brees broke an NFL record held by Johnny Unitas for 52 years ago.  Brees has thrown for a touchdown pass in 48 straight games.  Brees is an amazing quarterback, but Cabrera’s accomplishment is more impressive.

Football may be the most popular sport in America, but it is impossible to compare individual accomplishments across eras.  Professional football in 2012 does not resemble the game played from 1956-1960 when Unitas completed at least one touchdown pass in 47 straight games.  NFL teams throw 55% more passes per game than they did in 1956 when Unitas began his streak.  Through the first five games of the 2012 season Brees has thrown 236 passes.  This is more than Bart Starr, Bobby Layne, John Brodie, Billy Wade, Eddie LeBaron, Zeke Bratkowski and three other starting quarterbacks attempted through the entire 1960 season.

The short pass has largely replaced the running play in short yardage situations as teams get close to the goal line.   During Brees’ streak 47% of his touchdown passes have been within 10 yards of the end zone compared to 37% for Unitas during his streak.  In addition, 29% of Brees’ touchdown passes have been from the 5 yard line or closer, compared to 22% for Unitas.

Cabrera’s feat displayed an amazing ability to hit for both power and average in an era of more and more specialization in sports.  One of the biggest changes that hitters confront today is that they must face fresh and talented set-up relievers and closers on a daily basis.  In 1967, when Carl Yastrzemski last won the Triple Crown, the typical team had 39 complete games from their starting pitchers and teams generally used a four-man rotation.  Today the average team has four complete games per season.  Hitters today face pitchers who are better rested and more specialized.  A hitter typically will face, within the same game, both right-handed and left-handed pitchers who throw a wider selection of pitches than an individual would be able to master.

There are rule changes in baseball that also make comparisons difficult (but interesting) across eras.  When Yaz won the Triple Crown baseball was in the midst of a pitchers’ era; only four batters in the American League hit better than .300 and the following year Yaz repeated as the leading hitter at .301 with the second place hitter at .290.  Then the mound was lowered and hitters have gained on pitchers for most of the past 40 years.

Nonetheless, Cabrera’s accomplishment may not be repeated by another baseball player for decades.  Brees’ streak will probably continue throughout this season.  It is also likely that other top quarterbacks will challenge his record in the next decade as NFL teams rely more and more on the pass and record books continue to be rewritten every few years.

To Punt or not to Punt: Policy Advice based on Observational Data

Rocky Long, second year head football coach of the San Diego State Aztecs, is facing a problem that is similar, in some respects, to what voters face.  Coach Long may choose to never punt the football once the Aztecs cross midfield, regardless of distance on fourth downs.  He is listening to advice suggesting that the strategies of many previous coaches were wrong.  Coach Long says “We had one of our professors in our business school … go over a system we are thinking about using.  We’ll have a chart come game time that will determine what we do in different situations.”

Voters must decide whether the policies of another Obama Administration will help turn the economy around and contribute to more job creation, or if the Romney campaign proposals will be more successful in achieving these goals.  Football and economic policy advice are both derived from observational, not experimental, data.  It is difficult to know what might happen if alternative policies were to be enacted.  Analysts look to history, in similar circumstances with similar policy options, and hope this provides useful guidance.

Coach Long’s decision apparently follows the strategy of high school coach Kevin Kelley of Pulaski Academy in Little Rock, Arkansas who has been remarkably successful.  But college football is not high school football.  The strategy also appears similar to advice given by Berkeley macroeconomist David Romer, who several years ago found that NFL teams kick surprisingly often on fourth down.

Romer concluded that teams are not pursuing strategies that would maximize their chance of winning the game.  Romer may be correct, but we should be cautious because his study is based purely on observational data.  It is possible that the real world problem is more complicated than the model used to analyze the data.  Whenever economics (or other social science) professors explain that agents motivated by self-interest are making choices not in their self-interest, the professors may have mis-specified their model or may misunderstand the real-world problem that people are attempting to solve.

Romer’s paper is interesting, well written, and well executed.  All of the criticisms raised here are ones that Romer acknowledges, but they aren’t enough to sway his opinion and policy advice.  The data Romer analyzed indicated that NFL teams rarely try for a first down on fourth down.  The primary question is why?  Romer’s explanation is myopia.  An alternative explanation is that a failed fourth down attempt will shift momentum in the game.

The key problem with observational data is that it is difficult to calculate the expected outcome from counterfactual decisions and policies.  Romer argues that teams are not optimizing because he believes they would be successful fairly often on fourth down and two yards to go.  He concludes this despite rarely seeing teams attempting this play.  So how does Romer “guesstimate” the likelihood of success on fourth down and two?  He looks at outcomes of third down plays with two yard to go in the first quarter of games.  He uses first quarter plays because once enough game time has elapsed and the score is uneven, both teams will adjust their game strategies.  He assumes that third down strategies and outcomes are very similar to what would happen on fourth down plays (if they actually were to occur) because he doesn’t have enough data on fourth down plays.  Even if he observed more fourth down plays, they would not be a random or representative sample of teams and/or game situations.  Romer’s assumptions are made out of necessity, not because they are realistic or accurate.

It is also important to note that Romer’s empirical model does not allow for momentum.  The value of having possession of the ball with first down and ten yards to go on a given yard line (say midfield) in his empirical model is completely independent of how one reached that position on the field.  In the language of dynamic programming, the state variables for the optimization problem include down and yardage, but not the sequence of plays leading up to that point.  He imposes this assumption, as good applied economists often do, to make the problem tractable.  He recognizes that momentum could matter and makes some supplemental calculations to show that teams don’t perform much differently immediately after very bad plays (fumbles, interceptions, blocked kicks, and long kickoff and punt returns by the opponent) and just after very good plays (touchdowns) than they do after typical plays.  This is, at best, a half-hearted attempt to determine whether there is momentum in NFL games.  The model simply doesn’t take the idea of momentum shifts seriously, but avoiding these shifts seems to be a key reason why coaches kick field goals rather than go for it on fourth down.

Rocky Long, at San Diego State, may follow the advice of economics and business school professors and forsake the punt.  But he should do so understanding how the policy advice was determined.  It is extremely difficult for economics professors to evaluate counterfactual policies- whether it is a forecast of what will happen if teams ran and passed on fourth down or a “guesstimate” of the 2012 unemployment rate had there been no stimulus package in 2009. 

Asking economics professors, the Congressional Budget Office or other forecasters to evaluate alternative policies and predict what might happen over the next decade also has limited value.  Many of these same professionals either didn’t forecast the recession or underestimated its severity.  Government economists and advisors didn’t know how deep the downturn was until a year or two later when the data came in.  Mis-estimation of the recession in the midst of the downturn is the explanation given for the woefully inaccurate prediction that the stimulus would keep the unemployment rate below 8%.

It is unwise to rely too heavily on economists as authorities on counterfactual policies.  Economists can’t easily determine what would have happened had there been no stimulus, or how the economy might perform if taxpayers earning more than $200,000 were to face higher marginal tax rates.  In fact they struggle to measure output and employment in real-time.  Predictions about hypothetical economic policies are as fraught with error as predictions about fourth down decisions that have rarely been tried in the past.

NFL Replacement Referees are Less Disruptive than the 2011 Player Lockout

Work stoppages are costly to labor and management.  One cost of a strike in professional sports is the diminished quality of play that results from missed practices.  Some teams and players, especially those with less experience, are harmed more by reductions in practice time.  In an earlier blog post I demonstrated that strikes in the NBA are associated with subsequent reductions in the shooting efficiency of players.  This post compares the impact of the NFL player lockout of 2011 to the referee lockout of 2012 on NFL game outcomes.

Itis clear to NFL fans that the replacement referees, used in the first two games of 2012, make more imistakes than experienced referees.  Although the lockout with referees seems to introduce additional noise into game outcomes, it appears that referee errors are largely uncorrelated with teams’ strengths and weaknesses.  In contrast, it appears that the lockout with players favored stronger and more experienced teams.

The player lockout of 2011 drastically reduced the amount of practice time prior to the beginning of the season.  One would expect this to have a larger effect on teams with less experienced players and teams that made more roster and coaching changes prior to the season.  Successful teams are likely to have greater stability in their personnel, have more experience playing as a team, and are less likely to change offensive or defensive coaching philosophies.  Therefore it would not be surprising that a loss in pre-season practice time harmed the weaker teams more than the stronger teams.  This is exactly what happened last year.  Final score differentials in NFL games were unusually high in the first two weeks of the 2011 season, immediately after the lockout.

In contrast there is less reason to expect that the use of replacement referees during the NFL’s lockout with the more experienced referees would tend to favor stronger or weaker teams.  In fact, the final score differentials in the two weeks of the 2012 season are only slightly higher than in earlier seasons despite the use of replacement referees.

The margin of victory in an NFL game includes signals of the opposing teams’ strengths and noise due to luck, player injuries, weather, and other factors.  These factors include the impact of a shortened training camp due to the player lockout in 2011 and the use of replacement referees in 2012.  The following chart shows the mean absolute score differential for games in the first two weeks of the 2009 through 2012 seasons.The mean score differential was 26% higher early in the 2011 season than it was in the first two weeks of the 2009 and 2010 seasons.  Games were more lopsided by about 2.66 points per game in the first two weeks of 2011.  If the team most disadvantaged by the shortened preseason always lost the game, the average impact of lost practice time is a 2.66 points advantage for the winning team.  If missed practices sometimes worked to the detriment of the winning team the average gross effect on scoring would be somewhat larger.  (If the impact of reduced practice time was uncorrelated with team strength the gross impact could be as high as a swing of 5.32 points per game.)  It seems likely that shortened practices altered outcomes by at least 3 to 4 points per game and sometimes worked to the disadvantage of the team that ultimately won the game.

In contrast there is a much smaller difference between the average margin of victory/loss between the 2009 and 2010 seasons and the first week of 2012.  Although replacement referees have affected the calls on the field, their impact on the typical score differential is only 41% of the increase caused by the players lockout.

Work stoppages and strikes are costly.  The 2011 player lockout caused game outcomes to be more uneven.  Weaker teams with more rookies and roster changes seemed to be harmed more than successful veteran teams by the lockout of players and loss of practice time.  The impact of the strike may have been as high as a swing of 3 to 4 points per game, on average.  In contrast the use of replacement referees in 2012 increased final score differentials by much less.

Alabama and Stanford Provided the Most Valuable Talent to the NFL in the 2012 Draft

Many NFL teams use the relative valuation of draft selections established by the Dallas Cowboys to evaluate possible trades for “moving up” or “moving down” in the draft.  According to the Cowboys’ chart, the top pick in the draft is worth more than 5 times as much as the first pick in the second round (the 33rd pick) and ten times as much as the first pick in the 3rd round (the 65th selection).  The value of players declines exponentially because there are more substitutes for less skilled players and the NFL imposes a minimum salary schedule.

These values can be used to determine which positions are expected to provide the NFL with the most valuable talent in the just completed 2012 Draft.  The following chart shows that quarterbacks, wide receivers, defensive ends and cornerbacks, despite representing less than one third of a team’s positions, are expected to provide almost half of the value in the draft.  This is a clear indication that the NFL has become a pass first league.

Position Share of Draft Value Share of Players Selected
Quarterback

14.12%

4.35%

Wide Receiver

13.14%

13.04%

Defensive End

10.26%

7.51%

Cornerback

10.17%

11.86%

Defensive Tackle

10.10%

9.88%

Offensive Tackle

8.19%

7.11%

Running Back

7.95%

7.51%

Offensive Guard

6.00%

8.30%

Outside Linebacker

5.83%

9.09%

Safety

5.46%

7.91%

Inside Linebacker

5.02%

3.56%

Tight End

2.20%

4.35%

Offensive Center

0.90%

1.98%

All Other Positions

0.66%

3.56%

The chart also shows that quarterbacks are selected much earlier in the draft (their share of draft value is more than three times their share of players selected) than other positions.  Safeties, inside linebackers, tight ends and centers are selected later, on average, than other positions.

The draft values used by NFL teams also can determine which college teams provided the NFL with the most valuable talent in expected value terms) in the 2012 draft.  Alabama had the most players selected (8 out of 253) and are expected to be the source of almost 10% of the value of the 2012 draft.

Position Share of Draft Value Share of Players Selected
Alabama

9.85%

3.16%

Stanford

7.86%

1.58%

Baylor

5.84%

1.98%

LSU

5.34%

1.98%

South Carolina

4.41%

2.37%

USC

4.12%

1.19%

Oklahoma State

4.11%

1.19%

Illinois

3.62%

1.58%

Notre Dame

3.05%

1.58%

Boise State

2.80%

2.37%

College football players were drafted out of 105 different colleges and universities.  The ten schools listed above accounted for 19% of the players and 51% of the value of the talent in the draft.  Only twenty schools accounted for 32.4% of the players and 71.5% of the value in the draft.

The pattern of players selected in the draft emphasizes the high value that NFL General Managers place on both passing offense and defense.  It is difficult to forecast the value of professional football players based on their performance in college and the NFL combine.  Many of the quarterbacks selected in the 2012 draft will underperform relative to expectations, while others will outperform quarterbacks selected ahead of them.  An NFL  team, such as the Miami Dolphins, is willing to take a big chance in the draft on a quarterback because the right player can elevate a team’s performance and profitability for a decade.

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