Week 14 Picks

Happy Thanksgiving!

Last week: 17-6 (.739). Overall: 237-54 (.814).

Picks in BOLD.

OLE MISS at Mississippi State
Texas Tech at TEXAS
Oregon State at No. 13 OREGON
No. 16 FRESNO ST at San Jose St
Arkansas at No. 17 LSU
South Florida at No. 19 UCF
EAST CAROLINA at Marshall
IOWA at Nebraska
MIAMI (FL) at Pittsburgh
Washington St at WASHINGTON
No. 1 ALABAMA at No. 4 Auburn
No. 2 FLORIDA ST at Florida
No. 3 OHIO ST at Michigan
No. 21 Texas A&M at No. 5 MISSOURI
No. 6 CLEMSON at No. 10 South Carolina
No. 25 Notre Dame at No. 8 STANFORD
No. 9 BAYLOR at TCU
Minnesota at No. 11 MICHIGAN ST
Arizona at No. 12 ARIZONA ST
Penn State at No. 15 WISCONSIN
No. 22 UCLA at No. 23 USC
No. 24 DUKE at North Carolina
GEORGIA at Georgia Tech
Louisiana-Monroe at LOUISIANA-LAFAYETTE
Wake Forest at VANDERBILT
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Thank You Notes

With Thanksgiving only a few days away, I wanted to show my gratitude. So I decided to write a few thank you notes.

Thank you, Utah Utes, for playing really well at home this year and somehow beating Stanford.

Thank you, Stanford Cardinal eight-and-nine-offensive-linemen formations, for playing old-school football and beating Oregon…again.

Thank you, Andre Heidari, for kicking the game winning field goal against the Cardinal, giving them their second conference loss.

Thank you, Josh Huff, for bagging on the Granddaddy of Them All and setting your team up for what is to follow.

Thank you, un-named players from the team in Baja Arizona, for obliterating and humbling an Oregon team that may have thought too highly of themselves (and for giving them their second conference loss).

Thank you, Carl Bradford, for your pick six that ended up being the difference maker in the Sun Devils Pac-12-South-Division-title-clinching victory over the UCLA Bruins.

Week 13 Picks

Here’s what I learned last week: USC is a lot better than when ASU played them, Myles Jack is a really good football player, and it turns out that Miami and Tucson aren’t very good.

Last week: 17-6 (.739). Overall: 220-48 (.821).

Picks in BOLD.

Rutgers at No. 18 UCF
Idaho at No. 2 FLORIDA ST
Indiana at No. 3 OHIO ST
No. 4 BAYLOR at No. 10 Oklahoma State
No. 5 OREGON at Arizona
No. 8 MISSOURI at No. 24 Ole Miss
California at No. 9 STANFORD
No. 12 TEXAS A&M at No. 22 LSU
No. 13 MICHIGAN ST at Northwestern
No. 17 ARIZONA ST at No. 14 UCLA
New Mexico at No. 15 FRESNO ST
No. 19 WISCONSIN at No. 25 Minnesota
No. 20 Oklahoma at KANSAS ST
Memphis at No. 21 LOUISVILLE
No. 23 USC at Colorado
BYU at Notre Dame
Cincinnati at HOUSTON
DUKE at Wake Forest
EAST CAROLINA at North Carolina State
Kentucky at GEORGIA
Michigan at IOWA
NEBRASKA at Penn State
Virginia at MIAMI (FL)

I wish NIU would just lose already.

UPDATE: The strengths of schedule below are based on Sagarin’s numbers. According to the NCAA, ASU has the #9 toughest schedule, UCF is at #83, and NIU is at #117 (the NCAA stats do not include DI-AA schedules like Sagarin’s do).

NIU just won’t lose. I’m starting to get annoyed. I’m rooting for Bowling Green to beat Buffalo next week. The Falcons have a lot better chance of beating NIU than the Bulls do.

I’m not an NIU hater, I just don’t think they are better than some of the teams they are ranked ahead of. I find it difficult to swallow that the voters think the NIU Huskies (with the 137th strongest schedule in the nation) are better than Arizona State (8-2 against the sixth strongest schedule) and UCF (8-1 against the #73 schedule). In case you were wondering, yes, there are only 125 teams in Division I-A (FBS). So, yes, there are 12 Division I-AA (FCS) teams that have a more difficult schedule than NIU. I understand that the quality of their conference opponents is out of their control. But here are their non-conference games this year: Iowa (an average Big Ten team who has been average for several years now), Idaho (arguable the worst team in Division I-A football), Eastern Illinois (a decent Division I-AA team that the Huskies only managed to beat by four points), and Purdue (hands-down the worst Big Ten team in existence). I don’t know when those four games were scheduled, but Iowa was last “good” in 2009, Purdue in 2003, and Idaho…well they’re Idaho.

Dear NIU, If you have a weak conference and you want people to respect you as a team (and not just a team with a really good quarterback), you have to schedule some better non-conference games. Love, Stephen

I Don’t Want a College Football Playoff – Part I

…or The Voices of Many Replaced by Those of a Few

I don’t want a college football playoff. I am an actual American who loves college football a lot more than the average Joe, but, for multiple reasons, I want to keep the BCS.

Reason #1 that I don’t want a college football playoff: The College Football Playoff Selection Committee

Currently, there are 13 individuals from different backgrounds and areas of expertise that will be deciding not only which four teams will be in the playoff, but also the seeding of those teams. The latter responsibility is one of equal if not greater importance than who will actually be playing in the semi-final games.

Let’s say for conversation’s sake that each individual has an equal say in who is in the playoff and how they are seeded. I’m sure that in practice it will be more than just individual votes that will decide the teams, but humor me for a moment. With 13 individuals each member of the committee’s decision has a weight of 7.69% (100% / 13) in regards to who gets into the playoff. Let’s compare that to the weight of the current BCS “decision makers.”

Coaches’ Poll

The Coaches’ Poll is made up of 62 different head coaches. Let it be known that I am not an advocate of coaches voting in something that decides who plays for the national championship. They are so all-consumed in preparing for their own games that there is no feasible way for them to watch enough games and read enough game recaps and articles to be able to accurately rank teams outside of their own schedule. Also, I believe there is going to be a bias (positive or negative) towards their own team and the teams on their schedule. I am aware and understand that they often will receive assistance in making their votes and that they are not voting entirely by themselves. However, having 62 voters will negate some of the inaccuracies of coaches voting.

Since the Coaches’ Poll is worth one-third of the BCS formula, each coach’s vote carries a weight of 0.54% (100% / 3 = 33.3% / 62) in the BCS standings or approximately 7% of the weight that one of the members of the new committee carries. The CFB Playoff Committee members’ decision is going to be more than 14 times as important as one of the coaches in the current system.

Harris Poll

The Harris Poll, in my opinion, is the best poll that exists, even though it is given little publicity. First of all, it is made up of former coaches and players, administrators, and members of the media. These are people who can spend a lot more time watching games and reading about college football therefore are able to make more accurate decisions. Also, this poll doesn’t even come out until halfway through the season, thereby (theoretically) eliminating the issue of a team’s preseason ranking affecting their later rankings (i.e. a team has to actually play some games before the voters decide how good they are). There are 105 voters in the Harris Poll, making each voter’s decision worth .32% (100% / 3 = 33.3% / 105) of the BCS rankings or approximately 4.2% as important as a vote from a new committee member. The new committee member’s decision is going to be over 23 times as important as one of the Harris voters in the current BCS system.

Computers

There are currently six computer ranking systems that are averaged to make up the final third of the current BCS rankings. The highest and lowest ranking of each team’s computer rankings are thrown out and the remaining four scores are averaged for their computer ranking. The new playoff selection process will not directly use any type of computer ranking system. This is problematic because of the small sample size being dealt with in college football. With teams only playing 11-14 games against other Division I-A schools, it can be, at times, difficult to gauge their abilities against teams that are not on their schedule. The computer systems, while not perfect by any means, attempt to do that. Theoretically, based on a different number of variables depending on the system, we can look at the computer rankings at the end of the season and have an idea if one team is better than the other even if they haven’t played each other in 10 years. Without using the computers, every decision made about one team being better or worse than a team they haven’t played will come down to the “eye test” or “gut feelings.”

Louisville is a great example right now. Louisville is not ranked in the top 25 by five out of the six computer-ranking systems. But they’re ranked #20 in the BCS because they passed the “eye test” for enough voters to rank them #13 and #14 in the Coaches’ and Harris Polls, respectively. Voters look at the fact that they are 8-1 and rank them highly. But their one loss came against the only quality team on their schedule thus far. Their eight wins have come against a seven teams that are averaging 2.4 wins each and a D-IAA team. I have a hard time believing the Cardinals are better than UCLA, Michigan State, Oklahoma, LSU, Wisconsin and Arizona State as the voters have indicated. If we look at the computers, we would see that the data does not line up at all with the rankings they have received.

Below we can see a comparison of the importance of each individual component of the BCS with the new playoff committee members.

COMPONENT % OF DECISION
Coaches’ Poll Voter .54
Harris Poll Voter .32
Computer Ranking System 5.56
Playoff Committee Member 7.69

There is too much weight being placed on each person’s shoulders in the new committee. I’m not suggesting for a moment that the current BCS system is without flaw. I have a dozen or more ideas that would improve it. However, in the current system, 167 human beings and six computers all have a say (a republican system) in which teams will compete in one of the most important sporting events in the nation every year. But now, 13 human beings (most of who have non-football-related occupations) will decide the fate of my beloved game (an oligarchic system).

I say let’s keep the BCS, fix it, and quit acting like we don’t love every second of the drama that unfolds every season about who the second-best team in the nation is.

Week 12 Picks

Last week: 21-4 (.840). Overall: 203-42 (.829)

UPSET OF THE WEEK: Washington over UCLA (IN LA!). The Huskies’ and Bruins’ only losses have come against Stanford and Oregon with Washington’s one additional loss being at the hands of the Sun Devils (whom UCLA has yet to face). These teams are a pretty even match-up and UW surprises everybody (except me) tomorrow night with the upset win.

Picks in BOLD.

No. 1 ALABAMA at Mississippi State
Syracuse at No. 2 FLORIDA ST
No. 3 OHIO ST at Illinois
No. 4 STANFORD at USC
Texas Tech vs. No. 5 BAYLOR
Utah at No. 6 OREGON
No. 25 Georgia at No. 7 AUBURN
Georgia Tech at No. 8 CLEMSON
Florida at No. 10 SOUTH CAROLINA
No. 12 OKLAHOMA ST at No. 24 Texas
WASHINGTON at No. 13 UCLA
No. 16 MICHIGAN ST at Nebraska
No. 17 UCF at Temple
Iowa State at No. 18 OKLAHOMA
Oregon State at No. 19 ARIZONA ST
Houston at No. 20 LOUISVILLE
Indiana at No. 22 WISCONSIN
No. 23 MIAMI (FL) at Duke
Washington State at ARIZONA
Cincinnati at RUTGERS
Troy at OLE MISS
LOUISIANA-LAFAYETTE at Georgia State
Maryland at VIRGINIA TECH

Scoring Offenses and Defenses Ranked Better 2.0 – Pac-12 Edition

As I have thought more about how to better rank offenses and defenses other than just total yards or average points per game, I began to look at percentage of opponents average points scored and given up. I have two issues with my original method of calculating the expected points percentages: 1. the points per game number being used included defensive and special teams scores and 2. it did not take into account the number of plays used to score those points.

Regarding the second problem, if both the blue team and the red team average 45 points per game and their opponents give up an average of 30 points, they both will have an expected offensive scoring percentage of 150%. However, if the blue team runs an average of 85 plays per game and the red team delivers the same results while only running an average of 75 plays per game, we can now see that the red team has a more productive (i.e. better) offense.

Therefore, I have made two major changes to the calculations. First, only offensive points will be figured into the calculations (no defensive or special teams scores). That should have already been done; I just failed to realize it until now. Secondly, the figure will now be an expected percentage of points per play.

By figuring in the number of plays run in addition to the points scored, we’ll get a better idea of actual offensive production regardless of the style of offense. By nature, the fast-paced offenses being played today are going to run more plays and have more opportunities to score points (e.g. Arizona St. ranks 9th in the nation running average of 84 plays per game) while the more power-oriented, ground-and-pound offenses will not run as many plays, but can still be just as effective (e.g. Stanford ranks 115th out of 125 in number of plays run per game with 65).

Considering plays per game also adjusts for blowout wins. Many times, in very lopsided games, the winning team will score most of its points in the first half, then run a significantly fewer number of plays in the second half as they run the ball more often attempting to keep from running up the score.

Without further ado:

Percentage of Expected Points Scored Per Play (SCORING OFFENSE)

TEAM % OF EXP PTS/PLAY OLD METHOD CHANGE IN RK
1 Arizona St 150% 162%
2 Oregon 148% 149%
3 Stanford 123% 108% +6
4 UCLA 113% 115% -1
5 Utah 111% 110% +2
6 Oregon St 110% 112% -2
7 USC 108% 95% +4
8 Washington 104% 112% -3
9 Arizona 102% 110% -1
10 Washington St 92% 112% -4
11 Cal 81% 97% -1
12 Colorado 79% 76%

Percentage of Expected Points Given Up Per Play (SCORING DEFENSE)

TEAM % OF EXP PTS/PLAY OLD METHOD CHANGE IN RK
1 Stanford 60% 58%
2 USC 66% 61%
3 Oregon 71% 76%
4 Washington 74% 76%
5 Utah 78% 78%
6 UCLA 79% 81%
7 Arizona 94% 94%
8 Washington St 100% 103% +2
9 Arizona St 102% 99%
10 Oregon St 107% 99% -2
11 Colorado 121% 121%
12 Cal 122% 122%

I’m assuming that the reason there wasn’t as much change in the defensive numbers is that teams are facing different styles of offense and varying play counts which, by this point in the season, begin to balance each other out.

Combined Difference

TEAM % OF EXP PTS/PLAY OLD METHOD CHANGE IN RK
1 Oregon 77% 73%
2 Stanford 63% 50% +1
3 Arizona St 47% 63% -1
4 USC 42% 34% +2
5 UCLA 35% 35%
6 Utah 33% 32% +1
7 Washington 30% 37% -3
8 Arizona 8% 16%
9 Oregon St 3% 12%
10 Washington St -8% -5% -2
11 Cal -41% -25%
12 Colorado -42% -45%