Below is the preview for the Mountain West, consisting of five tables. The first shows projections for each Mountain West 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 |
| Boise State | 32 | 7 | 9.40 | 7.15 | 89 | 1 | 57.6% |
| Air Force | 58 | 71 | 7.77 | 5.74 | 112 | 2 | 14.2% |
| Wyoming | 88 | 80 | 6.66 | 4.56 | 101 | 3 | 7.5% |
| San Diego State | 81 | 65 | 6.84 | 4.48 | 96 | 4 | 5.8% |
| Fresno State | 85 | 94 | 6.37 | 4.48 | 84 | 5 | 6.5% |
| Hawaii | 94 | 92 | 6.23 | 4.30 | 97 | 6 | 4.8% |
| Nevada | 105 | 54 | 5.15 | 3.34 | 106 | 7 | 2.2% |
| Colorado State | 109 | 111 | 4.87 | 2.88 | 119 | 8 | 1.0% |
| Nevada-Las Vegas | 117 | 114 | 2.89 | 1.87 | 99 | 9 | 0.2% |
| New Mexico | 121 | 118 | 2.57 | 1.20 | 104 | 10 | 0.2% |
Some notes and comments about the Mountain West and its teams:
1) Even with massive personnel losses, Boise remains the class of the league by a pretty solid margin. Now that TCU is gone, they don't really have any strong challengers, just a bunch of teams where on any given day you never know, and an Air Force team that is at least potentially capable of going on a 7-1 or 8-0 run through the league (since they avoid Boise) and making the race interesting.
2) Speaking of Air Force, they lose a lot of players even for them. That, combined with a clear down season in 2011, makes it odd to see them projected for improvement. Part of it is projected turnaround in luck, part of it is the simple fact that 2011 really did seem like an outlier (so reversion to more normal performance levels is by default fairly likely), and part of it is that they're actually improving their recruiting a bit, which is somewhat surprising for a military school. Of course, an atrocious schedule strength doesn't hurt at all. Michigan is a nasty game, but that gets more than balanced by a AA opponent, Army and Navy, and a MWC slate that doesn't include Boise (which seems really odd; if anything you'd think the league would want to see this potentially interesting matchup).
3) Nevada is projected worse than seems obvious. This is the combined impact of a few things: heavy lettermen losses (not starters so much as overall roster reduction); draft losses; fumble luck in 2011; and lower returning production than a simple list of starters would suggest. This is definitely a contrarian projection, so it'll be interesting to see how it plays out.
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 |
| Boise State | 32 | 7 | 4 | 37 | 8 | 0.5 | . |
| Air Force | 58 | 71 | 40 | 36 | 0 | -1.5 | . |
| Wyoming | 88 | 80 | 97 | 27 | 12 | -5 | . |
| San Diego State | 81 | 65 | 83 | 20 | 12 | -1.5 | . |
| Fresno State | 85 | 94 | 70 | 31 | -14 | -4 | 1 |
| Hawaii | 94 | 92 | 75 | 26 | -2 | -5.5 | 1 |
| Nevada | 105 | 54 | 43 | 19 | 0 | 3.5 | . |
| Colorado State | 109 | 111 | 94 | 52 | -4 | 2 | 1 |
| Nevada-Las Vegas | 117 | 114 | 101 | 18 | 3 | 5.5 | . |
| New Mexico | 121 | 118 | 111 | 31 | -8 | -2 | 1 |
Talent Inflows and Outflows
| Team | Recruit Rank | Recruit Trend | Starters | Ret. Yards | Ret. Tackles | Ret. Int | Ret. Sacks | Ret. Lettermen | Draft Losses |
| Boise State | 69 | 82 | 4/2/0 | 36% | 40% | 60% | 20% | 71% | 37 |
| Air Force | 93 | 41 | 3/3/1 | 29% | 35% | 22% | 47% | 68% | 0 |
| Wyoming | 106 | 77 | 5*/7/1 | 77% | 61% | 77% | 32% | 73% | 0 |
| San Diego State | 83 | 37 | 6/6/0 | 39% | 53% | 47% | 28% | 63% | 12 |
| Fresno State | 80 | 109 | 7*/7/1 | 78% | 63% | 80% | 59% | 66% | 4 |
| Hawaii | 81 | 98 | 6/4/2 | 49% | 45% | 43% | 53% | 69% | 1 |
| Nevada | 104 | 51 | 6*/6/1 | 39% | 52% | 60% | 27% | 57% | 10 |
| Colorado State | 99 | 68 | 7/8/1 | 57% | 61% | 63% | 35% | 63% | 0 |
| Nevada-Las Vegas | 89 | 88 | 7*/5/2 | 62% | 48% | 29% | 39% | 65% | 0 |
| New Mexico | 97 | 71 | 8*/6/1 | 52% | 48% | 33% | 40% | 66% | 0 |
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 |
| Boise State | 9.40 | 1.91 | . | 11% | 19% | 24% | 19% | 12% | 7% | 4% | 2% | 1% | 1% | 0% | 0% | 0% |
| Air Force | 7.77 | 2.17 | . | 1% | 7% | 14% | 18% | 18% | 15% | 11% | 7% | 4% | 2% | 1% | 0% | 0% |
| Wyoming | 6.66 | 2.36 | . | 0% | 4% | 7% | 12% | 16% | 17% | 15% | 11% | 8% | 5% | 3% | 1% | 1% |
| San Diego State | 6.84 | 2.33 | . | 1% | 4% | 8% | 13% | 15% | 18% | 15% | 11% | 8% | 4% | 2% | 1% | 1% |
| Fresno State | 6.37 | 2.27 | . | 0% | 1% | 5% | 11% | 15% | 18% | 16% | 12% | 9% | 5% | 3% | 2% | 1% |
| Hawaii | 6.23 | 1.93 | . | 0% | 1% | 3% | 7% | 13% | 20% | 22% | 17% | 9% | 4% | 2% | 1% | 0% |
| Nevada | 5.15 | 2.45 | . | 1% | 1% | 2% | 4% | 8% | 12% | 15% | 15% | 15% | 12% | 7% | 4% | 2% |
| Colorado State | 4.87 | 2.44 | . | 0% | 1% | 2% | 4% | 7% | 10% | 14% | 16% | 16% | 12% | 9% | 6% | 3% |
| Nevada-Las Vegas | 2.89 | 2.21 | . | 0% | 0% | 0% | 1% | 2% | 3% | 5% | 8% | 12% | 17% | 20% | 19% | 11% |
| New Mexico | 2.57 | 2.02 | . | 0% | 0% | 0% | 1% | 1% | 2% | 5% | 7% | 11% | 17% | 21% | 21% | 14% |
Projected Results - League Games
| | | | Odds of Winning _ League Games |
| Team | E(wins) | Stdev (wins) | 9 | 8 | 7 | 6 | 5 | 4 | 3 | 2 | 1 | 0 |
| Boise State | 7.15 | 1.14 | . | 50% | 29% | 12% | 5% | 2% | 1% | 0% | 0% | 0% |
| Air Force | 5.74 | 1.63 | . | 14% | 23% | 24% | 18% | 12% | 5% | 3% | 1% | 0% |
| Wyoming | 4.56 | 1.83 | . | 5% | 10% | 18% | 21% | 19% | 14% | 8% | 4% | 2% |
| San Diego State | 4.48 | 1.75 | . | 3% | 11% | 16% | 21% | 21% | 15% | 9% | 4% | 1% |
| Fresno State | 4.48 | 1.87 | . | 3% | 11% | 18% | 20% | 18% | 14% | 9% | 5% | 2% |
| Hawaii | 4.30 | 1.64 | . | 3% | 7% | 14% | 21% | 24% | 18% | 9% | 3% | 1% |
| Nevada | 3.34 | 1.80 | . | 1% | 3% | 8% | 14% | 19% | 20% | 19% | 11% | 5% |
| Colorado State | 2.88 | 1.57 | . | 0% | 1% | 4% | 8% | 17% | 25% | 25% | 14% | 5% |
| Nevada-Las Vegas | 1.87 | 1.47 | . | 0% | 1% | 2% | 4% | 8% | 15% | 24% | 30% | 17% |
| New Mexico | 1.20 | 1.31 | . | 0% | 0% | 1% | 1% | 4% | 8% | 18% | 30% | 37% |
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
Questions, comments or suggestions? Email me at cfn_ms@hotmail.com
