Week 2 BTBS Picks
UPDATE: a 22-24 week here, but at least the Safe/Queasy picks turned out better.
Week One is in the books, and the BTBS picks did ... fine. We went 24-13-2 (64%) overall, faring better than we did in Week One of 2009 (23-17, 58%), so there's something to be said for that. Plus, in terms of straight-up results, we got 34 of 39 correct (87%). But the way we did well was a bit confusing.
| Week 1 |
Season | |||
| Type/Range |
W-L |
Win% |
W-L |
Win% |
| ALL GAMES |
24-13-2 |
.641 |
24-13-2 |
.641 |
| Big 12 Games |
4-5 |
.444 |
4-5 |
.444 |
| Upset Picks |
2-3-1 |
.417 |
2-3-1 |
.417 |
| "LOCKS" |
2-3 |
.400 |
2-3 |
.400 |
| "Feeling Safe" |
2-3 |
.400 |
2-3 |
.400 |
| "Feeling Queasy" |
3-1-1 |
.700 |
3-1-1 |
.700 |
| 0-5 point spread |
5-4-1 |
.550 |
5-4-1 |
.550 |
| 5-10 points |
5-0 |
1.000 |
5-0 |
1.000 |
| 10-20 points |
6-3-1 |
.650 |
6-3-1 |
.650 |
| 20-30 points |
5-2 |
.714 |
5-2 |
.714 |
| 30+ points |
3-4 |
.429 |
3-4 |
.429 |
Let's face it: I'd have been willing to bet $1,000,000 that the "Picks I Feel Queasy About" would outperform the "Picks I Feel Safe About." That was just about a given. And I continue to find it odd that the "LOCKS" (the picks where there is the biggest difference between my projection and the spread) have, going back to last season, fared worse than the picks as a whole.
The picks were pretty much spot-on for the spreads that were not on either extreme. For the really tight spreads (0-5 points) and the really huge lines (30+ points), we went just 8-8-1. For the spreads between 5 and 30, we made a killing, winning at a 74% clip (15-5-1). It makes some sense that that would be the case, obviously -- the tight spreads have almost no margin for error, and the huge spreads can be impacted significantly by what happens in garbage time. It's something to keep an eye on as we move to the Week 2 picks after the jump.
Some notes:
- "LOCKS" signify games where the spread and projection are more than 17 points apart. Remember: locks don't seem to do particularly well for whatever reason, so don't take these picks as gospel. I had to point them out somehow, so I chose "LOCKS".
- If there is a "(!)" next to the spread, that means the projection and spread are within 2 points of each other ... and you should probably lay off of these picks if you are the betting type. There is already a marked increase in these games compared to how many there were last week. That's a bad sign for my overall win% down the line.
- Verdicts in all caps signify games where the underdog is picked to win straight up.
- Now's a good time to remind you that one week into the season, teams' ratings haven't changed much. They're still made up primarily by the preseason projections. That's why you see teams like Ole Miss and Kansas still faring quite well. I am quite confident in this approach -- too often we severely overreact to a one-game sample. Kansas and Ole Miss might very well be the worst teams in their respective conferences, but we can't conclude that beyond a shadow of a doubt after one week.
| Date | Time | Game | Projection | Spread | ATS Verdict |
| Thurs., 9/9 |
6:00pm |
Central Michigan at Temple (ESPNU) |
CMU by 6.2 |
CMU +7.5 |
CEN. MICH. (W) |
| 6:30pm |
Auburn at Mississippi State (ESPN) |
Auburn by 8.5 |
Auburn -2.5 |
Auburn (W) |
|
| Fri., 9/10 |
6:00pm |
West Virginia at Marshall (ESPN) |
WVU by 26.6 |
WVU -13.5 |
West Va. (L) |
| 9:15pm |
UTEP at Houston (ESPN) |
Houston by 19.3 |
Houston -20 (!) | Utep (L) |
|
| Sat., 9/11 |
11:00am |
Memphis at East Carolina |
ECU by 21.9 |
ECU -13.5 |
East Caro. (W) |
| Duke at Wake Forest (ESPN3) |
Wake by 15.5 |
Wake -5 |
Wake Forest (W) |
||
| San Jose State at Wisconsin (ESPN) |
Wiscy by 45.5 |
Wiscy -38 |
Wisconsin (L) |
||
| Hawaii at Army |
Hawaii by 1.5 |
Hawaii +3 |
HAWAII (W) |
||
| Florida Atlantic at Michigan State (ESPNU) |
Mich. St. by 36.6 |
Mich. St. -28.5 |
Michigan St. (L) |
||
| Georgia Tech at Kansas (FSN) |
GT by 13.6 |
GT -14 (!) | Kansas (W) |
||
| Georgia at South Carolina (ESPN2) |
UGa by 2.4 |
UGa +3 |
GEORGIA (L) |
||
| 11:21am |
South Florida at Florida (ESPN3) |
Florida by 35 |
Florida -16 |
UF (LOCK) (W) |
|
| 11:30am |
Idaho at Nebraska |
NU by 44.6 |
NU -28 |
Nebraska (L) |
|
| 1:00pm |
Eastern Michigan at Miami (OH) (ESPN3) |
Miami by 16.7 |
Miami -16 (!) | Miami (L) |
|
| 2:30pm |
Colorado at California (FSN) |
Cal by 12.4 |
Cal -9 |
California (W) |
|
| Michigan at Notre Dame (NBC) |
Irish by 5.8 |
Irish -4 (!) | Notre Dame (L) |
||
| Kent State at Boston College (ESPNU) |
BC by 34.3 |
BC -17.5 |
Boston Coll. (L) |
||
| Florida State at Oklahoma (ABC) |
OU by 10.9 |
OU -7.5 |
Oklahoma (W) |
||
| Arkansas State at UL-Lafayette (ESPN3) |
ULL by 1.6 |
ULL -1 (!) | ULL (W) |
||
| Iowa State at Iowa (ABC) |
Iowa by 30.4 |
Iowa -14 |
Iowa (W) |
||
| 2:40pm |
Miami at Ohio State (ESPN) |
Ohio St. by 12.3 |
Ohio St. -8.5 |
Ohio State (W) |
|
| 3:00pm |
UNLV at Utah |
Utah by 31.6 |
Utah -22 |
Utah (W) |
|
| BYU at Air Force (Versus) |
BYU by 10.6 |
BYU +1 |
BYU (L) |
||
| 6:00pm |
Toledo at Ohio |
Ohio by 12.1 |
Ohio -8 |
Ohio (L) |
|
| Troy at Oklahoma State |
OSU by 22.7 |
OSU -14 |
OSU (L) |
||
| Bowling Green at Tulsa |
Tulsa by 10.1 |
Tulsa -17 |
B. Green (W) |
||
| LSU at Vanderbilt (ESPNU) |
LSU by 24.3 |
LSU -10 |
La. St. (W) |
||
| Buffalo at Baylor |
Baylor by 10.6 |
Baylor -17 |
Buffalo (L) |
||
| Louisiana Tech at Texas A&M |
A&M by 21.9 |
A&M -19.5 |
A&M (W) |
||
| Rice at North Texas |
UNT by 2.49 |
UNT -2.5 (!) |
Rice (W) |
||
| Wyoming at Texas |
Texas by 51.1 |
Texas -29 |
Tex. (LOCK) (L) |
||
| Syracuse at Washington |
Wash. by 7.6 |
Wash. -13.5 |
Syracuse (L) |
||
| Penn State at Alabama (ESPN) |
'Bama by 13.8 |
'Bama -12 (!) | Alabama (W) |
||
| Arkansas vs UL-Monroe (ESPN3) |
Arky by 42.3 |
Arky -34 |
Arkansas (L) |
||
| Oregon at Tennessee (ESPN2) |
Oregon by 8.9 |
Oregon -12 |
Tennessee (L) |
||
| 6:30pm |
Western Kentucky at Kentucky (ESPN3) |
UK by 31.4 |
UK -24.5 |
Kentucky (W) |
|
| N.C. State at Central Florida |
NC St. by 4.8 |
NC St +3.5 |
NC STATE (W) |
||
| 7:00pm |
San Diego St. at New Mexico St. (ESPN3) |
SDSU by 5.9 |
SDSU -13 |
New Mex. St. (L) |
|
| Texas Tech at New Mexico |
Tech by 33.7 |
Tech -24.5 |
Texas Tech (W) |
||
| Rutgers at Florida Int'l (ESPN3) |
Rutgers by 26.1 |
Rutgers -19 |
Rutgers (L) |
||
| UAB at SMU |
SMU by 8 |
SMU -12 |
Uab (L) |
||
| 8:00pm |
Ole Miss at Tulane (ESPNC / ESPN3) |
Ole Miss by 35.5 |
Ole Miss -20.5 |
Ole Miss (L) |
|
| 9:30pm |
Stanford at UCLA (ESPN) |
Stanford by 4.4 |
Stanford -6 |
Ucla (L) |
|
| Virginia at USC |
USC by 18.7 |
USC -19.5 (!) | Virginia (W) |
||
| Colorado State at Nevada (ESPNU) |
Nevada by 13.9 |
Nevada -23.5 |
Colorado St. (L) |
Picks I am Feeling Safest About:
- LSU-Vanderbilt. You won't make a lot of money in life betting on Les Miles teams, but for one reason or another I feel pretty good about this one. LSU was dominant in the first half against North Carolina, and I think their problem in the second half was simply one of focus. They should stay focused enough in Nashville to win by 10 or more. (VERDICT: W)
- Colorado-California. Colorado's biggest problem in my eyes (speed) is California's biggest strength. I think the CU defense might have some saltiness to it this year, but I can't get the visions of last year's Colorado-Toledo game out of my head. Speed kills. (VERDICT: W)
- ISU-Iowa. Fourteen points is showing a lot of respect to Iowa State, considering both teams are at least comparable to where they were last year, and Iowa won by 32 in Ames. (VERDICT: W)
- WKU-Kentucky. Western Kentucky is terrible. That's the only rationale I have. (VERDICT: W)
- Troy-OSU. If Kendall Hunter really is doing his best Barry Sanders impression right now, then Vegas is, like last week, significantly underrating the Cowboys. I say hop on the bandwagon until Vegas figures it out. Or, you know, until Troy upsets them this week. (VERDICT: L)
Picks I am Feeling Queasiest About:
- CSU-Nevada. Picking Nevada to win by only two touchdowns over a seemingly lifeless Colorado State squad doesn't seem quite right to me. I think Nevada runs away with this one. (VERDICT: L)
- SJSU-Wisconsin. SJSU obviously isn't good, but 38 points is a lot to give for a grind-it-out team like Wisconsin. They could completely dominate but only win by 35. (This is similar to what I said about Nebraska last week, and they barely covered.) (VERDICT: L)
- Baylor-Buffalo. When you think about it, Buffalo's projection is based on them being a Turner Gill team, and a large portion of Baylor's projection is based on Robert Griffin having been injured last year. I don't think this one stays anywhere near 10.6 points. 17 is a lot for Baylor to give to anybody, but I like them in this one. (VERDICT: L)
- GT-Kansas. For very, very, very, very obvious reasons. (VERDICT: W)
- UTEP-Houston. Once Houston gets rolling, the score could get ridiculous. They're just as likely to win by 30 instead of 19.3. (VERDICT: L ... and yes, they won by 30)
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whoops...fixed.
Have you bought your 2010 Missouri Football Preview yet??
Rock M Nation
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UTEP-Houston. Once Houston gets rolling, the score could get ridiculous. They're just as likely to win by 30 instead of 19.3.
Of course UTEP ran all over Houston last year in a victory.
That's the flipside, yes.
The point was that a 19-point victory isn’t that likely…it’s 30-points, it’s tied, or it’s a 30-point loss.
Have you bought your 2010 Missouri Football Preview yet??
Rock M Nation
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How does btbs factor a lost QB?
I notice Texas, Florida and Central Michigan seem to be rating similar to last year. All lost QBs and in the case of CMU a bigger dropoff should be expected. How much of this is factored in? Is Vegas underrating these teams because of the new QB or is BTBS not reacting enough to a new QB (or in the case of CMU, replacing a historic QB)?
The projections absolutely factor that in.
The biggest factors are “institutional” ones (i.e. recent history/power) because they are by far the most closely correlated to year-to-year success. The change factors, like which starters are returning, or what your turnover margin was last year, are secondary. They often don’t have nearly the impact we think they will, especially with teams like Texas and Florida, who have ridiculous talent/athleticism everywhere else. The top tier stays very much the same from year to year. Maybe one team falls back briefly, but they rarely fall back for long.
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Thanks for the response
That’s similar to what I expected, but I wasn’t sure. I keep going back and forth on this CMU Temple line. Temple being more than a TD favorite after struggling with Villanova confuses me, but then again I don’t know what to make of CMU post-Lefevour.
The projections absolutely factor that in.
The biggest factors are “institutional” ones (i.e. recent history/power) because they are by far the most closely correlated to year-to-year success. The change factors, like which starters are returning, or what your turnover margin was last year, are secondary. They often don’t have nearly the impact we think they will, especially with teams like Texas and Florida, who have ridiculous talent/athleticism everywhere else. The top tier stays very much the same from year to year. Maybe one team falls back briefly, but they rarely fall back for long.
Have you bought your 2010 Missouri Football Preview yet??
Rock M Nation
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Do you think getting the higher percentage correct...
…with the (5-10) (10-20) (20-30) groups will stand up as the season progresses? Here’s why I ask. I would guess if you’ve adjusted your projections well from last season, the (5-10) and the (10-20) should give you the highest percentage correct and that these should help you keep up with Vegas. The cloesest games and the furthest apart should be hardest to predict, if you’ve tweeked it well.
Which were the groups that held up with the best percentage last year? I can’t remember.
But I barely know any advanced stats so, I really don’t know.
Dr. Ausgiano schools me in the classroom and on the field of battle
by MarioVanPeebles Republic of China on Sep 9, 2010 5:42 PM CDT reply actions
You know what I think is happening?
Your model generally beats the odds because it is better at weighting lots of small factors than regular people – they tend to fixate on one or two bits of info rather than being able to consider dozens of them all together.
BUT there is something that you are missing for some teams (maybe not always the same thing for all of them), and when that factor kicks in your model throws out a waaay wrong prediction, which you then gleefully label a LOCK.

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