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College football teams are volatile as hell. Why don’t we incorporate that into our picks?

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Michigan v Notre Dame Photo by: Gregory Shamus/Getty Images

You have a different team every week. It is a Lou Holtzian truism that we are reminded of every single week of the college football season. A team beats a great opponent, then lays an egg against a lesser one. Good one week, mediocre the next, great the next, WTF the next.

When you rely on the whims of 20-year old males, you are going to find life rather maddening. Still, some teams are more frustrating and volatile than others. Some are all over the map, while others are reasonably steady. (“Steady” can be “steady good” or “steady bad,” mind you.)

My S&P+ ratings are designed to simplify. They are now presented in the form of an adjusted point total — No. 1 Ohio State’s plus-29.4 rating means the Buckeyes are 29.4 points better than the average team at the moment; No. 128 Charlotte is 21.1 points worse than average. This is designed to tell you that, on a neutral field, Ohio State would be expected to beat Charlotte by 50.5 points. And that’s fine. But the frequency of, say, a closer-than-expected 24-point win or an all-time, 77-point blowout is uncertain.

Because I am an endless tinkerer, I’ve been looking into ways to incorporate volatility (in this case, represented by standard deviation) into my S&P+ picks. I haven’t simulated as much as I need to to know my approach is going to work particularly well, but I thought I’d show my work and open up a conversation.

On the team stat profiles, I share a team’s adjusted scoring margin for a given game. It is intended to express, “Based on this game’s stats, you could have expected to win/lose this game by X points.” It is unadjusted for opponent. But if I actually adjust for opponent, I can come up with a pretty solid basis for a standard deviation figure.

If you’re curious, here are the standard deviations for FBS teams in both 2015 and 2016 (sorted by current 2016 average).

Team 2016 Volatility Rk 2015 Volatility Rk
Idaho 12.0 20 10.1 1
Washington State 24.4 108 10.8 2
Old Dominion 24.6 110 11.3 3
North Carolina 13.5 33 13.0 4
San Diego State 19.8 82 13.5 5
Western Michigan 16.6 55 13.5 6
Indiana 9.2 10 13.7 7
Minnesota 8.7 7 13.9 8
Ohio State 11.1 16 14.2 9
Central Michigan 29.8 126 14.4 10
South Carolina 16.0 49 14.5 11
Virginia 23.8 104 14.6 12
Florida Atlantic 17.6 61 14.9 13
South Florida 18.3 67 15.1 14
UTEP 25.7 112 15.1 15
Wyoming 22.7 97 15.4 16
North Texas 28.8 124 15.5 17
Alabama 17.4 59 15.5 18
Tulsa 23.6 102 15.5 19
Stanford 33.0 127 15.7 20
Mississippi State 18.2 66 15.8 21
Nevada 22.5 96 15.9 22
Tennessee 9.1 9 16.0 23
Bowling Green 16.4 52 16.0 24
Clemson 14.1 36 16.2 25
Team 2016 Volatility Rk 2015 Volatility Rk
Toledo 10.0 12 16.2 26
Florida State 23.5 101 16.5 27
Pittsburgh 12.0 22 16.5 28
Georgia State 14.2 41 16.5 29
Western Kentucky 19.4 76 16.6 30
Arkansas 24.2 106 16.7 31
Connecticut 8.6 6 16.8 32
Appalachian State 24.5 109 16.9 33
Central Florida 18.5 70 17.0 34
Oregon 18.0 64 17.0 35
BYU 9.2 11 17.3 36
Akron 19.5 80 17.3 37
Houston 13.3 30 17.4 38
Arkansas State 16.4 51 17.4 39
Auburn 21.2 89 17.5 40
Ball State 21.0 87 17.8 41
Virginia Tech 21.4 91 17.8 42
Kansas 23.8 105 17.8 43
Nebraska 13.3 31 18.0 44
Arizona State 15.3 47 18.0 45
UL-Lafayette 23.7 103 18.0 46
SMU 17.9 63 18.1 47
Washington 22.4 95 18.2 48
Buffalo 13.2 29 18.2 49
Rice 12.7 25 18.3 50
Team 2016 Volatility Rk 2015 Volatility Rk
Southern Miss 20.3 85 18.4 51
East Carolina 15.9 48 18.6 52
Marshall 33.9 128 18.7 53
Utah State 18.6 71 18.7 54
UCLA 10.1 13 18.7 55
Notre Dame 13.6 34 18.8 56
UL-Monroe 22.9 99 19.0 57
Ole Miss 13.5 32 19.0 58
Massachusetts 14.8 46 19.2 59
Navy 17.1 57 19.3 60
Temple 27.5 120 19.4 61
New Mexico State 12.8 27 19.4 62
UTSA 12.5 23 19.5 63
Maryland 20.1 83 19.5 64
Louisville 17.9 62 19.6 65
Baylor 12.6 24 19.6 66
Oklahoma 18.5 69 19.8 67
San Jose State 19.4 78 19.9 68
Michigan State 12.9 28 20.0 69
Hawaii 27.4 119 20.1 70
Texas State 25.8 113 20.2 71
Rutgers 19.2 73 20.3 72
Miami (Ohio) 7.8 4 20.3 73
Troy 12.0 21 20.4 74
Texas 10.8 14 20.5 75
Team 2016 Volatility Rk 2015 Volatility Rk
Wake Forest 14.2 38 20.5 76
Utah 14.3 43 20.6 77
Fresno State 26.9 116 20.7 78
Colorado State 26.6 114 20.8 79
Eastern Michigan 23.0 100 21.0 80
Colorado 16.0 50 21.1 81
Oklahoma State 19.4 77 21.2 82
Air Force 16.4 53 21.2 83
Kentucky 21.8 92 21.2 84
UNLV 21.4 90 21.3 85
LSU 17.0 56 21.4 86
Middle Tennessee 16.6 54 21.5 87
Tulane 14.2 39 21.5 88
Louisiana Tech 11.8 19 21.5 89
Georgia 19.2 75 21.5 90
Syracuse 18.1 65 21.7 91
Texas Tech 18.8 72 21.7 92
Iowa 21.0 88 21.7 93
Wisconsin 17.3 58 21.8 94
Northern Illinois 13.7 35 21.8 95
Penn State 19.2 74 22.1 96
South Alabama 14.2 40 22.2 97
Arizona 14.3 42 22.4 98
Army 21.8 93 22.5 99
Miami 11.1 17 22.5 100
Team 2016 Volatility Rk 2015 Volatility Rk
Cincinnati 10.9 15 22.6 101
Missouri 28.2 121 22.9 102
Ohio 3.6 1 23.0 103
Charlotte 22.8 98 23.4 104
California 5.2 2 23.5 105
New Mexico 12.8 26 23.5 106
Florida International 11.7 18 23.7 107
Vanderbilt 14.7 45 23.9 108
Iowa State 28.6 123 24.1 109
Michigan 18.4 68 24.6 110
Purdue 27.2 117 24.7 111
Duke 20.7 86 24.7 112
Boston College 29.6 125 24.9 113
Kansas State 27.3 118 24.9 114
Oregon State 19.7 81 24.9 115
Memphis 26.7 115 25.0 116
Georgia Tech 24.4 107 25.3 117
NC State 8.4 5 25.6 118
Texas A&M 9.0 8 25.6 119
USC 28.3 122 25.6 120
TCU 14.3 44 25.6 121
West Virginia 7.1 3 26.6 122
Florida 20.2 84 26.7 123
Georgia Southern 21.9 94 26.8 124
Northwestern 14.2 37 27.6 125
Boise State 19.4 79 29.5 126
Illinois 25.0 111 29.8 127
Kent State 17.5 60 30.6 128

I’m guessing that it’s a bit too early for these to be reliable, and I haven’t finished setting up a simulation for 2015 yet, but like I said — we’re still in experiment stage. So we’ll press forward.

If we have an average (the S&P+ rating) and a standard deviation, we are in position to simulate. So what happens if we take every game on the Week 6 docket and simulate it 10,000 times? In theory, we can come up with different average and median scoring margins. We can also compare these margins to the Vegas spread and take a peek at how frequently Team A covers against Team B in these simulations.

See where I’m going with this?

Date Game Spread Team Cover%
8-Oct-16 BYU at Michigan State -6.0 BYU 69%
8-Oct-16 Fresno State at Nevada -9.5 Fresno State 60%
8-Oct-16 Florida International at UTEP -5.5 Florida International 60%
8-Oct-16 Ball State at Central Michigan -12.5 Ball State 60%
8-Oct-16 LSU at Florida 3.0 Florida 60%
8-Oct-16 Indiana at Ohio State -29.0 Indiana 59%
8-Oct-16 Notre Dame at NC State -2.5 NC State 58%
8-Oct-16 Michigan at Rutgers 28.0 Michigan 58%
8-Oct-16 Kent State at Buffalo 1.0 Kent State 58%
8-Oct-16 East Carolina at South Florida -20.0 East Carolina 58%
7-Oct-16 SMU at Tulsa -17.0 SMU 58%
8-Oct-16 Texas Tech at Kansas State -7.5 Texas Tech 57%
8-Oct-16 Texas vs. Oklahoma -10.5 Texas 57%
8-Oct-16 California at Oregon State 13.5 Oregon State 57%
8-Oct-16 Northern Illinois at Western Michigan -19.5 Northern Illinois 56%
8-Oct-16 Virginia Tech at North Carolina -2.5 Virginia Tech 56%
8-Oct-16 Massachusetts at Old Dominion -7.0 Old Dominion 56%
8-Oct-16 Maryland at Penn State 1.0 Penn State 56%
8-Oct-16 Utah State at Colorado State 6.0 Colorado State 56%
8-Oct-16 TCU at Kansas 29.0 Kansas 55%
8-Oct-16 Army at Duke -4.0 Duke 55%
8-Oct-16 Iowa at Minnesota 1.5 Minnesota 55%
8-Oct-16 Miami-OH at Akron -7.5 Akron 55%
8-Oct-16 Tennessee at Texas A&M -6.5 Tennessee 55%
8-Oct-16 UNLV at San Diego State -14.5 UNLV 55%
8-Oct-16 UCLA at Arizona State 9.5 Arizona State 54%
8-Oct-16 Georgia at South Carolina 7.0 South Carolina 54%
8-Oct-16 Idaho at UL-Monroe -5.0 Idaho 54%
8-Oct-16 Toledo at Eastern Michigan 17.0 Eastern Michigan 54%
8-Oct-16 Iowa State at Oklahoma State -17.0 Iowa State 54%
8-Oct-16 Syracuse at Wake Forest -2.5 Wake Forest 54%
8-Oct-16 Bowling Green at Ohio -12.5 Bowling Green 54%
8-Oct-16 Hawaii at San Jose State -3.0 Hawaii 53%
8-Oct-16 Charlotte at Florida Atlantic -13.5 Charlotte 53%
8-Oct-16 Texas State at Georgia State -10.0 Texas State 53%
8-Oct-16 Marshall at North Texas 10.0 North Texas 53%
8-Oct-16 Auburn at Mississippi State 3.0 Mississippi State 53%
8-Oct-16 Washington at Oregon 8.5 Oregon 52%
8-Oct-16 Purdue at Illinois -10.0 Illinois 52%
8-Oct-16 Cincinnati at Connecticut 2.5 Connecticut 52%
8-Oct-16 Alabama at Arkansas 13.5 Alabama 52%
8-Oct-16 Air Force at Wyoming 10.5 Air Force 52%
8-Oct-16 Georgia Tech at Pittsburgh -6.5 Pittsburgh 51%
8-Oct-16 Washington State at Stanford -7.0 Stanford 51%
8-Oct-16 Southern Miss at UTSA 16.5 Southern Miss 51%
7-Oct-16 Clemson at Boston College 16.5 Clemson 51%
7-Oct-16 Boise State at New Mexico 17.5 New Mexico 51%
8-Oct-16 Florida State at Miami-FL -3.0 Miami-FL 51%
8-Oct-16 Arizona at Utah -9.5 Arizona 51%
8-Oct-16 Colorado at USC -5.0 USC 51%
8-Oct-16 Houston at Navy 17.0 Houston 50%
8-Oct-16 Vanderbilt at Kentucky -3.0 Vanderbilt 50%

We’re miles from any sort of “Take THESE Picks to the Bank!!” proclamations, but I’m going to be paying particular attention to the five games at the top (not including Florida-LSU, obviously):

  • BYU at Michigan State
  • Fresno State at Nevada
  • Florida International at UTEP
  • Ball State at Central Michigan
  • Indiana at Ohio State

This is obviously based on the spread listed. Depending on the volatility of the two teams involved, a 0.5-point change in the spread could result in a change of anything between 0.4% (if both teams are crazy-volatile) and about 1.6% (if they’re not).

One week won’t tell us much, but I’ll keep trying to pursue this and see what I find. Coming up with an approximate “odds of covering” figure would be lovely, especially if Vegas and luck continue to be the jerk that they’ve both been so far this year. And if this does go somewhere, it will be fun to figure out the contributing factors to year-to-year volatility.