# Yet Another Method Of Ranking Teams

Submitted by biakabutuka ex… on December 9th, 2012 at 1:02 AM

## Intro

An idea has been nagging me for the last few weeks that goes like this: to say a team's goal is to win the game is needlessly over-specific. Any rational team’s goal is to have the lead all game. So every second you don’t have the lead is a failure to some degree. Not only that, but a measurable failure.

With this in mind, I was surprised that none of the computerized rankings sound like they take lead time into account. Sagarin, Massey, Colley, Wolfe and Harris don’t mention it on their sites. This fed my curiosity of whether it’s any good as a metric. For the record, I didn't seek out to prove anything. Most of all, I just wanted to take a look at the season through a different lens. With that said, onto the…

## Data

I started with the 2012 per-drive data from cfbstats.com (H/T to mgousesr TSS for pointing me there), then calculated lead times in each game. Then I weighted those leads against the strength of the team the lead was against. I used my own results from the first calculation for the team strength metric, so that my results were not skewed in the slightest by anyone else’s formula. Then I weighted those results one more time for good measure, so opponents’ opponents are weighed in. The only factor considered is amount of time teams had the lead in games.

### Charts

The Norm 1 (or normalized 1 time) ratings rank teams based on the amount of time they had a lead this season, nothing else. Norm 2 weights lead times against the Norm 1 rating of the opponent. Norm 3 weights lead times against the Norm 2 rating of the opponent.

The list, in three parts:

Top teams in graph form:

### Some important notes with the data and/or formula

• No 2-pt conversions or missed extra points are accounted for because the data I used doesn’t mention them. All touchdowns are assumed to be 7 points.
• After calculating the running score in games, some of the outcomes of games were...off. Just a little bit. This is probably because of the last bullet.
• Tie scores are ignored. I think it might be worth it to value them somehow, but I didn’t have time.
• Because of the last caveat, a constantly tied slugfest is worth less than a back and forth game. This should only affect the kinds of teams that get into these kinds of games, i.e. the middling ones, but it still bothers me.
• To add to the last point, I therefore believe the very best and very worst teams are ranked the most accurately
• Overtime is ignored
• Even with team weightings, you are rewarded slightly more for leading the whole game against #19 Utah State than for leading for half of the game against #1 Alabama.
• You are rewarded more for giving away a game where you led all the way than for being on the other side of that.
• Injuries that affect today’s team are not factored into yesterday’s results.
• A strategy to wear other teams out may arguably be lead-agnostic early in the game. However, Oregon and Alabama are the kings of this strategy—in radically opposite ways no less—and they are the top two teams rated. So there’s that.

But anyway, onto…

## Analysis

Well, the results are unique, that's for sure. But they're not exactly out of left field, either. And some of them are downright acceptable.

### Surprise Bullets

• Michigan: I have to admit, part of the reason I did this was to prove that Michigan is better than their record. This may still be true, but not according to my formula. Why would this be? It's simple, really. I've given them a lot of credit for playing top teams, but they rarely led in these games. Deep down, what's the difference between losing all game and never showing up? In regards to the Alabama game I can say not much. Furthermore, their most dominant performances came against the worst opponents on their schedule. That shouldn't be a surprise, but if it’s true, neither should the fact that they are properly rated. I am disappoint.
• Oklahoma State: A 7-5 team that was competitive in every loss but one is my #6 team. I wonder if their fans and MSU’s fans have a support group, and if so, where would they find a couch.
• Ole Miss: I barely noticed this team this year. I wonder how their fans feel about their season. They were 6-6 but they may be in for a bounce next year if nobody leaves.
• Utah State: Holy crap did they ever have an under the radar season. But they do drop from #4 to #19 once you factor strength of schedule. Let’s not play these guys, you guys.

### Not Surprise Bullets

• Notre Dame is not the best team but they are good. They look better when the strength of opponent is factored in (#4 vs #8).
• Ohio State is not an elite team. That's probably partly why Michigan played them so close. Like Notre Dame, the strength of opponents they led against does bump them up quite a bit (from #26 to #13).
• Texas A&M beating Alabama is somewhat less of a surprise—they’re my #3 team.
• Florida is overrated, said everyone ever until they beat Florida State. But guess who else is overrated? Florida State (their line happens to be one of the most interesting ones, though).
• Michigan State is...marginally better than Michigan? Well, no one would be surprised if you had claimed this in August.
• Stanford beat Oregon, had a tougher schedule, and won the Pac 12. So why do a lot of people just assume that Oregon is the better team? These results might explain why. Oregon was actually a lot more dominant all season, all else being equal. I mean if you don’t count all the stuff that counts.

### Takeaways

• Proving my assumptions about Notre Dame and Ohio State almost offsets the disappointment in not proving my assumptions about Michigan.
• The championship game should probably be Oregon-Alabama, just like a lot of people assumed for most of the season. Go BCS.
• In a 4-team playoff, Notre Dame and their undefeated record would deserve a shot. As would Texas A&M, owners of the best win by any team all season.
• These results would be considerably more controversial if Georgia had defeated Alabama, or Michigan had eked out a 2011-esque win against Notre Dame. But none of this happened and maybe there’s a lesson in that.
• I do think that completely removing wins and losses from the equation takes a little of the fun out of it. And it leads to teams with 6 wins being rated higher than BCS juggernauts…like Northern Illinois. But on the other hand, I don’t see why this metric couldn’t be used in unison with a few others in determining how dominant of a season a team had.
• Vegas, which you may know is in the business of predicting games, would no doubt give less than ten points to Bama against Oregon, the current line against Notre Dame. Hey, if Vegas agrees with my relatively simple formula more than the one the big boys use, maybe my poll is better.**

Phew, sorry for the long post. If anyone’s interested, I would consider running this against previous seasons, and hopefully writing a lot less. I would also consider tweaking the formula if the improvements are obvious and consistently better.

* I can’t think of a good name for this. “Lead metric”?

** for the record, Vegas does disagree with some of my rankings. For example, in the bowl games Vegas favors Miss State over Northwestern and Stanford over Wisconsin. Could be because the Big Ten sucked and I didn’t weight the data properly. Also, I already warned you about middling teams. Ctrl-F it.

# MICHIGAN #1 in B1G (sagarin computer rank)

Submitted by michelin on October 14th, 2012 at 10:46 AM

MIchigan is the top team in the B1G according to The Sagarin poll.  Below I list the PREDICTOR ratings--which are the best in actually predicting game outcomes.  I also list the overall national rank according to these ratings.*

1. Michigan  (#13 overall, rating 85.33)

2. Ohio (#18 overall, rating 83.15) INELIGIBLE for postseason

3. Neb (#23, rating 81.74)

4. Wisconsin (#27, rating 79.69)

5. PSU (#28, 79.64) ALSO INELIGIBLE for postseason

6. MSU (#36. 77.2)

One predicts the outcome of future games by subtracting the two Sagarin PREDICTOR ratings (with + or -3 for Home Field).  So, if we play Wisc in INDY for the B1G title, we should be favored by 5-6 points.  If Ohio were not ineligible and Michigan played them in INDY, UM would beat Ohio.   In Columbus, the game would be essentially a tossup (less than a one point margin).   Also, Michigan would be favored over MSU by 8 points on a neutral field and  by 11 points this coming week in Ann Arbor (+3 for home field).

I don't know what the Vegas point spread is, but I suspect that it will be smaller, since UM-MSU is a rivalry game.

*Michigan also is #1 when Sagarin's PREDICTOR ratings are averaged with the ELO-CHESS ratings.  The latter do not consider point margins and are not as good in predicting actual game outcomes.  Regrettably, the overall BCS computer rankings use  the ELO-CHESS Sagarin ratings--as well as other computer polls that often overweigh WL records and underweigh SOS.  So, we will not do as well when the BCS computer rankings come out.  However, I do not believe that any of these alternative ranks has been shown to do as well as the Sagarin PREDICTOR ratings in forecasting actual game outcomes.  And that's what's important in predicting the rest of the UM season.

http://usatoday30.usatoday.com/sports/sagarin/fbt12.htm

# Week #14 National Rankings and Gator Bowl Predictions

Submitted by Enjoy Life on December 14th, 2010 at 5:01 PM

Where's Waldo (i.e. The Offense)?: Yikes – 7 points?? An average of just 20.7 points over the last 3 games. Because of poor execution and unforced errors, the offense slowed to a dismal pace (20.7 points per game would rank #104). Let's hope all they need is a few weeks rest.

Synopsis: Looking at Conference Only game stats, the offense ended the year at #4 and the defense at #10 (thank you, Indiana). Last year the offense was #9 and the defense was #11 in conference only games. A comparison of national rankings for 2008 – 2010 is below.

I use scoring stats because yardage stats are inherently flawed. According to the FEI (Fremeau Efficiency Index) rankings at Football Outsiders, Michigan ended the regular season ranked #44 overall (4.8% better than the average FBS team) with a SoS ranking of #66. The offense is ranked #2 and the defense is ranked #103. Field Position Advantage is #91 while Field Goal Efficiency is #120.

For the Gator Bowl, a rough calculation of the FEI has Mississippi State favored by 4 points. Using the Sagarin Predictor, MSU is favored by 5 points. Vegas has MSU favored by 5.

2008 – 2010 National Rankings: Not any surprises. The offense has gotten much better each year and the defense has gone from terrible to worse to "that which cannot be mentioned".

DETAILS: Here are the FEI numbers ( FEI Forecasts and Football Outsiders FEI ). FEI is a weighted and opponent adjusted season efficiency and is expressed as a percentage as compared with an average FBS team. The average team will have an index of approximately 0.00. Teams below average have negative index values.

Note that FEI completely excludes all non-FBS data (the W-L record is only for FBS games, etc.). Therefore, you need to add 1 to FBS-MW to get the final predicted wins for M this year. Or, if you use FBS-RMW, you need to add 1 to the current W-L record to get the final predicted wins for M this year. BTW, the difference between FBS-MW and FBS-RMW is the number of FBS games each team would have been expected to win to date.

The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams. I've included the GE basic data so you can see the impact of adjusting for opponent.  (See: Football Outsiders Our Basic College Stats )

Here are the Sagarin Ratings.

Sagarin uses two basic ratings: PREDICTOR (in which the score MARGIN is the only thing that matters) and ELO-CHESS (in which winning and losing only matters, the score margin is of no consequence). The overall rating is a synthesis of the two diametrical opposites, ELO-CHESS and PREDICTOR.

Per Sagarin: ELO-CHESS is “very politically correct. However, it is less accurate in its predictions for upcoming games than is PREDICTOR”.

Here is the basic data for Michigan (each individual week followed by totals and then average per game). I've included Total Possessions for Offense & Defense along with the calculated data per possession. Number of possessions do not include running out the clock at the half or end of game. Offense Plays and Defense Plays are better indicators than Time of Possession.

Using Scoring Offense and Scoring Defense National Rankings for the past 5 years (FBS AQ teams only), this table shows the percentage of teams that finish the season with a +WLM and a +5 WLM. For example, teams that finished in the Top 40 in both offense and defense had a 100% chance to be +WLM and an 82% chance to be +5 WLM (9-4 or better).

Each year, of the 66 FBS AQ teams, 65% (43 teams) end up with a + WLM and 36% (24 teams) end up with a +5 WLM.

# Week #12 National Rankings and Predictions for osu

Submitted by Enjoy Life on November 24th, 2010 at 11:04 AM

It's The Offense: How many games can you win without scoring a point in the first half? How many games can you win when the offense leaves 21-35 points off the board? How many games can you win if the offense makes 8 unforced errors (not TOs, but overthrowing wide open receivers, dropped passes, missed FGs, not recovering an on-side kick, etc.)? Not very many – even if the defense plays well. Michigan has a good chance to beat that school down south IF THE OFFENSE MERELY PLAYS WELL, REGARDLESS OF THE DEFENSE! If the offense continues to stop themselves, this will be fugly. I say the offense gets it done and we shock the world. Meeechigan by 10.

Synopsis: Well, that totally sucked! The defense went from the best game of the year to the absolute worst. Combine that with the offense having a poor day and the outcome was obvious.

I use scoring stats because yardage stats are inherently flawed. According to the FEI (Fremeau Efficiency Index) rankings at Football Outsiders, Michigan is ranked #40 overall (7.4% better than the average FBS team) with a SoS ranking of #56. The offense is ranked #1 and the defense is ranked #103 (D was ranked #100 last week). Field Position Advantage is #84 while Field Goal Efficiency is #120.

M is predicted to win between 6.7 and 7.1 games (excluding bowl game but adjusted with +1 for M's one FCS opponent). Based on the FEI, M would have been expected to win 5.6 FBS games to date (we have won 6.0 FBS games to date).

A rough calculation of the FEI has osu favored by 14. Using the Sagarin Predictor, osu is favored by 21 points. Vegas opened with osu favored by 19.5.

In the Big 10, M is averaging 2.7 points per possession (PPP) and 38 YPP. The defense is giving up 3.0 PPP and 35 YPP. With an average of 12 possessions per game for each team, this translates into a 3.6 point disadvantage for Michigan. (In OOC games, this was a 20 point advantage.)

DETAILS: Here are the FEI numbers ( FEI Forecasts and Football Outsiders FEI ). FEI is a weighted and opponent adjusted season efficiency and is expressed as a percentage as compared with an average FBS team. The average team will have an index of approximately 0.00. Teams below average have negative index values.

Note that FEI completely excludes all non-FBS data (the W-L record is only for FBS games, etc.). Therefore, you need to add 1 to FBS-MW to get the final predicted wins for M this year. Or, if you use FBS-RMW, you need to add 1 to the current W-L record to get the final predicted wins for M this year. BTW, the difference between FBS-MW and FBS-RMW is the number of FBS games each team would have been expected to win to date.

The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams. I've included the GE basic data so you can see the impact of adjusting for opponent.  (See: Football Outsiders Our Basic College Stats )

Here are the Sagarin Ratings.

Sagarin uses two basic ratings: PREDICTOR (in which the score MARGIN is the only thing that matters) and ELO-CHESS (in which winning and losing only matters, the score margin is of no consequence). The overall rating is a synthesis of the two diametrical opposites, ELO-CHESS and PREDICTOR.

Per Sagarin: ELO-CHESS is “very politically correct. However, it is less accurate in its predictions for upcoming games than is PREDICTOR”.

Here is the U-M vs. Opponent National Statistical Rankings with the advantage for each category indicated (all categories within 10% are considered a "push").

Here are the week by week National Statistical Rankings for Michigan (cumulative thru the week indicated):

I have included the major rankings for offense and defense but scoring rankings show the best correlation to winning and losing. Scoring rankings are based on PPG. Rushing, Passing, and Total rankings are based on YPG.

Here is the basic data for Michigan (each individual week followed by totals and then average per game). I've included Total Possessions for Offense & Defense along with the calculated data per possession. Number of possessions do not include running out the clock at the half or end of game. Offense Plays and Defense Plays are better indicators than Time of Possession.

Using Scoring Offense and Scoring Defense National Rankings for the past 5 years (FBS AQ teams only), this table shows the percentage of teams that finish the season with a +WLM and a +5 WLM. For example, teams that finished in the Top 40 in both offense and defense had a 100% chance to be +WLM and an 82% chance to be +5 WLM (9-4 or better).

Each year, of the 66 FBS AQ teams, 65% (43 teams) end up with a + WLM and 36% (24 teams) end up with a +5 WLM.

# Week #11 National Statistics and Predictions for Wisconsin

Submitted by Enjoy Life on November 17th, 2010 at 1:17 PM

Glass Half Full: Michigan is 7-3! Currently only 42 of the 120 FBS teams have a record of 7-3 or better.Yes, the next two games will be the most difficult of the year but a winning season is guaranteed as is a bowl berth. A lot of folks seem to have written off the rest of the season and are proclaiming an overall 7-5 record. I am officially confused.

Synopsis: For the second week in a row, the defense played better! After 10 games, Michigan is currently ranked #14 in scoring offense and #93 in scoring defense. M allowed just 0.9 points per possession at Purdue which is actually the best we have done all year including OOC games.

I use scoring stats because yardage stats are inherently flawed. According to the FEI (Fremeau Efficiency Index) rankings at Football Outsiders, Michigan is ranked #41 overall (7.5% better than the average FBS team) with a SoS ranking of #85. The offense is ranked #2 and the defense is ranked #100 (D was ranked #109 last week). Field Position Advantage is #75 while Field Goal Efficiency is #118.

M is predicted to win between 7.1 and 7.4 games (excluding bowl game but adjusted with +1 for M's one FCS opponent). Based on the FEI, M would have been expected to win 5.7 FBS games to date (we have won 6.0 FBS games to date).

FEi has the game at Wisc 41 - M 30 with a 72% projected win expectation for W. Using the Sagarin Predictor, Wisconsin is favored by 4.5 points. Vegas opened with W favored by 5.5. (After Wisconsin scored 83 points against Indiana, they are ranked #8 in scoring offense – better than M @ #14. W is ranked #20 in scoring defense but Illinois was ranked #12 in scoring D before they played us. FEI does not include garbage time points and has M @ #2 in Offense and Wsky @ #4 in offense.)

This chart shows the improvement in the defense over the last 2 games. It excludes the OT points (and possessions) against Illinois.

In the Big 10, M is averaging 2.7 points per possession (PPP) and 38 YPP. The defense is giving up 2.8 PPP and 33 YPP. With an average of 12 possessions per game for each team, this translates into a 1.2 point disadvantage for Michigan. (In OOC games, this was a 20 point advantage.)

DETAILS: Here are the FEI numbers ( FEI Forecasts and Football Outsiders FEI ). FEI is a weighted and opponent adjusted season efficiency and is expressed as a percentage as compared with an average FBS team. The average team will have an index of approximately 0.00. Teams below average have negative index values.

Note that FEI completely excludes all non-FBS data (the W-L record is only for FBS games, etc.). Therefore, you need to add 1 to FBS-MW to get the final predicted wins for M this year. Or, if you use FBS-RMW, you need to add 1 to the current W-L record to get the final predicted wins for M this year. BTW, the difference between FBS-MW and FBS-RMW is the number of FBS games each team would have been expected to win to date.

The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams. I've included the GE basic data so you can see the impact of adjusting for opponent.  (See: Football Outsiders Our Basic College Stats )

Here are the Sagarin Ratings.

Sagarin uses two basic ratings: PREDICTOR (in which the score MARGIN is the only thing that matters) and ELO-CHESS (in which winning and losing only matters, the score margin is of no consequence). The overall rating is a synthesis of the two diametrical opposites, ELO-CHESS and PREDICTOR.

Per Sagarin: ELO-CHESS is “very politically correct. However, it is less accurate in its predictions for upcoming games than is PREDICTOR”.

Here is the U-M vs. Opponent National Statistical Rankings with the advantage for each category indicated (all categories within 10% are considered a "push").

Here are the week by week National Statistical Rankings for Michigan (cumulative thru the week indicated):

I have included the major rankings for offense and defense but scoring rankings show the best correlation to winning and losing. Scoring rankings are based on PPG. Rushing, Passing, and Total rankings are based on YPG.

Here is the basic data for Michigan (each individual week followed by totals and then average per game). I've included Total Possessions for Offense & Defense along with the calculated data per possession. Number of possessions do not include running out the clock at the half or end of game. Offense Plays and Defense Plays are better indicators than Time of Possession.

Using Scoring Offense and Scoring Defense National Rankings for the past 5 years (FBS AQ teams only), this table shows the percentage of teams that finish the season with a +WLM and a +5 WLM. For example, teams that finished in the Top 40 in both offense and defense had a 100% chance to be +WLM and an 82% chance to be +5 WLM (9-4 or better).

Each year, of the 66 FBS AQ teams, 65% (43 teams) end up with a + WLM and 36% (24 teams) end up with a +5 WLM.

# Week #10 National Rankings and Predictions for Purdue

Submitted by Enjoy Life on November 10th, 2010 at 8:36 PM

Synopsis: Wooo Baby – Now we can all relax! With all the points we scored and all the points they scored, the stats are going to be pretty funky. After 9 games, Michigan is currently ranked #12 in scoring offense and #104 in scoring defense. Without the 20 points allowed in OT, the D would be ranked #97. The 5 TOs put the D in terrible field position and resulted in 17 possessions for Illinois. M allowed 2.6 points per possession in regulation which is actually the best we have done in Big10 play. So, yes, the D played better this week!

I use scoring stats because yardage stats are inherently flawed. According to the FEI rankings at Football Outsiders, Michigan's defense actually improved and is now ranked #109 (it was #112 last week).

Based on the FEI (Fremeau Efficiency Index), Michigan is ranked #41 overall (7.8% better than the average FBS team) with a SoS ranking of #82. The offense is ranked #1 and the defense is ranked #109. Field Position Advantage is #84 while Field Goal Efficiency is #117.

M is predicted to win between 7.2 and 7.4 games (excluding bowl game but adjusted with +1 for M's one FCS opponent). Based on the FEI, M would have been expected to win 4.8 FBS games to date (we have won 5.0 FBS games to date).

FEI has the game as M 42 - Purdue 20 with a 89.7% predicted win expectation (Purdue has the #113 ranked O and #64 D). Using the Sagarin Predictor, Michigan is favored by 11.7 points. Vegas has M favored by 13.

This line chart differentiates between OOC and Big10 points per possession. Note that the defense PPP did not get worse even including the 6.7 PPP in OT. In the Big 10, M is averaging 2.9 points per possession (PPP) and 41 YPP. The defense is giving up 3.3 PPP and 38 YPP. With an average of 12 possessions per game for each team, this translates into a 4.8 point disadvantage for Michigan. (In OOC games, this was a 20 point advantage.)

For those who want yardage stats, here they are – split by OOC and Big10 games. The good news is that the yardage defense has been pretty consistent for the last 3 games. The bad news is that the defense is consistently horrible.

DETAILS: Here are the FEI numbers ( FEI Forecasts and Football Outsiders FEI ). FEI is a weighted and opponent adjusted season efficiency and is expressed as a percentage as compared with an average FBS team. The average team will have an index of approximately 0.00. Teams below average have negative index values.

Note that FEI completely excludes all non-FBS data (the W-L record is only for FBS games, etc.). Therefore, you need to add 1 to FBS-MW to get the final predicted wins for M this year. Or, if you use FBS-RMW, you need to add 1 to the current W-L record to get the final predicted wins for M this year. BTW, the difference between FBS-MW and FBS-RMW is the number of FBS games each team would have been expected to win to date.

The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams. I've included the GE basic data so you can see the impact of adjusting for opponent.  (See: Football Outsiders Our Basic College Stats )

Here are the Sagarin Ratings.

Sagarin uses two basic ratings: PREDICTOR (in which the score MARGIN is the only thing that matters) and ELO-CHESS (in which winning and losing only matters, the score margin is of no consequence). The overall rating is a synthesis of the two diametrical opposites, ELO-CHESS and PREDICTOR.

Per Sagarin: ELO-CHESS is “very politically correct. However, it is less accurate in its predictions for upcoming games than is PREDICTOR”.

Here is the U-M vs. Opponent National Statistical Rankings with the advantage for each category indicated (all categories within 10% are considered a "push").

Here are the week by week National Statistical Rankings for Michigan (cumulative thru the week indicated):

I have included the major rankings for offense and defense but scoring rankings show the best correlation to winning and losing. Scoring rankings are based on PPG. Rushing, Passing, and Total rankings are based on YPG.

Here is the basic data for Michigan (each individual week followed by totals and then average per game). I've included Total Possessions for Offense & Defense along with the calculated data per possession. Number of possessions do not include running out the clock at the half or end of game. Offense Plays and Defense Plays are better indicators than Time of Possession.

Using Scoring Offense and Scoring Defense National Rankings for the past 5 years (FBS AQ teams only), this table shows the percentage of teams that finish the season with a +WLM and a +5 WLM. For example, teams that finished in the Top 40 in both offense and defense had a 100% chance to be +WLM and an 82% chance to be +5 WLM (9-4 or better).

Each year, of the 66 FBS AQ teams, 65% (43 teams) end up with a + WLM and 36% (24 teams) end up with a +5 WLM.

# Week #9 National Rankings and Predictions for Illinois

Submitted by Enjoy Life on November 3rd, 2010 at 3:08 PM

Insanity: Doing the same things over and over again and expecting different results.

Synopsis: This is fracking beyond insanity. Bend Don't Break My Ass! It's time for Kamikaze Defense!! I hate the 3 man rush because it is passive and football is not a passive sport. Bend don't break is also passive. I've just watched 2 NFL teams compensate for really bad secondaries by blitzing on just about every down. The DBs only have to cover for a few yards because they know it has to be a quick pass. It also puts lots of people in the box to stop the run. The only other hope is takeaways – lots, and lots, and lots of takeaways (each takeaway = one defensive stop!).

After 8 games, Michigan is currently ranked #19 in scoring offense and #89 in scoring defense. Only 1 FBS-AQ team in the last 5 years has had a defense ranked worse than #80 and a +5 WLM (UCLA in 2005: #5 Offense, #108 Defense, +8 WLM). Only 21% of FBS-AQ teams ranked #80 or worse in defense had winning records.

I use scoring stats because yardage stats are inherently flawed. That said, being #89 in scoring defense is simply horrible and getting worse every week. Since these are cumulative stats, getting worse every week is quite a fete feat. According to the FEI rankings at Football Outsiders, Michigan's defense continues to plummet and is now ranked #112.

Based on the FEI (Fremeau Efficiency Index), Michigan is predicted to win between 6.7 and 6.8 games (excluding bowl game but adjusted with +1 for M's one FCS opponent). Based on the FEI, M would have been expected to win 4.1 FBS games to date (we have won 4.0 FBS games to date).

FEI has the game at Illinois 30 - Michigan 28 with a Projected Win Expectation of 53.3% for the Illini. Using the Sagarin Predictor, Illinois is favored by 3.2 points. Vegas has M favored by 3 (really?). Unless M plays their best game of the year AND we get at least +2 TOM, this is going to be deja vu all over again. I have a very bad feeling about this game. Derek Dimke (ILL) is ranked #20 in FGs.

This line chart differentiates between OOC and Big10 points per possession. It shows what has happened since the start of conference play. In the Big 10, M is averaging only 2.7 points per possession (PPP) and 43 YPP. The defense is giving up 3.3 PPP and 43 YPP. With an average of 12 possessions per game for each team, this translates into a 7.2 point disadvantage for Michigan. (In OOC games, this was a 20 point advantage.)

For those who want yardage stats, here they are – split by OOC and Big10 games. The good news is that the yardage defense has been pretty consistent for the last 3 games. The bad news is that the defense is consistently horrible.

DETAILS: Here are the FEI numbers ( FEI Forecasts and Football Outsiders FEI ). FEI is a weighted and opponent adjusted season efficiency and is expressed as a percentage as compared with an average FBS team. The average team will have an index of approximately 0.00. Teams below average have negative index values.

Note that FEI completely excludes all non-FBS data (the W-L record is only for FBS games, etc.). Therefore, you need to add 1 to FBS-MW to get the final predicted wins for M this year. Or, if you use FBS-RMW, you need to add 1 to the current W-L record to get the final predicted wins for M this year. BTW, the difference between FBS-MW and FBS-RMW is the number of FBS games each team would have been expected to win to date.

The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams. I've included the GE basic data so you can see the impact of adjusting for opponent.  (See: Football Outsiders Our Basic College Stats )

Here are the Sagarin Ratings.

Sagarin uses two basic ratings: PREDICTOR (in which the score MARGIN is the only thing that matters) and ELO-CHESS (in which winning and losing only matters, the score margin is of no consequence). The overall rating is a synthesis of the two diametrical opposites, ELO-CHESS and PREDICTOR.

Per Sagarin: ELO-CHESS is “very politically correct. However, it is less accurate in its predictions for upcoming games than is PREDICTOR”.

Here is the U-M vs. Penn State National Statistical Rankings with the advantage for each category indicated (all categories within 10% are considered a "push").

Here are the week by week National Statistical Rankings for Michigan (cumulative thru the week indicated):

I have included the major rankings for offense and defense but scoring rankings show the best correlation to winning and losing. Scoring rankings are based on PPG. Rushing, Passing, and Total rankings are based on YPG.

Here is the basic data for Michigan (each individual week followed by totals and then average per game). I've included Total Possessions for Offense & Defense along with the calculated data per possession. Number of possessions do not include running out the clock at the half or end of game. Offense Plays and Defense Plays are better indicators than Time of Possession.

Using Scoring Offense and Scoring Defense National Rankings for the past 5 years (FBS AQ teams only), this table shows the percentage of teams that finish the season with a +WLM and a +5 WLM. For example, teams that finished in the Top 40 in both offense and defense had a 100% chance to be +WLM and an 82% chance to be +5 WLM (9-4 or better).

Each year, of the 66 FBS AQ teams, 65% (43 teams) end up with a + WLM and 36% (24 teams) end up with a +5 WLM.

# Week #8 National Rankings, Fremeau Efficiency Index, and Sagarin Predictor for PSU (After Bye Week)

Submitted by Enjoy Life on October 29th, 2010 at 11:34 AM

Abbreviated Version: As expected, after a bye week, most of the data did not change. However, the computer analysis (Fremeau and Sagarin) did have significant changes – primarily due to strength of schedule adjustments. Michigan's SoS went from #52 to #77 in the FEI and from #49 to #64 for Sagarin. At the same time, PSU beat lowly Minnesota and their SoS improved slightly from #40 to #36 for the FEI but declined from #45 to #47 for Sagarin. The SoS adjustments have more to do with how all of your opponents did that week rather than whether you win or lose. This significantly changed the rankings and game predictions (see below). Thus, my prediction that the computer analysis would not change very much after the bye week was absolutely wrong!

Synopsis: After 7 games and a bye week, Michigan is currently ranked #17 in scoring offense and #80 in scoring defense (wooo hooo, the defense improved by not playing). According to the FEI rankings at Football Outsiders, Michigan is ranked #93 in total defense (a significant drop from #83 prior to the bye week).

Due to the large swing in computer rankings during the bye week, FEI has Michigan favored by 7 points over Penn State (an initial rough estimate showed M favored by 16 prior to the bye week). Using the Sagarin Predictor, PSU is now favored by 1.5 points (before the bye week M was favored by 2.8 points). Sagarin Elo-Chess has M favored by 3.1 and the Sagarin Overall ranking has M by 0.7 points. (Vegas Odds now have M favored by 3).

I am confused this week why Sagarin has PSU favored and FEI as the game relatively close. Unless M implodes with TOs, IMO this should be a big win.

DETAILS: Here are the FEI numbers ( FEI Forecasts and Football Outsiders FEI ). FEI is a weighted and opponent adjusted season efficiency and is expressed as a percentage as compared with an average FBS team. The average team will have an index of approximately 0.00. Teams below average have negative index values.

Note that FEI completely excludes all non-FBS data (the W-L record is only for FBS games, etc.). Therefore, you need to add 1 to FBS-MW to get the final predicted wins for M this year. Or, if you use FBS-RMW, you need to add 1 to the current W-L record to get the final predicted wins for M this year. BTW, the difference between FBS-MW and FBS-RMW is the number of FBS games each team would have been expected to win to date.

The FEI is a drive based analysis considering each of the nearly 20,000 drives each year in college football. The data is filtered to eliminate garbage time (at the half or end of game) and is adjusted for opponent. A team is rewarded for playing well against good teams (win or lose) and is punished more severely for playing poorly against bad teams than it is rewarded for playing well against bad teams. I've included the GE basic data so you can see the impact of adjusting for opponent.  (See: Football Outsiders Our Basic College Stats )

Here are the Sagarin Ratings.

Sagarin uses two basic ratings: PREDICTOR (in which the score MARGIN is the only thing that matters) and ELO-CHESS (in which winning and losing only matters, the score margin is of no consequence). The overall rating is a synthesis of the two diametrical opposites, ELO-CHESS and PREDICTOR.

Per Sagarin: ELO-CHESS is “very politically correct. However, it is less accurate in its predictions for upcoming games than is PREDICTOR”.

# Hypothetical: Running the NCAA like the English Premier League, 2009

Submitted by DoubleMs on December 15th, 2009 at 6:50 PM
I have always been curious how this would work: Dropping the bottom teams in FBS in favor of the top teams in FCS, very similar to the way that European soccer leagues are run.  In this, I am going to look at results from 2009 in a couple of different ways.

System One: Win-Based

Bottom 5 of the FBS:Eastern Michigan (0-12)
Western Kentucky (0-12)
Miami (Not That Miami) (1-11)
Washington State (1-11)
New Mexico (1-11)

Top 5 (6) of the FCS:
Montana (14-0) - In Championship Game
Villanova (13-1) - In Championship Game
Richmond (11-2) - Lost to App State
Southern Illinois (11-2) - Lost to W&M
William&Mary (11-3) - Lost to Villanova
Appalachian State (11-3) Lost to Montana

Win by Montana would drop out S. Illinois, win by Villanova would drop out Richmond.

System Two: Sagarin Rankings-Based

Bottom 5 Sagarin FBS (it is unlikely these will change):
Western Kentucky: 192
Eastern Michigan: 182
North Texas: 162
New Mexico State: 152
Miami (Not That Miami): 150

Top 5 Sagarin FCS (these might change next weekend):
Villanova: 35
William&Mary: 49
Montana: 61
Richmond: 63
Appalachian State: 75

So let's say we combined these two lists and dropped the bottom four out of the FBS, just for the sake of making promotion simple.  EMU, W. Kentucky, Miami (Not That Miami), and NM State all appear on both lists, and would get bumped down to FCS.  Montana, Villanova, William & Mary, and Appalachian State, the top four teams in the FCS playoff, would be brought up to replace.  The teams would take opened spots in the most local conferences, replacing the bumped teams on the conference schedules.

William & Mary and Villanova would trade conferences with EMU and Miami, because of location.  W. Kentucky would switch with App. State, again due to location, and Montana would switch with NM State.

If the FCS teams managed to win the next year, they would make the cut and get to stay. If they didn't, they would just get bumped back down into their old conferences. The old FBS teams would be required to make the final four in the FCS in order to move up again.

I feel like this would liven up competition in the FCS as well as lighting a fire under the bottom-rung teams in the FBS.  Probably will never happen, but wouldn't it be an amazing change?