THE POWER RANK

Predicted college football playoff rankings after week 9, 2015

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Screen Shot 2015-11-02 at 3.48.41 PMHow will the college football playoff committee rank teams this week? I’ve been posting my predictions all season, but there’s a right answer this week.

Last year, the committee sorted teams by losses in their opening rankings. This led me to make some adjustments to this week’s rankings, especially for undefeated Iowa and Oklahoma State.

Undefeated Memphis and Houston also caused some problems. It’s tough to know where the committee with rank these non Power 5 teams, so I put them behind the one loss teams.

To check out my predictions, click here.

We’ll see how these predicted rankings do Tuesday night at 7pm Eastern.

3 surprising college basketball teams early this 2013-2014 season

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teamrank_Dec12_2013After a month of college basketball, my teams rankings look strange.

Oklahoma State tops a motley crew of teams you wouldn’t expect in the top 10. Syracuse is the only traditional power on this list, sneaking in at 9th. Pittsburgh (4th) and Ohio State (5th) have had some good teams over the last decade. Otherwise, The Power Rank’s top 10 contains some surprise teams.

Before we discuss 3 of these teams in detail, consider teams not on this list.

  • Duke, 8th in the AP poll. Stuck at 49th in The Power Rank.
  • The Kentucky NBA Development League team. 24th in The Power Rank.
  • Arizona, 1st in the AP poll. 13th in The Power Rank.
  • Louisville, defending national champions. 16th in The Power Rank.

Small sample size plays a critical factor in these early season rankings. With more games, some traditional powers will rise while some upstarts will fall.

We’ll look at 3 surprise teams in more detail. In this post, the offense and defense rankings are a team’s points per possession adjusted for strength of schedule.

In addition, I also adjust Dean Oliver’s 4 factors for schedule strength, a critical factor so early in the college basketball season. Comments on each team reflect these numbers. For example, a team shoots well when they have a good 2 points shooting percentage after schedule adjustments.

Interested in all of this data? Members of The Power Rank have access to all of it, including daily data files that can be uploaded into a spreadsheet. I’m making a special offer for fans on my email list next week. To sign up for this free email newsletter, enter your email address and click “Sign up now”.








Oklahoma State

When I watch an Oklahoma State game, I feel old. Back before I knew any of the math used to rank teams on this site, I watched Travis Ford play at Kentucky in the early 90’s.

Now, he coaches the clear number one team in The Power Rank. Led by guard Marcus Smart, they rank 2nd in offense. The Cowboys shoot well and don’t commit turnovers. Behind Smart, they have 4 other players averaging 10 points a game.

Oklahoma State also has a sound defense, ranked 21st in the nation. They excel in holding opponents to poor shooting and forcing turnovers.

Oklahoma State will most likely regress from their lofty rank. Their 3 point shooting has improved from 32% last season to 41% this season. Most of this improvement has come from Phil Forte, who has sunk 53% of 3’s this season. Unless he can keep this up, Oklahoma State’s offense will not end the year 2nd in the nation.

Massachusetts

The Minutemen are lead by coach Derek Kellogg, a former assistant and recruiter for John Calipari. After finishing last season 88th in The Power Rank, they have surged to 7th this season.

Led by guard Chaz Williams, Massachusetts has the 18th best offense in the nation. They shoot well and get on the offensive glass. Moreover, they also have 5 players averaging over 10 points a game.

UMass also plays stingy defense, ranked 35th in the country. They excel in making opponents shoot poorly and not fouling.

Of the three teams profiled here, Massachusetts is mostly likely to stay high in The Power Rank. Their success so far hasn’t come from exceptional 3 point shooting or 3 point defense, two numbers that strongly regress to the mean.

Oregon

I had my doubts when Oregon fired coach Ernie Kent in 2010. Kent had the most wins in school history and led Oregon two Elite Eight appearances.

After a failed attempt to lure Tom Izzo to the Pacific Northwest, Oregon hired Dana Altman. Despite his success at Creighton, I had my doubts whether he could live up to super booster Phil Knight’s lofty expectations.

However, Oregon has risen from 31st at the end of last season to 3rd this season in The Power Rank. They excel on offense, ranked 3rd, but have some work to do on defense, ranked 110th.

Which direction the Ducks head depends on two factors.

Oregon has shot incredibly well from 3 point range. They have sunk 44% of 3 pointers, a much higher rate then the 33% they shot last season. The randomness of 3 points shooting suggests they can’t sustain 44% for the season.

However, Oregon has missed two key players, Dominc Artis and Ben Carter, so far this season. They were suspended for selling team issued apparel. If they return and show more brains on the court than off, Oregon could be a top 10 team.

3 predictions from a new college football ranking system, week 6, 2013.

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Rankings based on a regression model designed for early in the season.

Rankings based on a regression model designed for early in the season.

After 5 weeks of the college football season, we’re still in the dark about most college football teams. The only certainty is that Lane Kiffin no longer coaches USC.

I always try to improve the preseason and early season college football rankings at The Power Rank. The primary rankings on the site still use last season’s games, with this season’s games counted twice. I think they do a good job, but this method reacts slowly to teams that have struggled, such as Texas (31st).

So I developed new model this week. It’s based on the regression model that I used for my preseason predictions, which consider a team’s rating the last 4 years, turnovers and returning starters. Now, the model includes a rating calculated from only games this year.

The visuals shows the top 10 teams in this regression model. While Baylor is mostly likely overrated at 2nd since they have not played anyone, I do like that Alabama has dropped to 3rd and Washington has cracked the top 10.

Let’s look at the predictions this model makes.

How low should Texas be ranked?

Texas checks in at 51st in this regression model. Their moderate success over the past 4 seasons (moderate by Texas standards) and a host of returning starters keep the Longhorns above the average FBS team (125 teams total).

For last night’s game at Iowa State, the regression model predicted a 2.3 win for Iowa State. The rankings that use last year’s games had Texas by 2.8. The regression model has reacted faster to the Longhorn’s struggles, who have lost badly to Mississippi and BYU.

Texas squeaked out a win last night over Iowa State. They needed a hail mary touchdown at the end of the 1st half as well as a no call on a fumble that would have ended Texas’s game winning drive. Further more, Iowa State gained 6.0 yards per play compared to 4.9 for Texas.

Mack Brown is dating Lady Luck.

How good are the predictions of the new model?

I went back and tested how accurately each ranking system predicted game winners. This test considered all games after week 5 from the 2007 to 2012 seasons.

The regression model predicted 69.2% of game winners, while The Power Rank using last year’s games got 68.9% correct. With an error of about 0.8%, both rankings system have the same predictive power.

However, both methods perform better than The Power Rank with only this year’s games. Those rankings predicted 67.5% of game winners, quite a bit less.

Let’s look at the predictions these two models make.

Notre Dame and Arizona State

Notre Dame has disappointed this season. They have already lost twice, and that 7 point win over Purdue looks worse as the Boilermakers continue to lose badly each week.

The rankings with last year’s games predict a 1.3 point loss against Arizona State at a neutral site in Dallas. However, the regression model predicts a 5.5 point loss, the same as the line.

I still don’t know what to think about Notre Dame. Their defense doesn’t tackle well in the secondary. But Oklahoma scored 14 points off of 2 tipped passes against the Fighting Irish last week. Moreover, QB Tommy Rees had a terrible game.

I’d stay away from this game.

Illinois at Nebraska

Illinois has been a pleasant surprise, a rarity in the Big Ten this season. Behind the 9th best offense, the Fighting Illini are 53rd in the regression model, a miracle for a team that finished 115th last season.

They travel to Lincoln to face a Nebraska team that has struggled on defense. The regression model has reacted more quickly to the opposite fortunes of these two teams, picking a 6 point win for Nebraska (the line favors Nebraska by 9).

The rankings with last year’s games have Nebraska by 13.6 points. With the two teams that do not resemble their preseason expectations, it’s safe to ignore this prediction.

This is my upset special for the week. Nebraska’s offense has not lived up to expectations, and QB Taylor Martinez will not play again this week. Illinois gets the win in Lincoln. Next week’s headlines give Mack Brown a week of reprieve and focus on the job security of Bo Pellini.

Kansas State at Oklahoma State

Kansas State lost a host of starters from last season’s stellar team. In addition, the Wildcats had an unsustainable turnover margin in 2012. Hence, my preseason ranking had them at 37th.

The rankings with last season’s games predict a tight game (0.8 points) in favor of Oklahoma State. Again, it’s safe to ignore that given the changes to this Kansas State team.

The regression model predicts a 9 point win for Oklahoma State. This margin is probably to big. Kansas State fumbled the ball 3 times in gifting a win to Texas last week.

The line favors Oklahoma State by 14. This is too much for a team whose offense hasn’t performed at the elite level it did last season.

What do you think?

I’ve copied the rankings from the regression model below. Would you like to see them as the primary rankings?

Let me know in the comments. Thanks for reading.

1. Oregon (4-0), 28.80
2. Baylor (3-0), 26.81
3. Alabama (4-0), 23.22
4. Stanford (4-0), 17.67
5. Georgia (3-1), 15.98
6. Texas A&M (4-1), 15.55
7. LSU (4-1), 15.49
8. Washington (4-0), 14.31
9. Florida State (4-0), 14.14
10. Florida (3-1), 14.07
11. Ohio State (5-0), 13.87
12. Clemson (4-0), 13.46
13. Louisville (4-0), 12.92
14. UCLA (4-0), 12.58
15. Wisconsin (3-2), 11.93
16. South Carolina (3-1), 11.47
17. Miami (FL) (4-0), 10.73
18. TCU (2-2), 10.14
19. Oklahoma (4-0), 10.14
20. Arizona State (3-1), 9.84
21. Texas Tech (4-0), 9.74
22. Arizona (3-1), 9.59
23. Missouri (4-0), 9.01
24. Utah State (3-2), 8.32
25. Mississippi (3-1), 8.17
26. USC (3-2), 7.75
27. Northwestern (4-0), 7.42
28. Oklahoma State (3-1), 7.41
29. Oregon State (4-1), 7.23
30. Northern Illinois (4-0), 5.76
31. Virginia Tech (4-1), 5.24
32. Tennessee (3-2), 4.79
33. Maryland (4-0), 4.72
34. Auburn (3-1), 4.67
35. UCF (3-1), 4.53
36. Penn State (3-1), 4.43
37. Notre Dame (3-2), 4.37
38. Boise State (3-2), 4.28
39. Nebraska (3-1), 4.11
40. Iowa (4-1), 3.92
41. Michigan State (3-1), 3.67
42. Utah (3-2), 3.45
43. Brigham Young (2-2), 3.41
44. Vanderbilt (3-2), 3.05
45. Georgia Tech (3-1), 3.01
46. Michigan (4-0), 2.60
47. Fresno State (4-0), 2.24
48. West Virginia (3-2), 1.88
49. Arkansas (3-2), 1.76
50. Syracuse (2-2), 1.50
51. Texas (3-2), 1.40
52. Kansas State (2-2), 1.21
53. Illinois (3-1), 1.02
54. East Carolina (3-1), 0.94
55. Mississippi State (2-2), 0.80
56. North Carolina State (3-1), 0.73
57. Iowa State (1-3), 0.72
58. Washington State (3-2), 0.50
59. Rutgers (3-1), -0.15
60. Toledo (2-3), -0.17
61. Ball State (4-1), -0.23
62. Cincinnati (3-1), -0.33
63. San Jose State (1-3), -0.38
64. Pittsburgh (3-1), -0.44
65. Houston (4-0), -0.58
66. California (1-3), -0.62
67. North Carolina (1-3), -0.66
68. Kentucky (1-3), -0.75
69. Minnesota (4-1), -1.11
70. Bowling Green (4-1), -1.49
71. Marshall (2-2), -1.65
72. North Texas (2-2), -1.87
73. Indiana (2-2), -1.90
74. Boston College (2-2), -1.92
75. Western Kentucky (4-2), -2.02
76. Buffalo (2-2), -2.33
77. Ohio (3-1), -2.50
78. Rice (2-2), -2.77
79. Navy (2-1), -3.03
80. San Diego State (1-3), -3.31
81. Connecticut (0-4), -3.37
82. Colorado State (2-3), -4.02
83. Virginia (2-2), -4.74
84. Wyoming (3-2), -5.16
85. SMU (1-3), -5.28
86. Arkansas State (2-3), -5.78
87. Louisiana Lafayette (2-2), -6.11
88. Tulsa (1-3), -6.14
89. Nevada (3-2), -6.31
90. Duke (3-2), -6.34
91. Louisiana Monroe (2-4), -6.46
92. Colorado (2-1), -6.49
93. Army (2-3), -7.09
94. Wake Forest (2-3), -8.01
95. Temple (0-4), -8.05
96. Kent State (2-3), -8.11
97. Louisiana Tech (1-4), -8.17
98. Florida Atlantic (1-4), -8.54
99. Middle Tennessee State (3-2), -8.61
100. Purdue (1-4), -9.07
101. Kansas (2-1), -9.54
102. South Florida (0-4), -9.68
103. Tulane (3-2), -10.27
104. Western Michigan (0-5), -10.40
105. Troy (2-3), -11.14
106. UAB (1-3), -11.34
107. Hawaii (0-4), -11.75
108. Air Force (1-4), -11.80
109. UNLV (3-2), -12.39
110. Southern Miss (0-4), -13.19
111. Memphis (1-2), -13.20
112. Akron (1-4), -13.27
113. UTEP (1-3), -14.38
114. Idaho (1-4), -14.94
115. Miami (OH) (0-4), -15.71
116. Florida International (0-4), -15.86
117. Central Michigan (1-4), -16.30
118. Eastern Michigan (1-3), -17.36
119. New Mexico (1-3), -18.10
120. New Mexico State (0-5), -19.98

Infographic shows the effect of paying players at Oklahoma State

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Oklahoma State

Sports Illustrated dropped a bomb on Oklahoma State and college football this week. A report revealed a massive number of NCAA violations, including paying players and academic fraud.

The payment of players started in 2001 when Les Miles became head coach. With data visualization, we can look at how team performance changed after this started.

The top panel shows wins over the last 30 years. Oklahoma State struggled in the 1990’s, even managing a winless season in 1991.

The Cowboys started to win more after 2001. In fact, they have won at least 6 games in each year of the past decade, with Mike Gundy’s first year in 2005 as the only expection.

The bottom panels shows the team rating from The Power Rank algorithm. This rating gives an expected margin of victory against an average FBS team.

If you’re not sure what to think about a computer rating, consider the predictive power of The Power Rank. In pre bowl rankings, the higher ranked team has won 66.8% of bowl games since 2005. In comparison, the opening line in Vegas has correctly predicted 59.8% of bowl game winners over the same period (data from The Prediction Tracker).

The rating also shows improvement in Oklahoma State football since 2001. They became an above average Big 12 team during the tenure of Les Miles. However, it took time to become an elite program. In 2011, they beat Stanford in the Fiesta Bowl and finished 3rd in the rankings behind Alabama and LSU. This came ten years after the alleged payments to players started.

Two things stand out about this Sports Illustrated report.

No denials of the allegations

If athletic director Mike Holder knew nothing about paying players, I would expect him to deny the allegations in the report. Instead, Holder apologized to other member institutions of the Big 12.

Even Oklahoma State super booster T. Boone Pickens didn’t deny the allegations. Within 24 hours of SI’s story, Pickens released this well shot and edited video. He only criticized SI for not looking at the state of the program today.

No accusations against the super booster

T. Boone Pickens is well know for his generosity to Oklahoma State football. In December of 2005, he gave $165 million towards renovating the stadium, now know as Boone Pickens Stadium.

However, Sports Illustrated does not allege that Pickens participated in any of the payment to players.

It’s hard to say with certainty that the payments to players caused the rise in Oklahoma State’s football program. However, visualizing the data certainly shows a rise in their program after 2001 when these payments started.

Can a defense force turnovers? A look back at Stanford, Oklahoma State.

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Heading into the Fiesta Bowl against Stanford, Oklahoma State led the nation with 42 turnovers created by their defense. But is this a skill? Can a defense consistently force turnovers? We searched for any statistical analysis that could answer this question. The most complete study was done by Bill Barnwell at Grantland. He found that turnovers in the first 5 games of the NFL season is weakly correlated with turnovers in the remaining 11 games (correlation coefficient of 0.14). We used this study in our Fiesta Bowl preview to suggest that a large turnover total is not predictive of future turnovers.

So how did the Fiesta Bowl turn out? In the 1st quarter, Oklahoma State cornerback Justin Gilbert intercepted an Andrew Luck pass. It’s reasonable to argue that the Cowboys forced this turnover, as Gilbert had the speed and agility to step in front of the Stanford receiver. In the 3rd quarter, Oklahoma State recovered a Stanford fumble. The replay clearly showed that Andrew Luck had a bad exchange with Geoff Meinken. In no way did Oklahoma State force this turnover. The defense only capitalized on a mistake by the offense. Stanford had 2 turnovers the entire game, nothing near the almost 4 turnovers per game the Oklahoma State defense had received this season. It’s not that Oklahoma State didn’t try. On two catches in the 2nd half, Stanford receiver Griff Whalen had a horde of defenders standing him up and trying to rip the ball away. No luck.

At the end of regulation, Stanford missed a field goal to win the game, and Oklahoma State won in overtime. The outcome supports The Power Rank’s assertion that Oklahoma State was the better team.

The final college football rankings for the 2011 season.
But luck was also involved, as Oklahoma State converted a critical field goal after the Stanford fumble in the 3rd quarter. Looking ahead to next year, analytics suggests that randomness plays a huge role in how many turnovers a defense forces. No matter how much they practice creating turnovers, don’t be surprised if Oklahoma State doesn’t force 44 turnovers next year. It might be a more difficult season for the Cowboys.

For more content, find The Power Rank on Twitter.

Related Posts:

—Can a defense force turnovers? A Stanford, Oklahoma State preview.
—About The Power Rank.
—College football’s incredibly slow progress towards a playoff.
—The Power Rank featured on KALX Spectrum, the science and technology show on UC Berkeley student radio.