THE POWER RANK

Podcast: Michigan at Ohio State

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thefootballanalyticsshow_cover_landscapeThis week, I focus on Michigan at Ohio State, a critical game in the college football playoff picture. After looking at all the numbers, the game boils down to which team can run the ball, because both teams will find it extremely difficult to throw.

I end with a prediction for Michigan at Ohio State, and then jump into college football upset alert. You might laugh at one of the picks, but hey, I’m here to entertain.

I end with a college football total that just might make one of our picks in the prediction service.

To listen to the podcast on iTunes, click here.

To listen here, click on the play button.

Warning: Don’t think Michigan should be too big a favorite over Michigan State

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harbaugh_streetsMichigan travels to Michigan State this weekend in a game with two program headed in opposite directions.

Michigan has blossomed in Jim Harbargh’s second year as coach. The defense has excelled as the Wolverines have dominated every game except Colorado and Wisconsin.

In contrast, Michigan State started the year 12th in the AP Poll but have lost their last 5 games. It’s not a surprise the offense has declined with the departure of key talent from last year. But the drop off on defense led by Malik McDowell has been a shock.

So what will happen on Saturday in East Lansing? As of Tuesday afternoon, the markets favor Michigan by 23 point.

This point spread is too large. Let me explain.

The curse of small sample size

Some type of analytics give a spread even larger than 23.

For example, consider my rankings algorithm that takes margin of victory and adjusts for strength of schedule. Using only games from this season, this method makes Michigan 32 points better than Michigan State. With home field for the Spartans, this gives a predicted point spread of 29 points.

However, this prediction considers only 7 or 8 games for each team, and it’s dangerous to draw conclusions based on small sample size. In addition, randomness can affect the margin of victory through plays like turnovers, as Michigan State has a -4 turnover margin this season.

To get a better assessment of the right point spread for this game, let’s consult other sources of data.

Adjusted Yards Per Play

At The Power Rank, I also rank teams based on yards per play, a powerful efficiency metric that captures the ability of the offense to move the ball and the defense to prevent this movement. The same ranking algorithm takes data from each game and adjusts for strength of schedule.

By adjusted yards per play, Michigan State ranks 38th in the nation. While not stellar, the Spartans look much better by yards per play than adjusted margin of victory (90th).

To explain the discrepancy between yards per play and margin of victory, we consult Bill Connelly’s data on finishing drives. By points per trip inside the 40, Michigan State ranks 94th and 89th on offense and defense respectively.

The Spartans haven’t been clutch this season. However, this could change any week, as an offense ranked 34th in adjusted yards per play will almost certainly finish drives better than they have so far this season. And the defense overall should be better than their rank of 62nd by adjusted yards per play.

Michigan is 5th in team rankings based on adjusted yards per play, and this suggests they should be favored by about 10 points.

Market rankings

The betting markets provide another way to evaluate teams. This year, I started applying my ranking algorithm to closing point spreads in the markets to rank teams. Just like with the team rankings, each team gets a rating that gives an expected margin of victory against an average FBS team on a neutral site.

In these market rankings, I weight recent games much more than games earlier this season. For example, the spreads in week 1 get only 3% of the weight of this past week’s games.

This bias should favor Michigan, as they have improved from preseason expectations. In addition, they got an extra bump last week as a 40 point favorite against an Illinois team starting their 3rd quarterback.

The weight towards more recent games should also hurt Michigan State, as the markets have adjusted to their decline. The Spartans would have been more than a 3 point favorite at Maryland last week if the game had been earlier this season.

However, the market rankings predict a 9.5 point win for Michigan at Michigan State.

Ensemble Prediction

Members of The Power Rank have access to ensemble predictions that combine the factors discussed here with other calculations. These predictions have gone 53.7% (217-187 with 8 pushes) against the closing spread this year.

My member prediction has Michigan by 10.7 points over Michigan State. That seems low to me based on the play I’ve seen from both teams this year, and I could see Michigan covering more than 20 points.

However, if you think Michigan will one hundred percent dominate this game, don’t underestimate the randomness of college football.

Michigan State might play above their true talent in this game, as Mark Dantonio hasn’t suddenly become a terrible football coach the last 8 weeks. Throw in an ill timed turnover from Michigan, and it could be a close game on Saturday.

The Ultimate Guide to College Football Conference Win Probabilities

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Will your college football team win a conference title in 2016? Which teams will win the Power 5 conferences, giving them the inside track towards a College Football Playoff berth?

Unlike the typical college football publication, I won’t pick a single team to win each conference. Every team has some chance to win, even Kansas, and modern sports analytics can assign each team a conference win probability.

These numbers come from my preseason college football model, which considers team performance over the past four years, turnovers and returning starters to rank all 128 FBS teams. This model predicted the winner in 73.3% of games last season, a win rate that only includes games with two FBS teams.

This preseason model gives a win probability for each game this season, and these numbers drive my win total predictions at The Power Rank.

These win probabilities also provide the parameters for simulating each conference 10,000 times with random numbers. Each simulation determines the division winners through tiebreakers, and then flips another coin to determine the outcome of the championship game. These simulations give the win probabilities below, which I compare with the market odds from Bovada.

Let’s look at the numbers and story lines for each Power 5 conference.

SEC

sec

Is Tennessee the new beast in the SEC East?

Despite 4 losses last season, Tennessee played close games with Alabama and Oklahoma and never lost by more than a touchdown. The Vols finished last season 8th in my team rankings, which take margin of victory in games and adjusts for strength of schedule.

This season, Tennessee should fully see the fruits of strong classes Butch Jones recruited in 2014 and 2015. My preseason model ranks the Vols 7th and gives them a 44.8% chance to win the East despite a difficult cross division game with Alabama.

Tennessee’s strong chances to win the East reflect poorly on the other programs in the division.

  • Georgia hired a coach (Kirby Smart) who has never been a head coach.
  • Florida looked on the rise last season under Jim McElwain before getting demoralized by Florida State, Alabama and Michigan to end the season.
  • Steve Spurrier left South Carolina mid-season, and the Gamecocks replaced him with Will Muschamp, who never got the job done in four years at Florida.
  • Missouri won the SEC East in 2013 and 2014 but appear in rebuilding mode after the retirement of Gary Pinkel.

My model doesn’t like the prospects of these usual contenders for the SEC East crown, which enhances the odds for Tennessee. The story changes if Tennessee played in the SEC West.

My numbers rank Ole Miss right behind Tennessee at 8th in the nation. However, with Alabama (#1) and LSU (#3) ahead of them, Ole Miss has a 8.7% chance to win the division.

The lack of power balance also favors Tennessee in the overall conference odds. My preseason model would make LSU a 2.5 point favorite over Tennessee in the SEC title game. However, because they play in a weaker division, Tennessee has a better probability of winning the SEC than LSU.

SEC East

Tennessee (#7) has a 44.8% chance to win.
Georgia (#16) has a 28.4% chance to win.
Florida (#28) has a 12.2% chance to win.
South Carolina (#34) has a 8.0% chance to win.
Vanderbilt (#44) has a 4.0% chance to win.
Missouri (#52) has a 2.2% chance to win.
Kentucky (#83) has a 0.3% chance to win.

SEC West

Alabama (#1) has a 45.1% chance to win.
LSU (#3) has a 27.7% chance to win.
Mississippi (#8) has a 8.7% chance to win.
Arkansas (#12) has a 8.3% chance to win.
Texas A&M (#10) has a 5.6% chance to win.
Mississippi State (#23) has a 3.5% chance to win.
Auburn (#32) has a 1.1% chance to win.

Big Ten

bigten

A year ago, Ohio State was the toast of college football. Urban Meyer’s team had won the first playoff, and he was killing it as usual on the recruiting trail.

Then in the most inexplicable game of 2015, Ohio State lost to Michigan State, a team without star QB Connor Cook. The loss cost the Buckeyes a spot in the playoff, and they lost 10 players to the first 3 rounds of the NFL draft.

In contrast, Michigan had many unanswered questions a year ago. They went 5-7 the previous season, and their hopes for 2015 rested on their faith in new coach Jim Harbaugh.

Michigan had a few rough spots in 2015, including a demoralizing 42-13 home loss to Ohio State. However, they finished 10-3 after a convincing win over Florida in a bowl game, and Harbaugh landed a top 5 recruiting class in February.

How do Ohio State and Michigan compare in 2016?

My numbers imply a dead heat between Ohio State and Michigan in 2016. Michigan (#9) is ranked ahead of Ohio State (#11) but would be a 2.5 point underdog when they travel to Columbus in November.

However, Michigan does have a better chance to win the Big Ten East (37.8% vs 34.9% for Ohio State) due to an kinder cross division schedule. Both teams play Wisconsin, but Michigan gets Iowa (#36) and Illinois (#88) while Ohio State tangles with Nebraska (#25) and Northwestern (#58).

In the Big Ten West, it might seem strange to that Nebraska has the highest conference win probability. However, the Huskers went 1-5 in games decided by a touchdown or less, which included a loss to BYU on a Hail Mary. A turnover margin of -12 didn’t help either.

Luckily for Nebraska, my research shows that their record in close games and turnover margin most likely improve in 2016. QB Tommy Armstrong returns, and Nebraska could be really good if they can fix their porous pass defense.

However, the real reason Nebraska has the highest odds to win the Big Ten West is Wisconsin’s schedule. After two years of playing Rutgers and Maryland in cross division games, the Badgers get Ohio State, Michigan and Michigan State. Nebraska also plays Ohio State but gets Indiana and Maryland. Advantage Nebraska.

And I guess we should discuss defending Big Ten West champion Iowa. The Hawkeyes had a magical season last year, but quickly regressed in the Rose Bowl against Stanford. My numbers give them a 19.3% chance to win the division, much less than the even odds in the markets.

Big Ten East

Michigan (#9) has a 37.8% chance to win.
Ohio State (#11) has a 34.9% chance to win.
Michigan State (#29) has a 19.0% chance to win.
Penn State (#43) has a 5.7% chance to win.
Indiana (#67) has a 1.4% chance to win.
Maryland (#78) has a 0.7% chance to win.
Rutgers (#84) has a 0.5% chance to win.

Big Ten West

Nebraska (#25) has a 34.2% chance to win.
Wisconsin (#22) has a 31.1% chance to win.
Iowa (#36) has a 19.3% chance to win.
Minnesota (#60) has a 7.7% chance to win.
Northwestern (#58) has a 4.8% chance to win.
Purdue (#76) has a 2.5% chance to win.
Illinois (#88) has a 0.5% chance to win.

Pac-12

pac

My numbers understand some of the hype surrounding the Washington Huskies. They return 15 starters from last season, including 7 players on a defense that ranked 9th by my adjusted yards per play.

The subjective adjustments also seem to favor Washington, as QB Jake Browning returns as a sophomore after a promising freshman season. Coach Chris Petersen enters his third year and might find the same success he had at Boise State.

But it’s pure insanity to make Washington the Pac-12 favorite, as the markets have them in early August.

While Washington showed promise last season, they finished 7-6 and 31st in my team rankings that take margin of victory and adjust for schedule. Not exactly playoff material.

Last season, Washington had one signature win, a 17-12 win at USC. However, it almost doesn’t count, as USC coach Steve Sarkesian got fired the next week and possibly wasn’t sober while preparing for the Huskies.

Washington has yet to prove itself on the field, which makes it difficult to think they’ll win the Pac-12 North over proven teams.

  • Stanford has to replace their QB and fill holes on both lines, but they still have this guy named Christian McCaffrey.
  • Even though they’re replacing the quarterback, Oregon has most of its weapons back on offense. And the defense can’t get worse, can it?

My numbers like Stanford (35.8%) and Oregon (21.4%) over Washington (10.1%) to win the Pac-12 North.

In the Pac-12 South, the odds makers might be overlooking Utah. It’s not just that Kyle Whittingham has the Utes back on the rise with stellar play on defense. It’s the schedule.

When the Pac-12 split into two divisions, UCLA and USC wanted to keep their rivalries with Stanford and California. However, this has implied a more difficult schedule for all four of these teams.

USC gets the worst of it this season, as they not only play their two northern California rivals but also Oregon. The Trojans always have talent. However, Clay Helton went an uninspiring 5-4 as interim head coach last season, so there’s reason to doubt his ability to get this talent to play at a championship level.

UCLA catches a break in getting Oregon State as their third cross division game. In addition, I think my numbers underestimate Jim Mora’s team this year. My preseason rankings are based on their team rank of 41st last season, but this seems inconsistent with an offense and defense that ranked 27th and 14th last season by my adjusted yards per play.

My numbers make Utah the favorite in the Pac-12 South because they play Oregon State, California and Oregon in cross division games. If the offense can get better with new personnel, Utah could become a legitimate Pac-12 contender.

Pac-12 North

Stanford (#6) has a 55.1% chance to win.
Oregon (#18) has a 21.4% chance to win.
Washington State (#30) has a 11.8% chance to win.
Washington (#26) has a 10.1% chance to win.
California (#56) has a 1.5% chance to win.
Oregon State (#87) has a 0.1% chance to win.

Pac-12 South

Utah (#24) has a 35.8% chance to win.
USC (#19) has a 29.9% chance to win.
UCLA (#37) has a 15.9% chance to win.
Arizona (#38) has a 12.3% chance to win.
Arizona State (#53) has a 4.9% chance to win.
Colorado (#77) has a 1.3% chance to win.

ACC

acc

It seems like Clemson should win the ACC over Florida State in 2016.

Clemson beat Florida State on their way to the national title game against Alabama. Despite the 5 point loss against Bama, you could argue Clemson should have won. They dominated the line of scrimmage but couldn’t overcome blown coverages in the secondary.

However, my preseason ranking like Florida State, as the Seminoles rank 2nd over Clemson at 5th. The returning starters variable plays a critical role in this rank.

Florida State has 17 returning starters, which includes star running back Dalvin Cook. In contrast, Clemson returns only 12 starters. The Tigers also had heavy attrition in the secondary, including 3 players that got drafted by the NFL.

In addition, while Clemson beat Florida State by 10 last year, it was a closer game than the final score indicated. Florida State had more yards per play than Clemson. The Seminoles couldn’t overcome a 2 for 12 rate in converting third downs.

However, Clemson might have the trump card. They bring back Deshaun Watson, the best quarterback in the nation. Florida State is still deciding between returning starter Sean McGuire at QB or a few younger players.

In the Coastal division, the markets have the same odds for Miami as for defending champion North Carolina. This shows major respect for new Hurricane coach Mark Richt, who won 145 games in 15 season at Georgia.

My numbers, which do not consider the coaching change, give Miami the fourth largest win probability for the Coastal division.

ACC Atlantic

Florida State (#2) has a 53.3% chance to win.
Clemson (#4) has a 31.3% chance to win.
Louisville (#14) has a 13.9% chance to win.
Boston College (#55) has a 0.6% chance to win.
North Carolina State (#59) has a 0.4% chance to win.
Syracuse (#64) has a 0.4% chance to win.
Wake Forest (#73) has a 0.2% chance to win.

ACC Coastal

North Carolina (#20) has a 37.3% chance to win.
Virginia Tech (#31) has a 25.0% chance to win.
Pittsburgh (#33) has a 16.4% chance to win.
Miami (FL) (#40) has a 10.2% chance to win.
Georgia Tech (#47) has a 6.7% chance to win.
Duke (#75) has a 2.3% chance to win.
Virginia (#72) has a 2.1% chance to win.

Big 12

big12

Can any team topple Oklahoma from the top of the Big 12?

Bob Stoops has had consistent success as coach at Oklahoma. Only once in his 17 years have the Sooners finished the season outside the top 25 in my team rankings (2005).

Stoops has had his bad years. In 2014, Oklahoma went 1-3 in games decided by a touchdown or less and had an 8-5 record. However, despite an embarrassing bowl loss to Clemson, they still finished 15th in my team rankings.

My preseason model that looks over the past four years appreciates this type of consistency, and it ranks Oklahoma 5th. They could slip like they did in 2014. But with QB Baker Mayfield back, don’t count on it.

The Big 12 win probabilities do not consider the departure of Baylor coach Art Briles. There should be some type of adjustment downward for the Bears. They have one starter returning on both the offense and defensive lines, which suggests they might regress even with Briles as coach.

The team most likely push Oklahoma is TCU. Gary Patterson had the 17th ranked defense by my adjusted yards per play despite a rash of season ending injuries. With the return of a few of these players, who do not count towards the number of returning starters, TCU’s defense should be elite.

On offense, TCU lost almost all of their skill players on offense. However, they will reload with Texas A&M transfer Kenny Hill at quarterback.

How many conferences will my numbers get right?

The Power Rank’s preseason model predicted the game winner in 73.3% of games in 2015. Despite appearances, it is possible to make accurate game by game college football predictions right now.

However, that doesn’t imply we know which teams will win their conferences with any certainty. Teams play a small sample size of 8 or 9 games to determine a champion, which provides an opportunity for teams to steal a conference title.

It only takes one game. In 2015, Michigan State traveled to Ohio State without QB Connor Cook. The markets made the Spartans more than a two touchdown underdog. Michigan State won the game anyway, and this one loss eliminated Ohio State from Big Ten title contention.

For the Power 5 conferences, no team has better than a 50% chance to win their conference by my numbers. Oklahoma has the highest odds at 47.6%, a number that could be higher because of the coaching changes at Baylor.

This means that if three of my predicted champions actually win, I would have benefitted from some good fortune in making my predictions. This leaves plenty of room for surprise teams to make a run at the College Football Playoff, just like Michigan State in 2015.

How many games will Michigan win in 2016?

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This is an excerpt from The 2016 College Football Win Totals Report, which has my predictions for all 128 bowl subdivision teams. For more information, click here.

A preseason rank of ninth might seem low to Michigan fans.

The defense returns almost every significant starter from last season. If this unit does not end the season in the top ten by my adjusted yards per play, it would be a disappointment.

There’s also the Jim Harbaugh factor. My preseason model looks at a four year window of team ratings. While this usually gives an accurate assessment of team strength, it will underestimate a team on a rapid rise.

stanford_harbaugh

Michigan does have some questions to answer. The quarterback battle will get the headlines, but the offensive line might be even more critical for a team determined to impose its will at the line of scrimmage.

In addition, Michigan had exceptional special teams last season. Jabrill Peppers will still return kicks this season, but special teams coach John Baxter left for USC during the off season.

Michigan will start the season higher than ninth in the preseason AP and Coaches polls. Since these preseason human polls are surprising predictors of team strength, this suggests my predicted win total of 9.4 games might be low.

Get college football win totals for all 128 teams

You can look at my predictions in The 2016 College Football Win Totals Report. Here’s what you get:

  • A win total for all 128 bowl subdivision teams.
  • The hidden factor that makes accurate preseason college football predictions possible.
  • 3 surprising teams based on expected win total.
  • Which human polls to trust in making predictions. The answer might surprise you.

You can get this report by signing up for my free email newsletter.

But that’s not all you get. Each week during the season, the newsletter contains a sample of my best college and pro football predictions usually reserved for paying members of the site.

To get The 2016 College Football Win Totals Report and in season predictions, enter your email and click on “Sign up now!”








Finally!! College football preseason rankings for 2016

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ncaaf2016_preseasonWhich college football teams will dominate in 2016?

Which teams will have value in the market for win totals?

It might seem difficult to answer such questions before the season begins. College football relies on the ungainly actions of hormonal young men. Throw in the randomness of a bouncing football, and it seems unpredictable.

However, it is possible to make accurate preseason college football predictions. My preseason rankings come from a regression model that considers team performance, turnovers (both over the past four seasons) and returning starters.

The visual shows the top teams, while the list at the bottom gives all 128 bowl subdivision teams.

How to construct a simple preseason model

For team performance, I use my college football team ratings. These numbers come from taking margin of victory in games and adjusting for strength of schedule with my proprietary algorithm.

Team performance tends to persist from year to year, as Alabama and Rice will never trade places in the college football hierarchy. Hence, the four years worth of team ratings makes up the most important input into the model.

While turnovers can greatly impact a team’s rating, turnovers tend to be random from year to year. If a team has 20 more take aways than give aways during the season, they most likely over performed in their rating. The model uses turnovers to adjust this rating down to better estimate the true strength of the team.

Finally, teams with many returning starters tend to perform better the following season. When only 6 starters return due to early exits to the NFL draft (Ohio State in 2016), we expect a dip in team performance.

How well does the preseason model predict games?

The regression model doesn’t account for every factor in evaluating a college football team. For example, it fails to consider whether the starting quarterback returns for this season.

Despite these flaws, the preseason model picked the winner in 73.3% of games during the 2015 season. This only includes games between two bowl subdivision teams, excluding the cupcake games with FCS teams.

Don’t expect the model to work quite that well again. The firing of Baylor coach Art Briles alone might screw up its predictive ability, and I always encourage you to make subjective adjustments based on situations.

However, the model should be solid in 2016. Over the past three seasons, the preseason rankings has predicted the winner in 71.7% of games (1519-599 with no predictions in 144 games).

Get the college football win totals report

These preseason rankings also drive my college football win totals, which I make available to those who sign up for my free email newsletter. To sign up, enter your best email and click on “Sign up now!”








Let’s look at 3 stories based on these preseason rankings that jump out at me.

Michigan vs Ohio State

In August of 2015, Ohio State was the toast of college football. Urban Meyer’s team had won the first playoff, and the preseason chatter revolved around his success on the recruiting trail.

Then in the most inexplicable game of 2015, Ohio State lost to Michigan State, a team without star QB Connor Cook. The loss cost the Buckeyes a spot in the playoff, and then 10 Buckeyes got drafted in the first 3 rounds of the NFL draft.

In contrast, Michigan had all kinds of question in August of last year (2015). They were coming off a 5-7 season, and all hopes rested on incoming coach Jim Harbaugh.

Michigan ended the season with a surprising 41-7 win over Florida during bowl season. Harbaugh crushed it on the recruiting path, landing top recruit Rashan Gary and a top 5 class.

Now, heading into 2016, many believe that Michigan is a much better team than Ohio State. There are numerous reasons to doubt this.

  • Ohio State beat Michigan in the Big House 42-13 last season.
  • Ohio State’s recruiting over the past four years has outpaced Michigan according to my numbers.
  • Michigan has questions at QB and offensive line heading into 2016.
  • Ohio State has to replace many starters, but one of them is not QB J.T. Barrett.

My preseason model has Michigan a slim half a point ahead of Ohio State. It’s too close to call, and Michigan travels to Columbus to play the Buckeyes this year.

Stay tuned for my Big Ten East win probabilities.

Can LSU contend for a national title?

Last year, Les Miles almost lost his job. LSU lost three straight SEC West games, and the Mad Hatter looked like a goner.

The LSU administration then suddenly changed course, announcing they would retain Miles after an LSU win over Texas A&M. This might actually make sense, since Miles has averaged over 10 wins per season despite playing in college football’s best division.

Now, LSU checks in at 3rd in my preseason rankings, a clear contender for the SEC West and playoff spot. Let’s look at the top reasons.

  • Leonard Fournette
  • 9 starters back on both sides of the ball
  • The hiring of coordinator Dave Aranda, whose defense at Wisconsin ranked 12th, 16th and 12th over the past 3 years in my yards per play adjusted for schedule
  • Did I mention Leonard Fournette?

There’s only one problem, and he’s the guy taking snaps from the center. QB Brandon Harris completed a meager 54% of his passes last year, allowing defenses to key on Fournette in critical games.

Harris looks like a stumbling block for this team. However, he did have off season surgery to fix a sports hernia that might have affected his play late in the season.

Also, Les Miles has had success without a star QB. LSU played in 2013 BCS title game despite the maybe average play of Jordan Jefferson and Jarrett Lee at QB.

Florida State vs Clemson

It seems like Clemson should be ahead of Florida State heading into the 2016 season.

Clemson beat Florida State on their way to the national title game against Alabama. Despite the 5 point loss against Bama, you could argue Clemson should have won. They dominated the line of scrimmage but couldn’t overcome blown coverages in the secondary.

However, my preseason ranking like Florida State, as the Seminoles rank 2nd over Clemson at 5th. The returning starters variable plays a critical role in this rank.

Florida State has 17 returning starters, which includes star running back Dalvin Cook. In contrast, Clemson returns only 12 starters. In addition, the Tigers had heavy attrition in the secondary, including 3 players that got drafted by the NFL.

In addition, Clemson beat Florida State by 10 last year. However, Florida State had more yards per play than Clemson, an indication of a fairly even game. The Seminoles couldn’t overcome a 2 for 12 rate in converting third downs.

However, Clemson might have the trump card. They bring back Deshaun Watson, the best quarterback in the nation. Florida State is still deciding between returning starter Sean McGuire at QB or a few younger players.

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In addition, you get a sample of my college football predictions usually only available to paying members of the site. In 2016, these numbers correctly predicted the winner 76.2% of games.

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Full college football preseason rankings

1. Alabama, 21.2
2. Florida State, 19.3
3. LSU, 17.3
4. Clemson, 16.3
5. Oklahoma, 16.2
6. Stanford, 15.7
7. Tennessee, 14.8
8. Mississippi, 13.2
9. Michigan, 12.6
10. Texas A&M, 12.3
11. Ohio State, 12.1
12. Arkansas, 11.8
13. Notre Dame, 11.8
14. Louisville, 11.3
15. Baylor, 11.3
16. Georgia, 11.0
17. Oklahoma State, 10.8
18. Oregon, 10.7
19. USC, 10.4
20. North Carolina, 10.1
21. TCU, 9.9
22. Wisconsin, 9.8
23. Mississippi State, 9.5
24. Utah, 8.9
25. Nebraska, 8.7
26. Washington, 8.6
27. Brigham Young, 8.6
28. Florida, 8.3
29. Michigan State, 7.9
30. Washington State, 7.3
31. Virginia Tech, 7.2
32. Auburn, 7.1
33. Pittsburgh, 6.7
34. South Carolina, 5.9
35. West Virginia, 5.8
36. Iowa, 5.8
37. UCLA, 5.6
38. Arizona, 5.5
39. Texas, 5.4
40. Miami (FL), 5.2
41. Houston, 5.2
42. Texas Tech, 5.0
43. Penn State, 3.9
44. Vanderbilt, 3.7
45. Memphis, 3.6
46. Toledo, 3.5
47. Georgia Tech, 3.4
48. Cincinnati, 3.4
49. Boise State, 3.4
50. Kansas State, 3.3
51. South Florida, 3.2
52. Missouri, 3.0
53. Arizona State, 2.6
54. Temple, 2.6
55. Boston College, 2.5
56. California, 2.1
57. Georgia Southern, 2.0
58. Northwestern, 1.9
59. North Carolina State, 1.9
60. Minnesota, 1.8
61. Navy, 1.3
62. Western Kentucky, 1.3
63. Iowa State, 1.0
64. Syracuse, 0.9
65. Northern Illinois, 0.7
66. San Diego State, 0.6
67. Indiana, 0.5
68. Western Michigan, 0.3
69. Bowling Green, 0.0
70. Air Force, -0.3
71. Connecticut, -0.3
72. Virginia, -0.5
73. Wake Forest, -0.6
74. Utah State, -0.6
75. Duke, -0.6
76. Purdue, -1.2
77. Colorado, -1.2
78. Maryland, -1.3
79. Marshall, -1.5
80. East Carolina, -1.8
81. San Jose State, -1.8
82. Tulsa, -2.2
83. Kentucky, -2.3
84. Rutgers, -2.4
85. Appalachian State, -2.4
86. Central Michigan, -2.4
87. Oregon State, -2.7
88. Illinois, -4.2
89. UCF, -5.5
90. Arkansas State, -5.7
91. Army, -5.9
92. Middle Tennessee State, -6.6
93. Louisiana Tech, -6.7
94. SMU, -6.9
95. Nevada, -7.0
96. Ohio, -7.5
97. Colorado State, -7.9
98. Florida Atlantic, -7.9
99. Troy, -8.0
100. Southern Miss, -8.0
101. Kent State, -8.1
102. Ball State, -8.6
103. Georgia State, -8.9
104. New Mexico, -9.1
105. Wyoming, -9.2
106. Louisiana Lafayette, -9.3
107. Hawaii, -9.4
108. Rice, -10.1
109. Buffalo, -10.3
110. Tulane, -11.0
111. Kansas, -11.4
112. UNLV, -12.0
113. Akron, -12.5
114. Fresno State, -12.6
115. South Alabama, -12.7
116. Old Dominion, -13.9
117. Miami (OH), -14.3
118. Florida International, -14.4
119. Louisiana Monroe, -14.8
120. North Texas, -15.2
121. Eastern Michigan, -15.2
122. UTEP, -15.9
123. Idaho, -16.0
124. Massachusetts, -16.6
125. UTSA, -17.4
126. New Mexico State, -18.8
127. Texas State, -20.9
128. Charlotte, -24.0