Compu-Picks 2012 Preview: WAC

Mr Pac Ten
Posted Aug 25, 2012


2012 Compu-Picks Previews Each 1-A League: WAC Preview

Below is the preview for the WAC, consisting of five tables. The first shows projections for each WAC team, with the others showing key statistics and/or details behind the projections.

Projected ranking and expected results

Expected Wins Projected League Results
Team 2012 Rank 2011 Rank All Games League Games SOS League Finish League Odds
Louisiana Tech 48 31 9.36 5.41 122 1 66.7%
Utah State 89 76 6.99 4.31 120 2 18.7%
San Jose State 110 86 4.80 3.15 114 3 7.8%
Idaho 113 109 4.09 2.87 113 4 2.9%
Texas St 118 0 3.59 2.17 121 5 2.0%
UTSA 120 0 3.58 1.91 124 6 1.4%
New Mexico State 123 106 2.09 1.19 115 7 0.6%

Some notes and comments about the WAC and its teams:

1) This looks like the least competitive league race in 1-A, even more so than the Mountain West, where Boise is widely expected to dominate. Louisiana Tech simply looks far better than everyone here, and should coast to an eight win season at the very worst, with 10+ wins a legitimate possibility. In fact, if they can somehow score a week one upset over Texas A&M, they'll have a serious chance to run the table the rest of the way, thanks largely to a schedule devoid of meaningful challenges.

2) Don't be surprised if Idaho is improved from last year's nightmare. They had a lot of bad luck, from injuries to fumbles to terrible fortune in close games, and while they lose a lot of talent (and they're really not recruiting well enough to replace it), a more normal luck season could put them at least close to a bowl berth.

3) New Mexico St is currently projected last in the WAC, even below the two 1-A newcomers, but it's tough to say whether that'll stick. Obviously they're not very good, and they lost a lot of production, but at this stage the newcomers' ratings are largely guesswork, so it wouldn't be at all surprising to see the Aggies jump a slot or two.

4) UTSA has the largest standard deviation in win projection, thanks to a schedule ranked dead last in 1-A. They're projected to be awful, but since they play a lot of awful opponents (including FOUR AA opponents), it wouldn't be at all surprising to see them win a few.

The next two tables show key statistics and details underlying the projections, from prior history and performance to luck-related statistics to key indicators of incoming and outgoing talent. Below is a brief explanation of some of these items:


Rank - Projected 2012 ranking, from 1 to 124
2011 Rank - 2011 ranking using the current compu-picks model, from 1 to 120 (does NOT include the four 1-A newcomers)
Prev 4 yr - ranking of the average rating from 2007-2010, from 1 to 120 (does NOT include the four 1-A newcomers)
Injuries - starts lost to injury during the 2011 season, from Phil Steele
Fumble Luck - the number of net turnovers in 2011 due to fumble luck
Recruit Rank - ranking of past 4 years of recruiting (each year equally weighted), from scout.com
Recruit Trend - the difference between the past 3 years of recruiting and the previous 4, ranked from best to worst
Starters - returning offensive / defensive / special teams (kicker and punter) starters, per Phil Steele magazine (* if the QB returns), with some edits due to subsequent news
Returning Yards, Tackles, Int, Sacks, Lettermen - returning production and roster depth; lettermen taken from philsteele.com, with the other stats calculated from cfbstats.com.
Draft Losses - based on the 2012 draft

Key Statistics - Performance, Luck and Coaching

Team 2012 Rank 2011 Rank Prev 4 yr Injuries Turnovers Fumble Luck New Coach
Louisiana Tech 48 31 82 14 11 0.5 .
Utah State 89 76 99 16 -9 -3 .
San Jose State 110 86 112 19 1 4.5 .
Idaho 113 109 104 33 -7 -3 .
Texas St 118 0 0 0 0 0 .
UTSA 120 0 0 0 0 0 .
New Mexico State 123 106 118 32 -3 4 .

Talent Inflows and Outflows

Team Recruit Rank Recruit Trend Starters Ret. Yards Ret. Tackles Ret. Int Ret. Sacks Ret. Lettermen Draft Losses
Louisiana Tech 90 94 8*/5/2 65% 52% 67% 36% 77% 0
Utah State 117 89 6*/6/2 62% 48% 25% 22% 65% 14
San Jose State 91 43 6/5/1 44% 56% 46% 75% 62% 0
Idaho 112 93 5/5/2 32% 55% 33% 47% 68% 3
Texas St 0 0 5* /8/1 0% 0% 0% 0% 0% 0
UTSA 0 0 11* /10/2 0% 0% 0% 0% 0% 0
New Mexico State 120 63 4/3/2 27% 34% 0% 28% 64% 2

The next two tables show probability distributions for the projections, based on 5,001 season simulation runs. Please note that a . indicates zero odds, while 0% indicates a non-zero probability that just rounds to 0%. The first table breaks down results across all games, while the second breaks down results across league games only.

Projected Results - All Games

Odds of Winning _ Games
Team E(wins) Stdev (wins) 13 12 11 10 9 8 7 6 5 4 3 2 1 0
Louisiana Tech 9.36 1.94 . 12% 20% 22% 17% 13% 8% 4% 2% 1% 1% 0% 0% 0%
Utah State 6.99 1.90 . 1% 2% 5% 12% 22% 23% 16% 8% 5% 3% 1% 1% 0%
San Jose State 4.80 2.19 . 0% 0% 1% 3% 6% 11% 15% 19% 16% 12% 8% 5% 2%
Idaho 4.09 2.03 . 0% 0% 0% 1% 3% 7% 12% 17% 20% 17% 13% 7% 3%
Texas St 3.59 2.36 . 0% 0% 1% 2% 3% 6% 10% 11% 14% 16% 16% 14% 8%
UTSA 3.58 3.17 . 0% 1% 3% 6% 8% 7% 3% 2% 5% 12% 18% 20% 13%
New Mexico State 2.09 1.80 . 0% 0% 0% 0% 1% 2% 3% 5% 8% 14% 22% 27% 18%

Projected Results - League Games

Odds of Winning _ League Games
Team E(wins) Stdev (wins) 9 8 7 6 5 4 3 2 1 0
Louisiana Tech 5.41 0.87 . . . 59% 28% 9% 3% 1% 0% 0%
Utah State 4.31 1.18 . . . 14% 35% 29% 14% 5% 2% 0%
San Jose State 3.15 1.47 . . . 5% 14% 23% 25% 19% 10% 4%
Idaho 2.87 1.29 . . . 1% 8% 24% 29% 24% 11% 4%
Texas St 2.17 1.38 . . . 1% 4% 12% 22% 26% 23% 11%
UTSA 1.91 1.38 . . . 1% 3% 9% 19% 25% 26% 17%
New Mexico State 1.19 1.19 . . . 0% 1% 4% 9% 18% 34% 34%

There are a few important notes and caveats I need to make about this model:

1) Compu-Picks does not endorse implicitly or explicitly any form of illegal gambling. Compu-Picks is intended to be used for entertainment purposes only.

2) No guarantee or warranty is offered or implied by Compu-Picks for any information provided and/or predictions made.

3) This preseason model is primarily based on the main compu-picks model. Essentially, it attempts to predict how well a team will rate given its rating history, as well as a number of other data points, such as returning starters, draft talent lost, turnovers, recruiting, etc. This means, among other things, that the rankings are power rankings based on how good a team projects to be, as opposed to a more cynical (though accurate) model that attempts to project how the BCS will rank a team by making adjustments to favor those with easy schedules and punish those with tough schedules.

4) I have provided adjusted division (or league) odds in a couple of instances. For the Big Ten Leaders, it shows the odds of each team winning adjusting for the fact that Ohio St and Penn St will both be ineligible. The same is true for the ACC Coastal and North Carolina.

5) There is a substantial amount of noise in these projections, which is to be expected given the large number of unknowns (who will have good and bad luck with injuries, which young players will improve and which won't, how specific matchups will come into play, etc.). Right now the standard error is a bit over 0.2 on a scale of about -1 to +1. It's important to look at the projections with this in mind to get a sense of how material the projected differences are. Given a standard error around 0.2, it is safe to project Alabama to be a much better team than Mississippi St, but it is not safe to project Mississippi St to be any better than Arkansas, much less a lot better.

6) At this point, there are a number of model features that need to be investigated further. Chief among these is the distribution of extreme events. It appears that the model may be overstating the probabilities of extreme events, such as 12-0 or 0-12 records, or major underdogs winning their division/league. This overstatement has been reduced compared to last year's projections, but still likely exists to some degree. Please keep this in mind when looking at the distribution of win probabilities.

7) Since there is much less data available for the four 1-A newcomers, the power rating methodology has been more manual and arbitrary. As a consequence, I am somewhat less confident of the projections for those four teams than I am for the other 120 1-A members. Please keep this in mind when looking at the newcomers' projections.

2012 Compu-Picks Blog

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