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» Impact of the NFL's Kickoff Rule Change

After three NFL seasons of kicking off from the 35-yard line, what has been the impact on touchbacks, returns, field position, scoring and injuries? Also, is this rule responsible for a record number of big comebacks?

01 Sep 2011

FEI: Preseason Primer 2011

by Brian Fremeau

It’s been a long offseason, and I think we’re all ready for some football. The last few months have been peppered with salacious scandals and conference crises, but there are finally games to be played and game data to be consumed. I’ve taken the opportunity in the offseason to thoroughly examine the ways in which I process college football drive data, and I’m particularly excited to get a new season underway. There are new and enhanced metrics I’ll be debuting in 2011, and I’m ready to get started.

But before we get into the new stuff, there are some things that haven’t changed at all. The Fremeau Efficiency Index (FEI) college football ratings will continue to be published weekly here at Football Outsiders and the methodology to produce the overall FEI team ratings has not been modified. Game Efficiency still represents my summary measure of each team’s offense, defense, and special teams effectiveness over the non-garbage drives of a game. Game Efficiency continues to be the raw metric at the core of the FEI ratings, and my opponent adjustment methodology has not been altered this year. I’ve been pleased with the consistency and quality of the overall FEI ratings as well as the game projections and complementary metrics (strength of schedule, mean wins) that are derived from those ratings.

What has changed is the way I have carved up drive data to produce separate offense, defense and special teams efficiency metrics. The changes aren’t so significant that they dramatically shake up Offensive FEI or Defensive FEI, and the principles behind the metrics haven’t changed at all. But there were gaps last season -– bits of drive or field position value that was unaccounted for in the splits data. I’ve closed those gaps and can now distribute that fractional drive value to the offense, defense, or special teams unit that was responsible for producing it. Let’s review the principles and process.

Every possession has automatic expected value. A typical college football game consists of 24 non-garbage game possessions (12 for each team) and each team is expected to score about 23 points. In other words, every drive is worth a little less than two points, automatically. Doing nothing other than possessing the ball is, on average, worth something.

We can be even more precise. Following the opening kickoff of each half, the automatic expected value of the ensuing possession is 1.6 points. On every other non-overtime possession in a game, the expected value is 1.9 points. What accounts for the difference? Starting field position is better, on average, on non-opening-of-half drives. Which leads us to the next principle.

Starting field position value is earned. Drives that start in opponent territory versus drives that start on a team’s own side of the field can have very different scoring expectations. When a team starts a drive at midfield, it should expect to score 2.4 points -– more than the automatic expected value we had just described. And that extra value was earned by a combination of the offense, defense and special teams play during the preceding possessions. Likewise, the automatic value lost due to starting a drive deep in a team’s own territory is also shared by those units.

The value distribution for each unit in each situation varies based on the specific factors in play. Kickoff returns are measured against average resulting field position. Punt return expectations are a function of the return unit and the drive-ending field position of the previous possession. And who is responsible for the drive-ending field position?

The result of a drive impacts subsequent possessions. This is the gap that I needed to address this offseason. Previously, I measured offensive success on a drive in isolation; results versus expectations of every drive were calculated in a vacuum. But a fraction of the scoring expectation of the opponent’s next drive (and sometimes, the team’s own drive after that) is at stake as well. By closing the gap, the fractional next-possession value at stake is now attributed to the offense, defense and special teams units that earned it. This was covered in an FEI column two weeks ago.

The offense, defense, and special teams efficiency splits I produce are based on these principles and the measurable average expectations of every possession and possession change event.

So how does this approach change the offensive and defensive FEI ratings from last season? Actually, over the course of the season the changes aren’t particularly dramatic. At the game level though, the differences are a bit more apparent. For instance, in the Rose Bowl last season, TCU’s offense scored three touchdowns on eight total possessions against Wisconsin. But part of the key to TCU’s victory was its consistent success on non-scoring drives. The Horned Frogs went three-and-out only once that day, moving the chains and forcing the Badgers into poor field position throughout the second half. The incremental value of each of those non-scoring drives improved TCU’s offensive efficiency for the game by by about 10 percent in our new methodology. Likewise, Wisconsin's defensive efficiency in the game drops, having been unable to get TCU off the field throughout the game.

On the other end of the spectrum, teams that created field position advantages through defensive and special teams play are given an extra boost. The USC defense set up frequent scoring opportunities for the offense against Notre Dame late last year, positioning four drives following turnovers in Irish territory. Though USC's offense sputtered, it's defense earned extra value on the possession changes that never materialized on the scoreboard.

As mentioned, the impact on season-long OFEI and DFEI rankings were not significant for most teams. Teams that were strong in isolated possession success were generally just as strong when accounting for the fractional field position value now added in. The following tables represent the new rankings for 2010 OFEI and DFEI, with last year's ranking provided for comparison.

Updated 2010 Offensive FEI Ratings
Rk Team OFEI LY Rk Team OFEI LY Rk Team OFEI LY
1 Auburn .857 1 41 Georgia Tech .123 45 81 Washington State -.143 79
2 Michigan .652 2 42 Troy .113 35 82 Western Michigan -.146 80
3 Alabama .618 4 43 Oregon State .111 54 83 Eastern Michigan -.152 84
4 Arkansas .578 3 44 Northwestern .102 46 84 Temple -.156 86
5 Stanford .556 6 45 Nebraska .096 44 85 Fresno State -.159 85
6 Wisconsin .552 5 46 Arkansas State .074 34 86 Rice -.162 81
7 Navy .534 9 47 Maryland .072 56 87 Louisiana Lafayette -.169 74
8 Virginia Tech .460 11 48 Louisville .069 60 88 Toledo -.172 90
9 Florida State .455 8 49 Southern Mississippi .062 49 89 Central Michigan -.175 88
10 South Carolina .444 7 50 Hawaii .061 53 90 Duke -.189 82
11 Oklahoma .429 13 51 Indiana .061 47 91 Rutgers -.191 95
12 Nevada .425 10 52 Cincinnati .060 38 92 Louisiana Tech -.194 92
13 San Diego State .424 12 53 UAB .059 59 93 Idaho -.222 94
14 TCU .421 14 54 Miami .058 40 94 BYU -.254 96
15 Oregon .409 15 55 SMU .055 58 95 Louisiana Monroe -.254 91
16 Ohio State .365 16 56 Clemson .053 50 96 Boston College -.259 100
17 Boise State .340 18 57 West Virginia .050 52 97 Ohio -.260 75
18 Arizona .310 28 58 Texas Tech .046 48 98 San Jose State -.271 98
19 Iowa .307 24 59 Tennessee .038 62 99 Wake Forest -.276 99
20 LSU .307 22 60 Illinois .030 55 100 Wyoming -.290 103
21 Oklahoma State .307 19 61 Florida International .019 61 101 UCLA -.323 102
22 Missouri .294 21 62 Central Florida .002 69 102 Florida Atlantic -.336 97
23 East Carolina .282 17 63 Washington -.007 68 103 California -.375 108
24 Kansas State .281 20 64 Western Kentucky -.015 67 104 Kansas -.381 105
25 North Carolina State .261 26 65 Colorado -.017 51 105 Texas -.398 104
26 USC .258 32 66 Mississippi -.023 63 106 Middle Tennessee -.411 101
27 Northern Illinois .251 25 67 Army -.031 71 107 Miami (OH) -.419 109
28 Houston .228 23 68 Florida -.031 57 108 Bowling Green -.430 107
29 Kentucky .220 27 69 Mississippi State -.047 66 109 Ball State -.445 106
30 Pittsburgh .202 29 70 South Florida -.051 70 110 Marshall -.446 111
31 Michigan State .191 30 71 Virginia -.054 64 111 Akron -.462 113
32 Baylor .188 36 72 North Texas -.073 73 112 Purdue -.476 110
33 Air Force .185 39 73 Penn State -.087 77 113 Vanderbilt -.485 112
34 Minnesota .171 41 74 Syracuse -.098 76 114 Kent State -.531 117
35 Georgia .160 33 75 Utah -.120 72 115 Colorado State -.550 116
36 Notre Dame .143 42 76 Connecticut -.120 93 116 New Mexico State -.584 119
37 North Carolina .139 37 77 UTEP -.120 78 117 Memphis -.600 114
38 Tulsa .137 43 78 Tulane -.127 83 118 New Mexico -.618 118
39 Texas A&M .132 31 79 Iowa State -.134 87 119 UNLV -.622 115
40 Arizona State .129 65 80 Utah State -.138 89 120 Buffalo -.741 120

Updated 2010 Defensive FEI Ratings
Rk Team DFEI LY Rk Team DFEI LY Rk Team DFEI LY
1 West Virginia -.698 1 41 USC -.081 59 81 Central Michigan .130 74
2 Ohio State -.591 2 42 Florida International -.076 39 82 Louisiana Lafayette .135 71
3 Oregon -.531 8 43 Purdue -.073 44 83 Kentucky .146 81
4 Oklahoma -.523 4 44 Louisville -.068 41 84 Miami (OH) .185 86
5 Nebraska -.517 5 45 San Diego State -.061 45 85 Western Kentucky .187 87
6 Stanford -.508 11 46 Rutgers -.053 54 86 Tulsa .191 84
7 TCU -.487 12 47 Kent State -.052 57 87 Toledo .201 88
8 Auburn -.480 6 48 Texas Tech -.051 52 88 Virginia .211 85
9 LSU -.479 20 49 Air Force -.049 47 89 Idaho .232 96
10 Missouri -.474 3 50 Mississippi -.046 51 90 Iowa State .237 89
11 North Carolina State -.472 13 51 Arizona -.037 53 91 Wake Forest .237 93
12 Mississippi State -.456 10 52 SMU -.031 46 92 Duke .241 92
13 Boston College -.445 15 53 Georgia -.024 55 93 North Texas .243 83
14 Miami -.441 9 54 Middle Tennessee -.016 48 94 Fresno State .243 98
15 Clemson -.437 7 55 Penn State -.013 49 95 Bowling Green .246 101
16 Alabama -.403 16 56 Louisiana Monroe -.006 42 96 Houston .253 90
17 Boise State -.397 17 57 Tennessee -.003 50 97 Minnesota .266 95
18 Arkansas -.397 19 58 Northern Illinois .005 64 98 Ohio .272 97
19 Texas A&M -.387 14 59 California .012 66 99 Indiana .291 94
20 Maryland -.383 21 60 Marshall .015 56 100 Northwestern .303 100
21 South Florida -.363 18 61 Arkansas State .021 61 101 Kansas .304 99
22 Illinois -.349 26 62 Buffalo .042 58 102 Kansas State .314 102
23 Oklahoma State -.346 23 63 Southern Mississippi .046 65 103 Baylor .322 103
24 Iowa -.339 22 64 Troy .056 63 104 Ball State .347 105
25 Virginia Tech -.334 27 65 Florida Atlantic .060 60 105 Utah State .385 104
26 South Carolina -.324 28 66 Nevada .061 69 106 New Mexico .392 109
27 Notre Dame -.305 25 67 Western Michigan .063 67 107 Louisiana Tech .397 106
28 North Carolina -.303 24 68 UCLA .068 72 108 Akron .417 107
29 Florida -.282 30 69 Vanderbilt .082 62 109 Michigan .419 108
30 Texas -.275 31 70 Cincinnati .087 68 110 San Jose State .447 110
31 Pittsburgh -.270 29 71 Hawaii .097 73 111 Memphis .464 114
32 Central Florida -.242 33 72 Washington .098 77 112 UNLV .494 111
33 Wisconsin -.228 34 73 Temple .102 78 113 Wyoming .498 113
34 Utah -.217 35 74 Oregon State .108 82 114 Rice .499 116
35 Michigan State -.196 32 75 Navy .113 75 115 UTEP .513 112
36 Arizona State -.180 36 76 Tulane .113 80 116 Colorado State .523 115
37 Florida State -.178 38 77 Army .114 91 117 East Carolina .537 117
38 Syracuse -.161 37 78 Colorado .124 79 118 Washington State .578 119
39 BYU -.124 43 79 UAB .125 76 119 New Mexico State .593 118
40 Connecticut -.103 40 80 Georgia Tech .130 70 120 Eastern Michigan .729 120

The other significant addition to this year's FEI data will be expanded special teams ratings. I broke down punt, kickoff, and field goal efficiencies last season, but I've been meaning to combine special teams into a single metric. We'll dig into those numbers in more detail in the coming weeks, but for now, I've simply added up the cumulative value created by each team's field goal units and ranked every team accordingly. As may have been expected based on field position numbers I've shared recently at my blog (here and here), the LSU Tigers created more special teams value than any other team in college football last year.

2010 Special Teams Value
Rk Team STV Rk Team STV Rk Team STV
1 LSU 51.8 41 Rice 13.0 81 Idaho -9.5
2 Utah 47.1 42 Florida 11.9 82 Texas -10.8
3 Virginia Tech 44.4 43 Ball State 11.0 83 Florida Atlantic -12.0
4 USC 41.6 44 Oregon State 10.5 84 California -12.1
5 Louisiana Tech 41.2 45 Oklahoma 9.1 85 South Carolina -12.7
6 Oklahoma State 40.1 46 BYU 9.0 86 Wyoming -14.6
7 Western Michigan 39.6 47 Purdue 7.4 87 Miami -15.2
8 Southern Mississippi 35.7 48 Clemson 7.1 88 New Mexico State -15.8
9 Nebraska 34.5 49 Fresno State 5.7 89 Hawaii -19.9
10 TCU 33.3 50 Temple 5.6 90 Arkansas State -20.5
11 Louisville 31.7 51 San Diego State 4.8 91 Utah State -20.8
12 East Carolina 31.7 52 Auburn 4.7 92 Colorado -21.2
13 Boise State 31.3 53 Pittsburgh 4.6 93 West Virginia -22.0
14 Central Florida 29.0 54 Florida International 4.2 94 Kansas -22.3
15 Kansas State 29.0 55 Vanderbilt 3.8 95 Texas Tech -22.4
16 Tulsa 28.3 56 Air Force 3.6 96 Arizona -22.8
17 North Carolina State 27.8 57 Rutgers 3.6 97 Minnesota -23.4
18 UTEP 27.5 58 Arkansas 3.6 98 Central Michigan -23.7
19 Georgia 27.2 59 Maryland 3.4 99 Navy -24.2
20 Mississippi State 26.8 60 Georgia Tech 2.3 100 SMU -26.4
21 Florida State 25.2 61 Houston 1.9 101 UNLV -28.1
22 Wisconsin 24.9 62 Iowa 1.4 102 Memphis -28.5
23 UCLA 23.9 63 Iowa State 1.2 103 Louisiana Monroe -30.0
24 Stanford 23.8 64 Kentucky 0.9 104 Wake Forest -30.1
25 Ohio State 23.6 65 Bowling Green 0.5 105 Marshall -31.5
26 Northwestern 22.9 66 Washington State 0.0 106 Kent State -33.2
27 Northern Illinois 22.7 67 Nevada -0.9 107 Colorado State -34.6
28 Oregon 21.6 68 Virginia -2.1 108 Indiana -34.6
29 Ohio 20.8 69 Texas A&M -2.2 109 Baylor -35.3
30 Troy 20.2 70 Illinois -2.7 110 North Carolina -36.2
31 Connecticut 20.2 71 Mississippi -3.3 111 Western Kentucky -36.7
32 Missouri 19.9 72 Arizona State -4.0 112 San Jose State -37.7
33 Alabama 19.3 73 North Texas -4.1 113 Akron -38.2
34 Notre Dame 19.1 74 Washington -5.6 114 Toledo -40.5
35 Penn State 18.8 75 Boston College -5.8 115 Michigan -44.7
36 Middle Tennessee 17.9 76 Miami (OH) -5.9 116 UAB -47.4
37 Duke 17.6 77 Buffalo -6.2 117 Eastern Michigan -49.4
38 Army 17.2 78 Tennessee -7.8 118 Louisiana Lafayette -51.8
39 South Florida 13.4 79 Syracuse -8.4 119 New Mexico -54.7
40 Michigan State 13.4 80 Cincinnati -9.2 120 Tulane -76.9

All of which sets the stage for 2011. Readers that purchased Football Outsiders Almanac 2011 know that the F/+ projections favor Alabama as the favorite to win this year's national championship. This year's FEI projections, based primarily on Program FEI, returning starters and recruiting data, also love the Crimson Tide. As has been the case in the past, the projections will play a part (reduced each week) in the FEI ratings until week seven. FEI forecasts for every FBS game will also be posted on my site.

2011 Projected FEI
Rk Team FEI Rk Team FEI Rk Team FEI
1 Alabama .275 41 Georgia Tech .068 81 Florida International -.080
2 LSU .246 42 Navy .064 82 Temple -.086
3 Oklahoma .235 43 BYU .063 83 Arkansas State -.090
4 Virginia Tech .221 44 Michigan State .056 84 Fresno State -.094
5 Auburn .205 45 Oregon State .053 85 Kansas -.098
6 Oregon .192 46 Arizona .052 86 Louisiana Monroe -.098
7 Florida State .190 47 Rutgers .048 87 Indiana -.103
8 Stanford .183 48 Utah .047 88 Hawaii -.104
9 Ohio State .183 49 Texas Tech .045 89 UAB -.104
10 Florida .180 50 Tennessee .043 90 Iowa State -.109
11 Boise State .178 51 Mississippi .042 91 Ball State -.112
12 Arkansas .176 52 Illinois .035 92 Toledo -.112
13 Pittsburgh .175 53 Louisville .026 93 Army -.121
14 USC .170 54 Air Force .025 94 Kent State -.121
15 West Virginia .168 55 Tulsa .018 95 Ohio -.123
16 Clemson .165 56 Nevada .010 96 Marshall -.126
17 Georgia .156 57 Northern Illinois .010 97 Miami (OH) -.129
18 North Carolina State .153 58 Northwestern .008 98 Bowling Green -.134
19 Missouri .152 59 Southern Mississippi .003 99 Western Kentucky -.137
20 Oklahoma State .145 60 Central Florida -.004 100 Middle Tennessee -.140
21 South Carolina .140 61 Virginia -.010 101 Louisiana Tech -.142
22 Notre Dame .136 62 UCLA -.011 102 Wyoming -.148
23 TCU .135 63 Kansas State -.019 103 Washington State -.150
24 Wisconsin .125 64 Vanderbilt -.019 104 UTEP -.159
25 Miami .117 65 Purdue -.021 105 San Jose State -.159
26 Arizona State .116 66 California -.021 106 Florida Atlantic -.175
27 Nebraska .106 67 SMU -.027 107 Tulane -.177
28 Boston College .106 68 Houston -.030 108 North Texas -.178
29 Iowa .100 69 Syracuse -.031 109 Buffalo -.182
30 Penn State .097 70 San Diego State -.032 110 Rice -.186
31 Cincinnati .095 71 Colorado -.033 111 Louisiana Lafayette -.192
32 Mississippi State .088 72 Wake Forest -.034 112 New Mexico -.194
33 North Carolina .084 73 Washington -.038 113 Utah State -.197
34 Texas A&M .082 74 Minnesota -.038 114 Idaho -.202
35 Michigan .082 75 East Carolina -.040 115 Akron -.204
36 Maryland .081 76 Central Michigan -.045 116 Eastern Michigan -.223
37 Kentucky .071 77 Western Michigan -.049 117 Memphis -.224
38 South Florida .071 78 Troy -.059 118 Colorado State -.226
39 Connecticut .071 79 Duke -.063 119 UNLV -.250
40 Texas .069 80 Baylor -.077 120 New Mexico State -.271

Posted by: Brian Fremeau on 01 Sep 2011

10 comments, Last at 11 Oct 2011, 2:12pm by

Comments

1
by jpeta :: Thu, 09/01/2011 - 1:48pm

It's x-mas morning at FEI headquarters and we get the presents. Can you remind us, FEI is adjusted for opponent strength - are OFEI and DFEI as well? Also at the FEI level can you explain how opponent adjustments work. If Stanford starts at its own 35 vs. San Jose St and scores a TD and then does the same vs. Oregon (from the same starting point) how does the drive efficiency calculation change?

6
by Brian Fremeau :: Thu, 09/01/2011 - 4:00pm

The opponent adjustments are done at the game level, not at the drive level. In other words, I can do a comparison of a complete game opponent-adjusted FEI, OFEI, and DFEI if the same raw efficiency were played against San Jose State or against Oregon. Probably would be better if that was the subject of a whole column.

Yes, OFEI, DFEI, and FEI are all opponent-adjusted. The special teams value table is not opponent adjusted data.

2
by aaa (not verified) :: Thu, 09/01/2011 - 2:22pm

Are the S&P rankings going to be posted before the weekend?

8
by aaa (not verified) :: Thu, 09/01/2011 - 4:42pm

By that, I meant on-line.

3
by killabe7 :: Thu, 09/01/2011 - 3:08pm

Both FEI and S&P still LOVE Auburn this year. Vegas does not - set the o/u at 6 wins...seems intersing...

4
by Harrison Bergeron (not verified) :: Thu, 09/01/2011 - 3:25pm

I'm not sure how much FEI and S&P account for the fact that Auburn has lost the best offensive player in the country and (arguably) the best defensive player in the country since last year. In fact, they're only returning six starters, fewest in the country. Plus, their recent recruiting history isn't like Alabama/Florida/Texas/USC, where they have a wave of 5-star recruits ready to replace those that just departed.

Also, keep in mind that last year Auburn beat Mississippi State by 3, Clemson by 3 in OT, Kentucky by 3, South Carolina by 8, LSU by 7, Alabama by 1, and Oregon by 3. Teams don't usually go 7-0 in one-possession games, and it would be reasonable to expect their record in tight games to even out a bit this year even if they brought everybody back.

5
by Brian Fremeau :: Thu, 09/01/2011 - 3:50pm

I think Bill and I pretty much agree with all of this. However, the Tigers' Program F/+ rating is No. 13, 5YR recruiting is No. 11, and Program FEI is No. 7 (could be better, but Auburn stacks up well in these components of the formula).

The projection model does recognize that Auburn will take a step back. The projection model, however, has nothing to compare to Auburn. Never before has a team been so good in one season and then lost so many critical parts. We could have arbitrarily assigned some additional weight to Auburn's personnel losses, but there wasn't a way to do so without it being exactly that: arbitrary.

Our models are designed to maximize accuracy of projections for as many teams as possible. We know the model will miss on some teams. It certainly looks like Auburn is an easy candidate for a misfit for the model. I'm holding out hope that we'll get the over on 6 wins right, but I think they'll have a hard time winning 8 or 9.

It should also be noted that though F/+ projects Auburn at No.4 overall, it picks the Tigers to finish 4th in the SEC West in terms of mean conference wins:
1. Alabama (6.9)
2. LSU (5.7)
3. Arkansas (5.3)
4. Auburn (5.1)

7
by Will Allen :: Thu, 09/01/2011 - 4:41pm

Minnesota may give some insight as to the value of coaching with regard to game preparation, and in-game decisions (coaching value exclustive of recruiting, in other words), since their new coach has taken a decidedly more old school approach to execution, especially on defense. At least, that is what is apparent to me from afar, which admittedly has its limits. I've read the usual rhetoric surrounding a new coach through the years, and this guy Minnesota stumbled upon (believe me, it had nothing to do with intent by Minnesota's bumbling AD) seems strikingly different from other guys, at least since they had Holtz for a couple years on the sidelines.

Now, I have no idea whether the guy can recruit like Holtz, and absent decent recruiting, nothing happens in the long run, but in the short run, the Gophers may be an interesting experiment in coaching value this year.

Now watch USC beat them by eight touchdowns on Saturday.

9
by Cegal25 :: Fri, 09/02/2011 - 1:15am

Brian:

Does FO make available all of the data in the FOA 2011 in a spreadsheet format? The data is very useful, but very cumbersome when trying to do matchup analysis. Thank you again for all of the hard work you do.

10
by <Will> (not verified) :: Tue, 10/11/2011 - 2:12pm

Hi, I'm a college student and was wondering how i could get into this line of work. Just any example of how you went about it or others around you would be greatly appreciated, thanks for your time.