The football analytics resource guide – the top 7 killer articles

helmets_football_croppedYou’re interested in how numbers can help you understand football.

Should your coach go for it on 4th down?

Will your team win or cover the point spread?

Analytics will always fight an uphill battle in football. The sport suffers from playing many fewer games than baseball or basketball, making it more difficult to obtain meaningful statistics.

In addition, important players like offensive linemen do not accrue any statistics. Analytics will never make the impact in football as it has in baseball or basketball.

However, we can make progress, especially on the team level.

In no particular order, I summarize the top 7 articles on football analytics, all of which are freely available on the web. Let it guide you towards what we know about our favorite sport.

1. Can a defense force turnovers?

steelers_logoThe Pittsburgh Steelers only forced 2 turnovers through five games of the 2011 season.

Was something wrong with the mighty Steel Curtain? Had star safety Troy Polamalu finally whacked his head into the line of scrimmage one too many times?

The numbers suggest otherwise. Bill Barnwell of Grantland asked whether turnovers forced in the first 5 games can predict turnovers forced the remaining 11 games. Over a huge sample of more than 600 NFL teams, he found no correlation between early and late season forced turnovers.

This lack of correlation implies that turnovers regress to the mean. For a team like the 2011 Steelers, this means they will most likely force an average number of turnovers the remainder of the season.

After Barnwell’s article appeared, the Steelers forced 13 turnovers the remaining 11 games, much closer to the NFL average of 1.6 turnovers per game.

To read Barnwell’s article on turnovers, click here.

2. When should teams go for it on 4th down?

If football analytics sneaks into the mainstream media, the discussion is probably about 4th down decisions.

Brian Burke, the founder of Advanced NFL Stats who now works at ESPN, has done the most complete study on the topic. The analysis is based on expected points, which measures the strength of field position in terms of down and distance.

For example, an offense with a 1st and 10 from the 27 yard line can expect to gain +0.7 points on the next score. Sometimes, they throw a long bomb for a touchdown (+7 for the offense). Other times, the defense returns an interception for a touchdown (-7 for the offense). But the average of the next score is +0.7 points for the offense.

To analyze 4th down decisions, Burke calculates the expected points for punting, kicking a field goal and going for it.

The results are startling.

Coaches should go for it much more often than they do. If fact, unless the offense is under the shadow of its own end zone, a coach should always go for it with 2 yards or fewer.

That’s right, Bill Belichick made the right decision on 4th and 2 on his own 28 against Peyton Manning and the Colts.

Of course, no other coaches are listening to Burke’s advice. Burke explains why at the end of the four part article.

To read this four part study from the beginning, click here. Burke also has a nice graphics that summarizes 4th down decision making at the bottom of the last article.

3. What is the NFL’s most efficient play?

Football's corner 3What is the NFL’s analogue of basketball’s corner 3 point shot?

This question bothered Robert Mays of Grantland, so he enlisted the help of ESPN’s analytics group. They found ample evidence that the play action pass is the most efficient play.

To show this, they looked at expected points added (EPA) for different plays. EPA is the change in expected points, the same concept used by Burke in his 4th down study, on a given play. This statistic acknowledges that 2 yards on 3rd and 1 is worth more than 2 yards on 1st and 10.

Mays and the ESPN quants found that the play action pass earned the highest EPA of all plays. And it wasn’t even close. Running plays lost expected points on average (-0.04 EPA), while passes averaged +0.04 EPA. The play action gained +0.17 on average, 4 times more than the typical pass.

Deception matters in football. On a play action pass, the offense fakes a run, which freezes the linebackers. This frees up space down the field for a big pass play.

Moreover, the data suggests that an NFL team doesn’t need a good run game for effective play action. For example, Minnesota had a strong rush attack with Adrian Peterson. However, the Vikings were only 21st in play action EPA over the last 4 years.

Play action passes are pass plays, and a team needs a good quarterback to make those throws. The top teams in play action efficiency have quarterbacks like Aaron Rodgers and Peyton Manning.

To check the article on football’s corner 3, click here.

4. Do you make these 3 mistakes with college football statistics?

boy_hitting_foreheadYou should never look at college football statistics for passing and rushing on major media sites.

For some reason, sacks count as rushing plays in traditional college football statistics. However, a play that ends in a sack began life as a pass play.

To get an accurate assessment of passing and rushing in college football, you must count sacks as pass plays. This adjustment is not necessary for NFL statistics since sacks do not count as rush plays.

In addition, it’s also important to account for pace and strength of schedule in college football. One of my articles discusses these three important points as well as shows how Stanford in 2012 illustrates the importance of these concepts.

To read my article on 3 mistakes with college football statistics, click here.

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5. The Five Factors in Football

In 2002, Dean Oliver wrote Basketball on Paper, a seminal work that introduced the four factors that affect a basketball game.

Bill Connelly of SB Nation has laid the same foundation for college football. These 5 factors drive success in football:

  • explosiveness
  • efficiency
  • field position
  • finishing drives
  • turnovers

Teams don’t control turnovers, so it could really be football’s 4 factors.

Connelly presents some rich data on how these factors affect winning and uses regression to estimate the importance of each factor.

To read about the five factors in football, click here.

6. The power of simple division in recruiting rankings

It’s easy to dismiss the recruiting complex of college football.

Johnny Manziel was a 3 (out of 5) star recruit who went to Texas A&M. He won the Heisman Trophy in 2013 as a freshman.

Moreover, many highly touted high school players flop at the college level. Over a recent 5 year period, only 42 of 316 college players named to All-American teams arrived on campus as 5 star recruits.

However, these stories and numbers are misleading.

Matt Hinton noted that only 158 high school players were 5 star recruits during the 5 year period (2008-2012). With simple division, 26.6% of 5 star recruits ended up as All-Americans. The success rate at becoming All-American goes down for 4 and lower star recruits.

Simple division is a powerful tool in sports analytics. You don’t need the most modern machine learning algorithm to make an impact in the field.

Hinton’s CBS Sports article also looks at how recruiting rankings fare on the team level. To read the article, click here.

7. How to use sports science to gain an edge in the NFL

When Chip Kelly arrived as coach of the Philadelphia Eagles in 2013, he hired the first sports science coordinator in the NFL.

He plucked Shaun Huls from the Navy Seals. Huls uses technology on players to track heart rate, movement in practice and even electrical signals from the heart. The goal is preventing injuries from too much stress in practice.

The article does not discuss the analytics behind the technology. However, it highlights an important frontier for sports analytics.

To read the full article by Jenny Vrentas of MMQB (Sports Illustrated), click here.