Sagarin Rankings

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.

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”.

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?