Official BCS Thread - 11/15/09 | by lsumatt on Nov 15, 2009 at 8:55 pm |  | |
BCS Standings
LSU needs help, but still has a legit chance at a BCS bowl if they win out. They would likely be a shoe-in, if it weren’t for the “max 2 teams per conference” rule, but that is the rule. If Bama slips up against Auburn and then again to Florida, LSU would likely get the BCS invite despite Bama’s head-to-head victory. The Sugar (or any bowl) wouldn’t want a Bama team that just lost 2 games (and went to the Sugar the previous year). Florida would be in a similar position if they lose two…but Florida might be more likely than Bama to get the nod over LSU. Otherwise a 10-2 LSU team goes to the Cap one Bowl and at 9-3 likely the Cap One or Cotton.
The National Championship picture is clear for now: Texas vs. SEC Champ, but could get fuzzy if Texas chokes to A&M or the Big12 CG. TCU is currently in 3rd, but I am fairly confident Cincy passes them with a win over Pitt. It is already close and it is the one big win Cincy is missing. Cincinnati played in a very respectable Big East this year with a decent OOC schedule.
Georgia Tech is sitting at #7, unnoticed. But they are a serious darkhorse imo. Ga Tech plays 3 SEC teams OOC, with Georgia left as well as the ACC CG. If Texas and Cincy BOTH lose, Ga Tech could make it interesting. They would almost definitely pass Boise, and while TCU probably edges them out, it might be close. My pecking order:
1. Undefeated SEC
2. Undefeated Texas
3. Undefeated Cincinnati
4. Undefeated TCU
5. 1-loss Ga Tech
6. 1-loss SEC (It is really tough to tell what would happen if Bama lost to Auburn and then beat Florida; I think their computer score keeps them low but they could be much higher than I am giving them credit for)
7. Undefeated Boise
Thoughts? I may move this to the MSB in the coming weeks.
Category: LSU Sports
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The Official BCS Thread for October 18th: LSU ranked No. 9 | by lsumatt on Oct 18, 2009 at 12:43 pm | | |
HARRIS POLL - LSU #9
Coaches- LSU #10
BCS standings - LSU #9
Let’s try and keep all the BCS discussion in one thread if we can. Bets on the first person to claim it is too early to talk about this? Or the person who insists on making football not fun by saying LSU will lose 3 more games?
Virginia Tech’s loss was a good one as their tough OOC schedule could have caused problems for LSU. Likewise for Ohio State. Now LSU just needs either Iowa or Texas to lose and they likely control their own destiny. Here is a first guess at the BCS standings. I haven’t done any calculations or anything (Harris poll and computers not really out yet), just a best guess.
1. Florida. Win out and they are in obviously. I am not quite as high as most if Florida drops a game. Their schedule is relatively weak avoiding Ole Miss, Bama, and Auburn in the regular season. Their OOC schedule is terrible, with a mediocre FSU the only thing of note. Moreover, any loss is now is a bad loss (and a late loss). I think USC could definitely finish higher in the computers and I would bet 50/50 if it came down to those two.
2. Bama. Win out and they are in. Playing in the SECW and beating Va Tech OOC makes them more appealing than Florida (at least to the computers). I don’t think they can lose to LSU (and be left out of the SECCG) or lose the SECCG. But any other loss, and they probably get in over USC.
3. Texas. Win out and they are in. But Texas’ weak schedule doesn’t bode well at all if they lose a game. I would think most 1-loss BCS teams as well as undefeated Cincy might be in better shape.
4. Boise State. They may have hit a ceiling here. Their schedule will just get worse and their computer score potentially abysmal. They need Oregon to win out to have any shot. If Oregon becomes a National Title contender themselves, it could get interesting. The Human polls would likely have Boise higher, but Oregon would be higher in the computers. How is that for controversy if 1-loss Oregon plays over undefeated Boise for a NC?
5. Cincy. Well this will get interesting if they go undefeated and it comes down to them and a 1-loss BCS team. Cincy actually plays in the third best conference statistically and has a respectable OOC schedule. But their computer score is going to hurt them still and they dont play anyone close to a top-10 caliber opponent. 1-loss SEC and Pac10 teams get in over Cincy, but I am not sure about Texas or Big 10 schools.
6. Iowa. Win out and have Texas or both Bama and UF lose and they are in. Any loss would require a minor miracle to get them in I think. Iowa’s computer score is very good despite any top-level opponents. Not sure if they can keep it up.
7. USC. They play in the 2nd toughest conference, have 2 nice OOC road wins, lost early without their starting QB, and they have been the team perennially left out of the BCSCG. At 1-loss they are in good shape against any 1-loss team except the SEC teams. I think they even stand a good chance (50/50?) against 1-loss Florida and a decent chance against 1-loss Bama. The bad news is they lost to a Washington team that may finish with a losing record. That could weight them down like an anchor in the computers.
8. TCU. They are in a similar boat as Boise State, They play a harder overall schedule but don’t have a team like Oregon either. If they went undefeated, not sure they would jump any 1-loss teams.
9. LSU. With all of LSU’s problems, they still almost control their own destiny. Things don’t look quite as good as they did a few weeks ago for SEC teams, but LSU still plays all the big boys in the SEC (and maybe Florida twice). Their OOC schedule isn’t anything to write home about, but Washington aint bad and La Tech and ULL are better rent-a-wins than expected. I think LSU will be fine against any 1-loss team. USC would be an interesting argument, but I would think LSU finishes with a slightly better computer score. Also, if it came down to the two, Washington tanking down the stretch would probably be a good thing for LSU.
10. Miami. They play in a weak ACC, but play a good OOC schedule so they may do well in the computers. They still don’t control their destiny for the ACCCG (which would be a must). They probably get in over 1-loss Big10 teams and maybe Texas, not sure about USC though.
11. Oregon. I said before the season that they had a BCS friendly schedule and at 1-loss could be in very good shape. I like them over any 1-loss BCS school except maybe the SEC schools. Again, they probably finish above undefeated Boise in the computers, so that would be an interesting argument.
12. Ga Tech. Similar boat with Miami. Nice OOC schedule gives them hope, but they need to make the ACCCG.
13. Penn State. I think they would need a minor miracle with their relatively weak schedule. But I think we could see a repeat of 2007, with even 2-loss teams being in the race.
**I will update this as more polls and computers are released, but this is probably close. Also, I will verify some of the commentary by running some future computer poll simulations.
Category: LSU Sports
Tags: LSU Football
THE OFFICIAL BCS THREAD - 10/06 | by lsumatt on Oct 6, 2009 at 11:28 pm | | |
This Week
As gigantic as this game is against Florida, you almost get the feeling that this game is only an exhibition in terms of the BCS. The loser still controls its own destiny in the SEC and chances are that the loser gets in the BCS NC if they win out. There are certainly a few undefeated BCS teams out there (e.g. Texas, Iowa, Wisconsin) that could run the table. It is not entirely clear yet how undefeated Cinci or even Boise would stack up and even 1-loss Va Tech and USC would have an argument. But in the end the SEC is sitting awfully pretty yet again and if out Tigers don’t pull it out this week, we should like our chances if they can win out.
BCS Overview
Chicken has requested a blog to we keep all the BCS discussion in, so I will try to make a weekly post to get the discussion started. As long as the Tigers have a shot at a BCS bowl, I will keep it on the rant. In the unlikely scenario LSU isn’t a top 10 team this year, I may move to the MSB. This year the BCS is released Oct 18 I believe, but that doesn’t mean we can’t start talking about it now. Last week I posted a description of how computer polls work and some specific info regarding the six used by the BCS. This week, I included an overview of how the BCS works in general and where some teams/conferences stand.
Just a refresher, the BCS is 1/3 Coaches Poll, 1/3 Harris Poll, and 1/3 average of the 6 computers (with the high and low thrown out). The calculation is actually based on votes in the polls. Consider an example: last year Florida had 2776 Harris votes out of a possible 2825 (113 voters x 25 positions) which is 0.983. Likewise they had 1481 points out of a possible 1525 in the Coaches, which is 0.971. Finally, their computer average (after dropping the high and low) was 2.75 and (25-2.75)/2.75 is 0.890. So Florida’s average is (0.983+0.971+0.890)/3=0.948; right above Texas and right behind OU.
Misconceptions about the BCS
1. You must win your conference to play for the NCS NC. Of course OU played for it in 2003, but no, they did not change the rules after to exclude a team that loses its conference. However, the human voters have so much power now (and voters try to avoid non-champs in the title game), it would be hard for them to make it unless they really were head and shoulders above everyone else.
2. There is a direct strength of schedule (SOS) component included in the BCS formula. Before 2004 a simple SOS calculation, along with a Quality Win component was included. Both were nixed in the formula we have used for the last 5 years. SOS is used indirectly in the computers to sort teams of like record…and supposedly in the human polls as well.
3. The SOS formulas used by the computers are over-simplified. Some people think that rankings from the human polls are used. Others think that it is just your opponents winning percentage. Many others believe the old BCS formula is used and beating a 10-0 team and 0-10 team is the same as beating two 5-5 teams. This simply isn’t true. Each computer uses its own measure of SOS, which is a function of its own rating, and most measures of SOS are complicated; weighting the top of your schedule much more heavily.
4. Since the BCS is 2/3 human polls, if you are ahead in both, the computers don’t matter. Not true at all. For one, its votes not ranking. So team A can be ranked 2nd but only be a few votes ahead of Team B. Also, if there are teams “wedged” between teams B and A in the computers…team B can easily be ahead in the BCS.
Where some teams/conferences stand
SEC teams (LSU, Florida, Bama, AU, Miss). The SEC is an amazing 25-3 in OOC games and once again has seemingly distanced itself from other conferences, and should be rewarded heavily in the computers as a result of the tougher schedule (note: the SEC still has 20 OOC games to play though). No undefeated SEC team could realistically get left out this year (ala 2004). A 1-loss SEC team is in very good position for a NC; especially a team like LSU or Bama who play in the super tough SEC West and play good or decent OOC schedules. And if the 1-loss team redeems itself by beating that team in the SECCG, it could be a done deal.
PAC 10 teams (USC, Oregon). The Pac10 is strong this year as (unlike last year) they have mostly taken care of business in OOC games. The Pac10 is the 2nd strongest conference. Last year, I was quick to write off USC after the OSU loss. But with the Pac10 looking strong, I think both USC and Oregon will do well in the computers. A 1-loss SEC team probably still has the edge on them on the computers, but since they lost earlier, they could have the edge in the polls.
BIG 12 (Texas). The Big12 has done a 180 from last year and their OOC performance has been mediocre…at best. Couple that with Texas’ extra weak OOC schedule, and Texas won’t do well in the computers. However, voters will likely give them the benefit of the doubt as long as they stay undefeated, but a 1-loss Texas probably doesn’t fair well against most other 1-loss BCS schools.
BIG 10 (PSU, OSU, Wisc?). The Big10 is better than most give credit for, but it isn’t good enough to make up for PSU’s weak OOC schedule if they finish with 1-loss. Ohio State lost early and it was to USC, but they play no CG and it would be tough to put them above any SEC, Pac10, or Va Tech/Miami. A 1-loss Big10 school would need lots of help for sure.
ACC (Va Tech, Miami). The ACC has been pretty abysmal on the whole and it won’t help Va Tech or Miami’s SOS at all. But both teams played very tough OOC schedules and lost early. If it came down to them, USC and a 1-loss LSU it would be interesting.
Big East (Cincinnati). A very interesting case. The Big East is arguably the 3rd best conference right now and have a solid OOC record to show for it. Moreover Cinci plays two BCS schools (Oregon State and Illinois) and a decent Fresno team OOC. I think if Cinci runs the table, they will be okay (but not great) in the computers. But may not have a single ranked team on their schedule (except maybe USF) and I have a feeling they get treated like a mid-major by the voters. It is too tough to say right now how they will shape up against the 1-loss powerhouses.
Boise, and TCU. After weeks 1 and 2 it looked to be the year of the mid-major. But the MWC missed golden opportunities with Utah and BYU losing. That leaves TCU with nothing real strong on their schedule. Boise had Oregon and nobody left. But if Oregon runs the table, they become a NC contender themselves. An undefeated Boise is easily over Oregon.
**When I find time, we can run “future” simulations to figure out where these teams really may shake out in the computers at the end of the season.
Thoughts?
Category: LSU Sports
lsumatt computer poll released | by lsumatt on Sep 29, 2009 at 8:56 am | | |
Here is the first version of my computer poll. It probably looks like a lot like Tuba's and xiv's poll (and the BCS computer polls). If some things look funny, read the BLOG on computer polls about them. We plan to merge a few TD.com polls with the TD top 10 to get a TD mock BCS.
THE TOP 10
1 Iowa 0.993
2 Alabama 0.975
3 Boise St 0.952
4 Michigan 0.939
5 LSU 0.923
6 Virginia Tech 0.918
7 Houston 0.909
8 Auburn 0.874
9 Florida 0.872
10 Cincinnati 0.866
THE BASICS
The basic principle is that when two teams play, there is always a chance either team will win The computer poll determines each teams ranking in such a way that the number of games thy actually won is equal to the number of games they were expected to win based on their rating and the rating of the teams they played. Each team is rated on a scale from 1.0 (very good) to 0.0 (very bad). If two teams play each other that have the same ranking, there is a 50% probability each team will win. If the best team (r =1.0) plays the worst team (r=0.0), then there is a 99.9% chance that the better team will win. Moreover, when a really good team plays a bad team, it makes little difference if they are the 120th best team or the 90th best team. This is taken into account, as the probability a team with r=0.1 beats r=1.0 isn’t much better than a team with r=0.
THE UGLY MATH
The plot below shows the probability of a victory versus the difference in rating of team “i” and team “j”
The above curve can be described by a “sigmoid” equation:
 (1)
Where ri and rj are the ratings of the two teams. Now the trick is to determine how many games a team was supposed to win. Suppose a team (LSU) had a rating r=0.9 and they played 3 games; Florida with r=0.95 (43% chance of winning), Auburn with r= 0.8 (64% chance of winning), and Miss State with r=0.45 (93% chance of winning), then they would be expected to have 2 wins (0.43+0.64+0.93=2) and be 2-1 overall. So in summary, the number of expected wins for team “i” is just the sum of all the game probabilities, which will always be less than the number of games they have played (N).
 (2)
One catch is that no team is ever expected to be undefeated, because there is never a 100% chance of wining any one game. So even if you are a “perfect” team and played 10 games against awful teams, you would be expected to have 9.9 wins, not 10. To avoid this problem, I assume every team starts out 1-1; beating an imaginary terrible team (r=0) and losing to an imaginary “perfect” team (r=1.0).
In the above example with LSU we knew the teams rating and calculated their expected wins. But we actually know their wins and want to know their rating. So we can write Equation 2 for every team in college football (120) and substitute the number of games they actually won for “Wins”. If LSU were 2-1 (3-2 when you include that 1-1 start) in the above example, their equation would look like:
But we don’t know the rating of team i (LSU) or the ratings of the teams it played (UF, AU, or MSU). In fact there are 120 teams ratings we don’t know, but we do have 120 very complicated equations. Lucky for us, Isaac Newton and others have found ways of solving systems of nonlinear equations (see the movie “21” with Kevin Spacey?). Using them we can calculate the ratings of each team in college football and sort them from highest to lowest.
SOME DETAILS
A few things:
1. There is no home/away component yet. But that is easy, I think maybe I will just say that the home team is 10% more likely to win. So if there is a 50% chance of winning on a neutral field, its 55% at home.
2. I have debated how to handle 1AA schools. First, I ignored those games altogether but that wasn’t good (what if a 1A team lost?) Then I thought to just set the rating of all 1AA teams to 0. That wasn’t fair either as many 1AA teams are better than 1A teams. Finally I decided to rank all the 1AA teams independently (from 1.0 to 0.0) and then re-scale it by subtracting by 0.75. So the “best” 1AA team has a rating of 0.25 and the worst of -0.75.
3. The “6” used in the sigmoid equation is arbitrary; I chose it so that the probabilities match what I thought they should be for a #1 team playing a #10 team, etc. If I had time, I think it would be neat to get a bunch of historical data and choose a value that matches the curve.
4. It is possible for a team to be rated slightly higher than 1.0 or lower than 0.0. But that is no big deal.
Category: LSU Sports
In Defense of Computer Polls..... | by lsumatt on Sep 17, 2009 at 11:12 am | | |
HOW COMPUTER POLLS WORK
There is always chatter about the computer polls this early and how they look bizarre. Many use it as an opportunity to discount the validity of them (and the BCS altogether). But remember, this is a STRENGTH of the computer polls; the fact they don’t have predetermined bias for teams based on what conference they play, how many National Titles they won in the 50s or if they are supposed to be good this year. If North Texas and Florida win their first game and start 1-0, they should be ranked the same (or close to it), because the computers don’t assume Florida was supposed to be better, nor does it assume their wins were better (even if Florida beat USC and North Texas beat ULM). As the season progresses, SOS can be determined more accurately and that Florida win over USC can be given more weight. Ultimately its SOS (however that poll determines it) is used to distinguish teams of like records. Remember SOS isn’t determined by what the Coaches poll thinks are the good teams, it is determined by what has been accomplished on the field this year.
In short, I don’t really trust any computer poll that DOESN”T look bizarre the first few weeks of the season. The Billingsly poll actually does use a “preseason” ranking which is his final poll from the previous year. It is based on a little more common sense, but I still find it unfair, and 90% of the time it is excluded from the BCS as an outlier. Sagarin and Massey also use “preseason” polls which make their polls look sensible early on, but both claim to drop that data by week 5.Anybody interested in how computer polls work should visit colleyrankings.com, Dr. Colley gives an excellent description of his poll and how and why it isn’t biased. There is a lot of math, but even if you get lost, the introduction is excellent.
TD.COM COMPUTER POLLS AND MOCK BCS
Several of your fellow posters produce excellent computer polls. The Tuba 101 has been a staple of TD.com for years. Xiv produces one also; both polls give outlandish results the first few weeks – a mark of a great computer poll imo! I have created my own also, the basic principle being that if two teams play there is a probability each team will win. The binger the difference in ranking, the greater chance the better team will win. I then solve a bunch of simultaneous equations (120, one for each team) which equates the expected wins (based on probability) with the actual wins for a team. We hope to merge the td.com computer polls with the TD top 10 to create a mock BCS around week 5.
THE EFFECT OF 1AA AND OTHER “WEAK TEAMS”
Strength of schedule is an inherent part of computer polls. It is how it is deteremined which team with the same record should be rated higher (or if 2-loss LSU should be higher than undefeated Hawaii). One misconception is that playing a 1AA team or a weak team actually hurts you; that you would be better off not playing a game at all. The thought process is that it brings down the average SOS of your team. For the most part, this just isn’t true. Beating McNeese State won’t help LSU’s rating much at all (if any), but rarely, if ever, will it hurt you in the computers. After all, beating a 1AA team is still (slightly) tougher than beating OPEN DATE. A couple computer polls ignore 1AA games altogether and treat them as an open date.
A DESCRIPTION OF THE BCS POLLS
Most of the BCS polls use an “iterative” strategy: the guess all the teams ranking, determine SOS based on that, re-calculate the ranking, and repeat until there is no change (and no, it doesn’t matter what their initial guess is). They don’t use MOV and the final poll doesn’t use any preseason bias (except Billingsly). Here is my best description of the computer polls (only Billingsly and Colley explain their ratings)
COLLEY MATRIX (www.colleyrankings.com). My favorite poll, because it is mathematically sound and he describes it in detail (see his pdf online). He basically sets up 120 equations and solves them. His algorithm is spelled out so well, we can (and I do) re-create his poll. I also have a “future poll” in which I predict the final Colley matrix based on expected outcomes of future games.
BILLINGSLY (http://www.cfrc.com /). What I call the “common sense” poll. The math is simple and he uses a preseason poll (last year’s final poll). He explains in detail on his website. He also does something different in which strength of schedule is a hybrid of a team’s current ranking and their final ranking. So if you beat Ole Miss in week 2, but then end up 5-7 you get some credit for beating a top 10 team. He claims top10 “feel” of the game, is important. Regardless, his poll is almost always excluded as an outlier.
SAGARIN (http://www.kiva.net/~jsagarin/sports/cfsend.htm ). I hate this poll, mostly because he refuses to explain it at all. Also, I am suspicious of his preseason ranking (which he claims to drop). He has two polls: the predictor which uses MOV and elochess which doesn’t…it is elochess that is included in the BCS). Sagarin also includes a Home/Away component which I think is good. Also, empirical evidence suggests that a bad loss in Sagarin weighs you like an anchor. For example, losing to 4-8 Tenn is 2005 killed LSU.
ANDERSON AND HESTER (http://www.andersonsports.com/football/ACF_frnk.html ). Another iterative poll that gives sensible rankings by the end. He doesn’t release until midseason because they would look bizarre. He appears to give bonus points for wins over top 10 and top 25 teams (in his own poll, not the human polls).
MASSEY (http://www.mratings.com/rate.php?lg=cf ) Uses a preseason poll, but claims to drop it mid season when things get connected. It appears to be a traditional iterative poll.
WOLFE (http://www.bol.ucla.edu/~prwolfe/cfootball/home.htm ). Another iterative poll, that isn’t released till mid season. His website is an excellent place to get data of scores of all games of the season.
TUBA 101, XIV, and LSUMATT POLL. All being wooed by the BCS, but we are holding out for a better offer.
Category: LSU Sports
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