TheGeekSheetSports.com was founded in 2003. We are dedicated solely to handicapping College Football. It’s 100% of our focus, 52 weeks a year. It’s what we do and we are the best on the net!

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This year marks our 6th season of The Geek Sheet Sports, and our lifetime record of 255-155-9 (62%) is as good as you will find out there. We’ve only had one season below 0.500, and over half have finished north of 65%, an accomplishment we are extremely proud of. Our system is predicated on a statistical analysis of past performance, and as such typically hits its stride around week 4-5 when we have 3-4 games of good data on each team. We are always looking for ways to improve our system and after a couple years of testing we rolled out an early season statistical modification last season that really improved our early season performance. We’ve made further refinements to that his off season and our looking forward to really hitting the ground running this year!

We do things a little differently around here, so take some time to review some of our posts regarding wager guides, our philosophy, past results, and listen to some of our web-casts. I hope you find things informative and more than anything 100% transparent. Football handicapping is a lot science, a little art, and a lot of things that are outside your control. We pride ourselves on our honesty and integrity. There is no way we can tell you what is going to happen. What we promise to always do is tirelessly research and report on what we think will happen and more importantly why. Handicapping can be extremely lucrative with the proper approach and attitude, more importantly, it should be fun! So take the proper approach to money management, understand the risks, what you do and do not control, and have fun with it! Otherwise we can all go try and mint our millions arbitraging spreads off Sovereign Debt…that sounds exciting…and certainly completely within our control!

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After spending many years tirelessly researching teams, trends, angles, and power ratings — while surveying the litany of “experts” out there and their mostly conflicting and confusing games of the week, games of the month, and games of the year — I realized that one thing was certain: to continue that course of action was to accept consistent losses. I realized there had to be a better way.

Instead of focusing on picking winners by searching out trends and angles, I shifted my focus to accurately determining what the score should be. I refined models which focus on those games with the highest level of reliability in those predictions, then identify which of those games have the largest variance from the current betting line.

I surmised that if I could devise a system to chart the accuracy of these forecasts, I could (relatively speaking) accurately assess the odds of my predictions proving out (when combined with large variances in the lines produces winners).

After identifying those opportunities, we then evaluate where the line values are. We don’t ignore situation analysis, trends, angles, or even common sense. But we make the above assessment the foundation of our research, from which we then focus on the specifics of the game.

We have found this approach to be extremely successful, and are constantly working to refine our methods, and analyze what makes up acceptable alignment of models and variances from line based on the lines themselves.

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We have released 5 RECOMMENDED Plays for the week 12.  We have some really strong plays and loved some of the line variances.  It’s been a really tricky year, but we truly believe our analysis has been dead on.  Our methods are proven, and we’ve been doing this for many years.  We have been really disappointed in our luck for the year, but we know things will turn around.

Click below to see the GEEKSHEETS:

• UConn – #3 Recommended Play – W
• UAB – #3 Recommended Play – L
• SMU – #4 Recommended Play – W
• ULM – #2 Recommended Play – L
• Hawaii – #2 Recommended Play – W

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Well if nothing else our bad luck is getting more and more absurd and hard to believe…had I told you Wednesday that your 30 pt dog would outgain the favorite by nearly 100 yards in the 1^st half and outgain them for the game, would you feel pretty good?  How about your 3 pt dog coming 3 yards from doubling the total offense of the favorite?   We would to.

Idaho lost to Boise 63-25 (as a 31.5 pt underdog), despite somehow outgaining Boise 514-498 as a 31 pts underdog, including a 399-303 advantage at half (so it wasn’t like it was poured on late hen the game was over).  Boise benefited from 5 INT, 2 Fumbles, a 100 YD Kick Return for TD, an INT for TD, and a Fumble and INT on the 1^st two possessions that set up scoring drives of 15 and 31 yards for Boise.  I can’t even fathom how a 30 pt dog outgains a team like that and it took nearly every bad break listed above for them to lose by 38.  Take away either the 100 YD kick return (w/ 27 seconds left to go before half) or the INT returned for a TD and we cover, although this certainly should have been much closer.

North Texas outgains FIU 513-258…that is 3 yards from lapping the team they where a 3 pt underdog to, but an INT returned for a TD, a blocked punt, and a NTU fumble all in the 2^nd half allowed FIU to overcome a 28-14 halftime deficit.  And to add insult to injury, NTU had an opportunity to tie the game and send it to OT, driving to inside the FIU 10 with 2 minutes to go before a TO on downs.

We had very solid Ws with Syracuse (7pt dog) who nearly one outright (UL scored with 1:27 remaining), correctly called for the Straight up Stanford W (as a 10 pt dog), and Utah State W 24-9.  Rutgers, ULM, and Duke weren’t so good, BC could have gone either way (W or L) so was probably fair to get a Push,  and got totally jobbed on the NTU and Idaho games.

3-5-1 isn’t good, but it definitely should have been 5-3-1, no worse than 5-4 and with some luck could have been 6-3 (depending on a break or two in the BC game).  We are now a disappointing 33-36-2 and an amazing 2-17-2 in good luck/bad luck games.  We’ve been correct in our analysis in 49 of 71 games or 69% of the time (33 W – 2 Good Luck Ws + 17 Bad Luck Ls + 1 Push=49).  So in any normal year where the good breaks and bad breaks would even out we’d be doing great (69% with 50-50 split of good luck to bad luck), and even with some parity in the luck would not only have a winning record, but would be pretty close to our historic record of 62% (248-152-9).

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It was a frustrating week going just 2-4 on our recommended plays, and again being the beneficiary of some horrible luck.  We had an easy winner on our #1 recommended play as Nevada destroyed SJSU 62-7, outgaining them 655-258 (including over 500 on the ground, which we called for them to top 400 yds rushing).  We again suffered some horrible luck this week on our 4 Losses:

1. #2 recommended play TAMU (-3):  TAMU was up 21-10 at half (which should have been more as they had a TAMU turnover on downs at the 1 yard line on the 1^st drive of the game), and up 6 with 3 minutes to go in the game despite a 2^nd half that included 1 missed FG and two stalled drives in the red zone that settled for FGs (one of which on the 3 yd line).

1. #3 recommend play Army (+17):  AF wins 35-7 despite only 292 yards (of which 75 came on one play).  The game was 7-7 with AFs only points coming via a punt return TD, long pass play (75yd) and some really unfortunate short field possessions  (AF gained 4.7 yppl which if you take out the one long pass play was much worse, 3.6 yppl), which is very close to our projections of 262 yds @ 4.0 yppl. Army gained 236 ypds (4.0 yppl) which is actually better than the 213 (3.7 yppl) we projected.  To give you a sense of how unusual 35 pts on just 292 yds  total offense is, here are the production of a couple other of our recommended plays this week:
   1. SJSU: 7 pts – 258 yds (4.9 yppl)
   2. UNC: 19 pts – 311 yds (3.9 yppl)
   3. Oklahoma -3 pts – 325 yds (3.7 yppl)

Oklahoma should have had a little more (probably close to 13-17), but all in all I think it is pretty obvious our analysis was correct, and we were on the right side, just horribly unlucky

1. #4 recommend play Duke (+10)- we were in great shape with a 6-6 score late in the 3^rd quarter before this comedy of errors occurred:
   1. Duke picks off UNC returning it to the UNC 37, looking good to go up at least 9-6 heading into the 4^th quarter.  2 plays later Duke throws a pick that is returned to the INT sets up 20, 3 and out later – UNC FG and 9-6 UNC lead to end the 3^rd quarter…at minimum a 6 point swing
   2. Duke TO on downs at the UNC 41 which leads to a TD
   3. UNC Punt return to the Duke 28 yard line which leads to a FG with less than 4 minutes to go in the game to push it over the 10 pt total.

We feel very confident in our analysis of this game, and that we were on the correct side and with any justice should have been up 9-6 heading into the 4^th.

1. We did get a little fortunate in the Nebraska game as their O struggled much more than we anticipated, however the D held up as we suspected.  OU missed 3 FGs, although all 3 where 40+ attempts with 2 of the 3 being from 45+ so they were anything but certain.  OU also had 5 Int, however 3 of them occurred in the 4^th Q w/ Nebraska already up 10-3.  The two other INTs set up Nebraska on short field leading to their 10 points, but to be fair Nebraska also fumbled the ball on the OU 21 which effectively erased at least 3 maybe 7 points as well, so the net effect of TOs wasn’t as bad as one might think.

Depending on whether or not you think we were lucky in the Nebraska game our record in bad luck / good luck games is now a nearly impossible to believe 2-15-1 (or 1-16-1).  With a record of 30-31-1that means we’ve been correct in our analysis of 46 (or 47) of 62 games which is right at 74%, yet just below .500 in the outcomes.  Presuming that luck, by definition, is random we should expect to be the beneficiary of good luck as frequently as the bad luck, which has clearly not been the case.  Even if you just took away half of our bad luck losses (which would still be just 2-8-1 on bad luck/good luck games), we’d be 37-31-1 or a respectable 54%.  If the luck was truly equitable we’d be .500 in our good luck/ bad luck games (effectively meaning we’ve suffered 13 too many losses / pushes) and a very solid record of 43-19 or 69%.
All that said, luck evens out in the long run, and our historical record (5 years) of 245-147-8 (63%) attests to that fact, and the validity of our methods.  Also, considering the bad breaks this year (basically 25% of our total games), to be .500 is actually a pretty accomplished feat (if you do the mathematics of starting -25% in the whole based on correct analysis and assessments validated by the performance).

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