How do the markets rank Green Bay without Aaron Rodgers?

Green Bay has been without QB Aaron Rodgers for 3 games, which lets us get a market estimate of his worth. We’ll do this through my market rankings which take closing point spread and adjust for schedule with my ranking algorithm.

After week 6, the markets rankings had Green Bay 5th in the NFL, with a rating of 3.9 points. This implies Green Bay would beat the average NFL team by about 4 points on a neutral field.

These current NFL market rankings only consider the 3 games for Green Bay since Rodgers got hurt.

1. New England, 8.07
2. Atlanta, 6.33
3. Pittsburgh, 4.71
4. Dallas, 4.49
5. Kansas City, 4.38
6. Seattle, 3.75
7. Philadelphia, 2.53
8. Los Angeles Rams, 1.98
9. Carolina, 1.84
10. New Orleans, 1.72
11. Tennessee, 1.52
12. Oakland, 1.20
13. Denver, 1.11
14. Minnesota, 0.99
15. Cincinnati, 0.01
16. Los Angeles Chargers, -0.05
17. Tampa Bay, -0.06
18. Baltimore, -0.12
19. Jacksonville, -0.19
20. Detroit, -0.67
21. Buffalo, -0.85
22. Washington, -1.04
23. Arizona, -1.32
24. New York Giants, -2.19
25. Houston, -2.22
26. Miami, -2.55
27. Chicago, -3.85
28. New York Jets, -4.55
29. Green Bay, -5.57
30. San Francisco, -6.21
31. Indianapolis, -6.21
32. Cleveland, -7.31

According to the markets, Green Bay has dropped into the bottom 5 of the NFL. They would now be expected to lose by 5.6 to the average NFL team on a neutral field.

While this 9.6 point drop seems too large for me, it does roughly explain the point spread against Baltimore. Giving 2.5 points for home field to Green Bay, these market rankings imply that Baltimore should be about a 3 point road favorite. The markets favor Baltimore by 2.

Members of The Power Rank have access to ensemble predictions that include these market rankings. To get a free sample of these predictions for both college football and the NFL, sign up for my free email newsletter.

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Podcast: Peter Jennings on analytics for Daily Fantasy Sports

On this episode of The Football Analytics Show, Peter Jennings, two time world champion at Daily Fantasy Sports (DFS) and cofounder of Fantasy Labs, joins me for a wide ranging discussion on analytics for DFS. Among other topics, we discuss:

  • An advantage his background in poker gave him in DFS
  • The times of year with the most value in DFS versus the times you’re stuck playing other professionals
  • How to use the markets to gain an edge
  • The sport he watches to gain an edge, and the sport he avoids watching
  • Whether strategy or analytics is more important for the beginning player

After listening to the interview, it won’t surprise you how much success Peter has had in playing DFS and starting Fantasy Labs.

After the interview, I discuss my new research on college football bowl pools. Is there value in these contests? Listen at 32:29.

To listen on iTunes, click here.

College football playoff probabilities after week 11, 2017

Three teams have become the favorites to make the College Football Playoff: Oklahoma, Clemson and Alabama.

Don’t count out Notre Dame. The Fighting Irish got smoked by Miami in week 11, but they can still make the playoff if they win their remaining games against Navy and Stanford.

It helps Notre Dame’s playoff probability that they don’t play in a conference championship game. They can’t lose and fall that final week of the season.

However, my methods do account for the possibility that a team like Ohio State wins a conference championship game and jumps ahead of Notre Dame. There’s no certainty for the Fighting Irish.

Miami moved up into the top 4 of the committee rankings with their big win over Notre Dame. However, they will be 4.5 point underdog in the ACC championship game to Clemson, and it’s unlikely both teams make the playoff.

How Line Yards Divides Credit on Running Plays based on Michigan, 2017

How should you divide credit between the offensive line and running backs on rush plays? One method is Line Yards, a metric developed by Football Outsiders to capture the contribution of the line.

Based on regression analysis, the Line Yardage formula takes all running back carries and assigns responsibility to the offensive line based on the following percentages:

  • Losses: 120% value
  • 0-4 Yards: 100% value
  • 5-10 Yards: 50% value
  • 11+ yards: 0% value

The offensive line gets full credit for the first 4 yards of any run, but half credit for the next 6 as the running back gets past the defensive line. The running back gets full credit beyond 10 yards.

To give a football example of how this works, consider the line yards per carry for Michigan through week 10 for the 2017 season.

  • Florida: 2.86
  • Cincinnati: 2.55
  • Air Force: 2.68
  • at Purdue: 2.41
  • Michigan State: 3.19
  • at Indiana: 3.23
  • at Penn State: 3.48
  • Rutgers: 3.62
  • Minnesota: 3.54

Michigan struggled early in the season against teams like Air Force and Purdue. But since the Michigan State game, Michigan’s run blocking has improved by line yards per carry.

The last two games show how line yards breaks down the contribution between the offensive line and running backs.

Against Rutgers, Michigan had 3.62 line yards per carry. They rushed for 334 yards on 6.55 yards per carry (numbers do not include sacks, although Michigan didn’t allow any against Rutgers).

Michigan had slightly worse line yards per carry against Minnesota: 3.54 compared to the 3.62 against Rutgers. However, the offense rushed for 394 yards on 11.59 yards per carry, an astounding rate.

The line yards gives about the same credit to the Michigan’s offensive line against both Rutgers and Minnesota.

The running backs get the extra credit against Minnesota, as Karan Higdon (47, 77 yards) and Chris Evans (60, 67 yards) both broke long runs. In contrast, Michigan’s longest runs were 49 and 32 against Rutgers.

Podcast: Kevin Cole on points added for NFL players

On this episode of The Football Analytics Show, Kevin Cole, a data scientist for football predictions, joins me to discuss his points added model for NFL skill players. Check out his work over at his site Predictive Football.

Among other topics, we discuss:

  • How the data on air yards, or how far the ball travels in the air, allows Kevin to break down contributions between quarterback and receiver
  • How one might use this calculation to adjust for injuries
  • The distinction between quarterbacks and running backs by points added
  • Why Bills QB Tyrod Taylor is rated so highly
  • Why Baker Mayfield could be a historically great QB prospect

After the interview, I have my own segment on the total in Oklahoma State at Iowa State. There’s an intriguing story why it’s so low. Listen at 31:58.

To listen to this episode on iTunes, click here.

To listen here on the site, click on the right pointing triangle.