Basketball is BACK and Dr. Bob Has the Scoop!

Friday, December 30
Basketball Best Bets +500.7 Stars (at -1.10 odds) Last 13 Seasons!
Friday Basketball Available after 3 pm Pacific.

NBA Best Bets 145-79-2 on a Star Basis first two weeks last 9 seasons
My early season NBA basketball handicapping has been very good since I discovered and starting using my indicators 9 years ago. In fact, my NBA Best Bets are 150-81-12 on a Star Basis in the first two weeks of the season the last 9 years (although I'm just 3-4 on my NBA Best Bets so far this season).

Basketball Best Bets 37-43-2 for -26.7 Stars
I have a few horrible stretches every season and 19 out of 25 years have still resulted in a profit on my basketball analysis. Unfortunately, I'm in the middle of a bad run right now, as I was just 3-5 on my Thursday Best Bets after a horrible night on Wednesday. Normally, the losing streaks are a function of losing close games and 3-point shooting variance and tonight my 8 Best Bets were a combined 27.9% on 3-pointers (39 for 140) while their opponents were 43.7% (69 for 158). My 5 college Best Bets, which were 1-4, were a combined 18 for 80 from 3-point range (22.5%) while their opponents were 46 for 111 (41.4%). It's impossible to predict that sort of variance, especially when my 5 College teams were expected to make a combined 35.2% from 3-point range while allowing 33.4%. My Best Bet win on Cal Irvine +4 (won by 9) was only positive 3.3 points in variance, so they would have covered easily anyway. Two of my losses, Marquette -8 (lost by 17 with -14.4 points of 3-point variance) and Tennessee Tech -10 1/2 (lost by 15 with -15.1 points of variance) would not have covered even if 3-point shooting was as expected. But, my Best Bet on Detroit -6 1/2 would have covered with normal 3-point shooting by both teams, as Detroit lost by 4 with -15.1 points of 3-point variance (they were 0 for 10 while Illinois-Chicago was 10 for 22). My other loss on The Citadel +21 1/2 (lost by 31) suffered -10.1 points of 3-point shooting variance so that game would have been a toss-up with expected 3-point shooting (The Citadel, expected to make 37%, made 4 of 19 while Tennessee, expected to make 38%, made 9 of 22). Negative variance in 3 point shooting is how a 2-3 or 3-2 record turns into a 1-4 record. I did win 2 of my 3 NBA Best Bets with wins on Dallas +5 1/2 (lost by 2 on a buzzer beater by Durant) and a close win on Chicago -8 (won by 10, but could have lost if the Kings were better from the line) and a loss on the Knicks. I'm going to have good stretches this season when I'm winning close games and have some positive 3-point variance. In the long run that stuff tends to even out and I'll be between 52% and 58% like I always am in basketball.

I am 37-43-2 on my Basketball Best Bets and 91-107-4 on a Star Basis (17-21 on 3-Stars and 20-22-2 on 2-Stars) for -26.7 Stars at -1.10 odds. My average line differential is slightly negative at -0.4 points, and I am 10-13-2 on games decided by 3 points or less. It's been a tough stretch, but I've been down more than this and come back to have profitable seasons and there is a lot of games left in this season to still make a good profit.

Last season I had a week in which I was -23.9 Stars and another week when I was -17.7 Stars and I still ended up +30 Stars for the season. In 2009-10 I was -9.5 Stars at the end of January and ended the season +34 Stars of profit. Losing streaks are inevitable in sports investing, even in very good seasons, and I know the short term losses sting. But the long run has been consistently good for my clients over the years so try to maintain the proper perspective.

4 Week Subscription Now Available for $245
You can purchase Basketball Best Bets daily for just $15 and I also have a 28 day subscriptions available and a packages that go through the NCAA Tournament and through the NBA Finals for about $7 a day. Available Best Bets Packages

2011-12 Season Subscriptions Available
All Football and Basketball Best Bets +697.5 Stars Last 13 Years!
My 2011 Football and Basketball season subscriptions, as well as my Football-Basketball Combo Package (the best value) are now available. Should the NBA season be shortened refunds for weeks missed will be given.

2010/2011 Season Results
Best Bets 442-375-16 on a Star Basis
I lost my 2-Star Best Bet on the Under but the win by Dallas resulted in a profit of +3.2 Stars on the series (2-Stars risked at +1.60 odds). I had Dallas rated as the best team in the NBA heading into the playoffs and that proved to be the case. In the playoffs I was 12-10 on Best Bets (despite losing a 5 point dog in OT), 14-9-2 on Strong Opinions, 16-21 on leans and 3-0 on Series Bets for +11.0 Stars (1 Star on Memphis over San Antonio for +3.3 Stars, 1.5 Stars on Dallas over the Lakers for +4.5 Stars, and 2 Stars on Dallas over the Heat for +3.2 Stars).

I had another profitable season of Basketball Best Bets despite losing more close games than I won (15-21 on Best Bets decided by 1 point or less). For the season I was 442-375-16 on a Star Basis (3-2 on 4-Stars, 59-53-2 on 3-Stars and 121-104-5 on 2-Stars and 3-0 on playoff series bets for +11.0 Stars) for a profit of +29.5 Stars at -1.10 odds. Had I gone 18-18 on those close games I would have profited another 14 Stars, so I'm satisfied with my level of handicapping despite not profiting as much as I usually do in Basketball.

Basketball Best Bets +500.7 Stars Last 13 Seasons!
My Basketball Best Bets are 6609-5553-265 on a Star Basis the last 13 seasons, for a profit of +500.7 Stars at -1.10 odds, and I’m 55% on my Basketball Best Bets over 24 seasons.

Free Analysis
I post free analysis almost every day during basketball season on anywhere from 1 to 5 games and those opinions have been profitable over the years.

I was 1-2 on my Wednesday opinions. I'm 2-1 on my free Best Bets and 21-18 on my free opinions this season.

Last season I was 12-6 on my free Best Bets and 105-88-2 on my free opinions and I am 38-30-1 on my Free Best Bets and 428-378-12 on my free opinions the previous 4 seasons.

Friday Basketball Available after 3 pm Pacific.

Houston vs. Indianapolis: Free Analysis

This is a great week to be in the sports handicapping business. There are tons of good match ups and tough games to pick- Oakland at Kansas City, San Diego at Detroit, and Philly at Dallas are all coming in with under 3 point spreads. This is what the end of the NFL season is all about!

Another hard game to handicap for any sports betting service is going to take place Indy. Indianapolis if coming hot off of their first win of the season under QB Dan Orlovsky, so they have a little momentum. Their offense may finally be clicking it seems. Defensively, they have also improved over the last 5 games, allowing only 5.2 yards per play. This might, however, be due to variance and we could see this stat change as the season finishes out.

On the other side of the ball, Houston is playing some of it's worst football of the season. They've been below average offensively for the last four games due to the loss of quarterback Matt Schaub. This may turn out to be irrelevant though, as they continue to be among the leagues leaders defensively. My sports analysis math model has them quenching the Colts newfound fire by an easy 8 points but I'm giving them 6 1/2 in case Indy's defense is turning into the real deal instead just being variance.

All in all, if you're looking for a game to bet this weekend, you'd probably do well to avoid this one. There are too many moving parts and a lot of variables that make this anything but a lock.

All About Football Handicapping Techniques

The NFL is among the most popular sports in America with millions of users around the country. Since first beginning there’s always been those betting on the outcomes. In order to get more accurate results numerous gamblers are now turning to football handicapping services.

In order to handicap these games professionals in this industry use a variety of techniques. There are many factors that can affect the outcome of the game including its location, strength of each team, player injuries along with weather conditions. Many will also rely on past statistics and recent trends to increase level of accuracy.

With latest developments in technologies, efficient software systems have been designed to assist pro handicappers with sports betting advice. In the past managing details and stats had been highly time-consuming plus difficult. Everything is assessed in seconds because this software is capable to record enormous amounts of information.

A bookmaker is the person who collects bets from gamblers on each game. When the person betting on the event does not win, the bookmaker simply keeps their money. They will pay off the amounts won to winners, and to guarantee profits they establish a point spread. The underdog is awarded a specified number of points and this attracts bets on each team.

A handicapper is someone who has skill predicting these games. However, even with their best efforts it’s impossible to always be completely accurate. There are instances when a team that’s favored will end up losing. Their job is to try and predict as many games as possible so that their clients can place winning bets.

Gambling upon sports is a large industry that takes in millions of dollars each year. Due to the increased popularity, football handicapping has become more in demand than ever and the industry is predicted to grow continuously in the future.

Sick putting money on poor sports betting choices? Do you want your buddies and co-workers to value your wager decisions? Then check out Dr. Bob Sports for the best in sports handicapping! The world famous Bob Stoll offers wagering tips on college football, the NFL, and pro basketball. Free analysis is available on the site, along with essays on wagering on sports, managing your money, and other helpful info.

Free Analysis of New England vs. Washington

This may surprise some in the football handicapping industry, but New England’s total yards per game margin of +11.6 yards isn’t much better than Washington’s -8.5 yards per game margin and Washington has improved offensively in recent weeks with Roy Helu as the main running back and with WR Santana Moss back from injury. Helu’s 4.7 ypr average is significantly better than the combined average of Tim Hightower and Ryan Torain (3.7 ypr combined) and the good rushing attack has made it easier for the Redskins to score when they get close to goal line, which has been a problem most of the season.

Washington has averaged 22 points the last 3 games after averaging just 15 points the first 9 games and part of that is also due to Moss and quarterback Rex Grossman returning to the lineup. Unfortunately, the Redskins will be without star TE Fred Davis, who was suspended for the final 4 games. Davis led the team in receptions and averaged a very good 9.0 yards per pass thrown to him, which is easily the best on the team. Backup TE Logan Paulsen has averaged 8.6 ypa but that’s only on 11 passes thrown to him and I doubt he’ll be able to maintain that average. The sports analysis I've done on the Redskins says that if Davis’ attempts are spread out amongst the current receivers then Washington’s pass rating would drop by 0.44 yards per pass play, which is worth about 1 ½ points. The Redskins’ attack is still better than their season rating of -0.4 yards per play even without Davis, as having Moss back helps the pass attack some (it was horrible when he was out) and having Helu as the starting running back is significant. Washington is actually just 0.1 yppl worse than average offensively with their current lineup and the Redskins’ defense is 0.4 yppl better than average and has allowed just 4.6 yppl their last 4 games.

I took Washington as a Best Bet last week and the Redskins out-gained the Jets 304 yards at 4.3 yppl to 268 yards at 4.5 yppl and led the game with 5 minutes left before turnovers killed their chances. I think the Skins can compete in this game against an overrated Patriots team with a horrible defense that has been even worse lately with injuries to the secondary. Patriots’ CB Kyle Arrington should return this week but the Pats have really struggled without S Patrick Chung, who is listed as questionable. My math model actually projects Washington to out-gain the Patriots in this game but turnovers are an issue with Rex Grossman at quarterback (he’s projected to throw 0.9 more interceptions than Tom Brady is, which is 3.2 points).

Even with that being the case, my main math model favors the Patriots by only 2 points. That model assumes teams score at efficiencies based on their overall level of play but New England has out-scored their statistics by 4.1 points per game this season. The Patriots have actually out-played their stats by 2.8 points with Brady at quarterback over the years and the would give me a prediction of New England by 5 points. My adjusted point differential model has the Pats by 6 ½ points, so the line is too high regardless of how you look at it so with my sports investing capitol, I’ll take Washington plus the points.

Tough Year For NFL Handicappers

Well it's been a tough year for my professional football analysis this year and it seems to me that I'm dealing with a big case of our familiar friend variance! For those who don't know, variance refers to the random up and down streaks that every bettor faces in their lives.

In the NFL, variance happens mostly because of turnovers, and no sports betting service in the world can predict those! It all boils down to bad luck. I still haven’t had any lucky wins in this season and I’m an unlucky 3-6 on Best Bets decided by less than 7 points (with one of those wins being the Dallas at New England game that was really not a close win since the Pats were down by 3 points before scoring late to win straight up).

That said, I am really just 13-14-1 on my NFL Best Bets (27-30-2 on Stars) and 21-6 on my Strong Opinions, which is still a winning record when combined. (34-20-1) This means my sports investing is paying off and obviously working well overall- which is a good sign going forward.

While there has been a ton of variance and I should be up much further than I am, in reality I’ve had a good grasp on the NFL overall this season given that I’m actually 101-63-5 ATS picking every NFL side (adding in my Free Analysis picks which are 72-47-5 ATS)

For the rest of the season, I'm just gonna continue what I'm doing, but focus mostly on which games to make my "Best Bets". Probably I'll take a slightly more conservative approach on this.

Great Wager Minds Interview With Dr. Bob!

If you’ve been interested in sports handicapping for any meaningful period of time, you’ve probably heard about Dr. Bob. In 2007, the Wall Street Journal called him ‘The Man Who Shook Up Vegas.’ He’s been profiled on CNBC, ESPN and and elsewhere. And he’s received this coverage for good reason.

Bob Stoll, aka Dr. Bob of Dr. Bob Sports, is one of the handful of honest pick-sellers in the sports advisory business. He attended Berkeley but didn’t graduate. He was a statistics major with a penchant for quantitative analysis. And he has put his math skills to work in the sports investment business. See, Dr. Bob refers to sports gambling as sports investing because, with statistical analysis and a disciplined money management system, he believes gambling is the wrong term. Since following his picks would have generated an average annual return of 69% over the past 12 years, a rate of return far in excess of the stock market return over the same period, investment may well be the best term.

Our question and answer session with Dr. Bob is below:

WM: How long have you been involved in sports handicapping?
Dr. Bob: I got involved in handicapping 26 years ago while I was studying statistics at Berkeley. I entered a $2 NFL pool and decided to crunch some numbers to see if I could come up with a system to help me win. As luck would have it, I won the first week by going 12-2 and that peaked my interest in doing more research.

WM: What led you to get involved in the industry?
Dr. Bob: There was a professor at Cal, Mike Orkin, who used to consult with the Gold Sheet from time to time when they had statistical questions, and Orkin also developed a computer tool called the pointspread analyzer to search for patterns. I was already doing some technical analysis of my own using time series analysis and professor Orkin recommended to the Gold Sheet that they talk to me about writing something for their Technical Report. I wrote about a pattern I had discovered and that article got noticed by the Las Vegas Sports News, who asked me to write a column for them. That exposure led to being asked to be a guest on a nationally syndicated radio show hosted by handicapper Dave Cokin and it went so well that Dave had me back as a regular guest pretty much every week. I think it might have been Dave that suggested I get a 900# and start charging from picks. I did and then started a weekly print publication in 1987.

WM: What was your worst season? And what was your best?
Dr. Bob: My worst season was 2007, when I was 32-42-1 on my College Football Best Bets. That was particularly bad timing to have a randomly bad season (I had a horrible record on close games that year) because it was just after 3 incredible seasons in which I was a combined 151-89-5 on my College Best Bets and those 3 great seasons led to an article in the Wall Street Journal and a story on ESPN’s E:60 show. That media attention got me a ton of new clients and then I had my worst year ever and lost most of them. I rebounded the next year and won 59% but I had lost most of the new clients that joined me because their first year with me was so bad.

My best season percentage wise was my 2005 College Football season when my Best Bets went 51-21-1, including 27-5-1 on my higher rated plays. I was also 58% on my Basketball Best Bets right after that so the 2005/06 year was my best overall year. My most profitable season was the 2003/04 Basketball season, in which I was 664-483-39 on a Star Basis for +132.7 Stars of profit at -1.10 odds.


WM: What makes your handicapping process distinct and how have you been able to enjoy winning records for such a long period of time?
Dr. Bob: I think what made me different was that my statistics background gave me some good insights into how to come up with models that would do a better job of predicting what’s going to happen rather than explaining what has happened, which is what most models do. I was also one of few that combined technical analysis with my successful math models. There are a lot of handicappers that depend mostly on situations and there are handicappers that depend on their math models, but there aren’t many that do both well and know how to weigh the different factors. I’ve done mathematical studies on how predictive situations are going forward and I also know how well my math model has predicted. I have a spread sheet with thousands of games that combine the math model predictions with the situational analysis associated with each game and I study that spread sheet to find the best combination of line value and situational analysis. I won’t bet a game in which the situational analysis is strongly on one side if my math model is on the other side, or visa versa, and I think using both methods keeps me from betting games that my math model or the situational analysis may like but actually aren’t good bets.



WM: Do you have other quantitative people on staff to help fine tune your models or do you do it all yourself?
Dr. Bob: I do everything myself. I’m sort of a control freak and I don’t trust anyone to do any of the modeling or any of the sports analysis. I do have a guy that keeps track of lineup changes and injuries and that tallies garbage yards in blowout games so I can adjust for those things in my model, but all the handicapping and modeling is done by me.

WM:If you were going to give a new handicapper 1 golden rule of handicapping, what would it be?
Dr. Bob: Take a statistics class to understand probabilities and variance. Actually, I wish every client would do that too. Understanding that short term variance is going to affect results can not only keep you focused on the long term, but it can also help you figure out how to take advantage of short term variance and use it in your favor when picking your games and developing models.

WM: Assuming you have a favorite team, do you have a policy to never bet when that team is involved in a game?
Dr. Bob: I am a Cal fan, but I will bet against the Bears if the situation or my math model tells me I should. I’ll still root for Cal regardless, as I am pretty good at separating my loyalty as a Cal fan with my job.

WM: As you know, the handicapping industry is filled with many unsavory characters. What people and information sources in the handicapping industry do you trust?
Dr. Bob: I know there are some good handicappers out there that supply good information and are profitable in the long run (Right Angle Sports comes to mind and I have a buddy that follows a Spanish guy named Gomez that’s great in the NBA), but I actually don’t follow any of them and don’t seek out their plays. I trust what I do and I don’t want to be swayed by someone else.

WM: Do you bet your own plays?
Dr. Bob: I got that same question when I did the Wall Street Journal article and my answer was that I’d rather not say because it’s a no win situation. If I said yes then I’m admitting in a national publication that I am betting illegally and that certainly is not something I want to admit. If I said no then people question me for that and think I don’t even trust my own plays enough to bet them. Whatever answer I gave could hurt me. Let’s just say that I trust my plays enough to bet them myself and I have good reason to do so given my long term record.

WM: Is there a limit to how many clients/subscribers you’ll work with?
Dr. Bob: No. The work I do each week is the same regardless of how many clients I have.

WM: What is your all-time worst beat?
Dr. Bob: Back in the late 80′s and 90′s I used to release 5-Star Best Bets, which were really rare since they were game I thought had a 70% chance of winning – you won’t find many of those these days. At one point I was 14-0 in my career on football 5-Stars and I had a 5-Star on San Francisco -3 1/2 (I forget what year, but sometime in the mid-90′s). The Niners were up by 17 points late in the game and gave up a touchdown with about 40 seconds remaining then didn’t recover the onside kick. The other team was then stopped on 4th down, as I recall, but there was a ridiculous penalty called against SF, which allowed for one more play. That play was a Hail Mary pass that was caught for a touchdown and the extra point made the final margin 3 points. I actually thought they may not kick the extra point since there was no time on the clock, but they did kick it. I’m sure everyone has had something as bad or worse than that, but that my first and only 5-Star loss ever, as I am 18-1 on 5-Stars in football and don’t release them anymore.

I do remember a lucky win though, also involving a 49ers game. I had the Niners minus 8 or 9 points and they were only up by 6 with one more play and the Packers had the ball on the San Francisco 3 or 4 yard line. The only way I could win was an interception return for a TD and that’s exactly what happened



WM: In your personal life, do the people around you know you’re Dr. Bob, a legendary sports investor? And, if so, how often does a neighbor hit you up for a ‘sure thing’ at a cocktail party?
Dr. Bob: I actually only have a couple of friends that gamble on sports, as most gamblers drive me nuts because they’re so undisciplined and irrational. So, I don’t often get asked for picks and there are ‘no sure things’ in sports betting. There are some people that find out who I am and want to know what my ‘Lock’ is. Then I find myself spending 10 minutes trying to explain to them that there is no such thing as a Lock and that no game has more than a 75% chance of winning since studies have shown that 50% of all sports bets are determined by highly variable events such as turnovers or special teams. So, if 50% of the games are determined by chance then a perfect handicapper would only win 75% of his bets even if he were on the right side of every game (he’d win all 50% of the games that weren’t determined randomly and win half of the 50% that are random).

WM: Since you’re probably best known for your college hoops skills (and it’s college hoops season), tell us what 3 college basketball coaches you want to round out your golf foursome.
Dr. Bob: I actually became well known for my College Football success but I have been more profitable in basketball over the years since there are so many more games to play in a season.

I suppose I’d like to play with Mike Montgomery because of his quick wit (and he’s the coach of my beloved Golden Bears). You’d also need someone to keep the mood light and I think Rick Majerus would be good for that. I’d also probably need someone even keeled like Coach K to teach me life lessons and give me necessary perspective in case I’m having a horrible round under the pressure of playing with those 3 guys (which would be likely).

This article was originally published at WagerMinds

Free Analysis For Thursday Night Football!

DENVER 21 NY Jets (-6.5) 20

Over/Under Total: 40.0

05:20 PM Pacific Time, Thursday, 17-Nov-2011

The Broncos are making the Tim Tebow experiment work by building an offense built around his skills, which is his ability to run a zone read running offense like he did at Florida. Denver threw just 8 passes and ran the ball 54 times last week in a win over Kansas City last week and they beat the Raiders with Tebow averaging just 4.9 yards per pass play (they ran for 299 yards). Denver has actually won 3 of Tebow’s 4 starters because of their underrated defense and by taking care of the ball. Teams that don’t throw much don’t turn the ball over as much and Tebow isn’t a quarterback that throws interceptions when he does have to throw it (just 1 interception on 105 passes this season and only 4 picks on 187 career passes). The Broncos have scored 18 points or fewer in 3 of Tebow’s 4 starts but the overlooked defense has allowed an average of 16 points in the 3 recent wins and that unit is a bit better than average for the season thanks to a solid run defense (4.2 ypr allowed to teams that would average 4.4. ypr against an average team) and a very good pass rush (2.7 sacks per game) that has turned up the pressure lately (17 sacks the last 5 games).

New York is still considered an elite team, but the Jets have actually been out-gained 314 yards at 5.1 yards per play to 329 yards at 5.3 yppl this season are only 0.1 yppl better than average from the line of scrimmage after compensating for their tougher than average schedule (they’re 0.4 yppl worse than average on offense and 0.5 yppl better than average defensively). The Jets do have great special teams, so they are pretty efficient with their yards, which is why they’re out-scoring their opponents by 1.7 points per game, but my main math model favors Denver by 1 point in this game. That model doesn’t take into account the Jets’ tendency to play better than their stats but my other model, which does take other factors into account, favors New York by only 2 ½ points. Even if the fair line should be Jets by 3 ½ points that would still make Denver a 55.5% play at +6 points. This is one of those games that is still tough to bet even when I know it’s a good bet. Those are the games that I’ve been making Strong Opinions this season and my Strong Opinions are 18-5 in the NFL. So, I’ve decided to pull the trigger on this game and make it a Best Bet, as the tougher a game is to bet the better bet it usually is. I also like that 77% of all bets have been on the Jets in this game and the public is usually wrong when the betting percentage is so one sided. I’ll take Denver in a 2-Star Best Bet at +6 points or more.

Free Big Ten Analysis

Here's my free analysis from last week for the Big Ten. If you haven't checked out my free college football analysis, check it out here!

Michigan St. (-2.5) 26 IOWA 21

Over/Under Total: 47.0
09:00 AM Pacific Time Saturday, 12-Nov-2011
Michigan State's defense has cracked a bit in recent weeks, so Iowa's good offense should be able to score a decent number of points. However, the Hawkeyes are mediocre defensively and my math favors the Spartans by 5 points in this game.




Nebraska (-3.5) vs. PENN ST.

Over/Under Total: 43.0
09:00 AM Pacific Time Saturday, 12-Nov-2011
This game is part of Dr Bob's Best Bets package, which includes all of Dr. Bob's Best Bets, Strong Opinions and other withheld games. For the analysis of this game and all the Bets and Strong Opinions for this week click here




Ohio St. (-7.0) 27 PURDUE 19

Over/Under Total: 46.0
09:00 AM Pacific Time Saturday, 12-Nov-2011
My math model favors Ohio State by 8 1/2 points.




NORTHWESTERN (-16.0) 45 Rice 26

Over/Under Total: 67.0
09:00 AM Pacific Time Saturday, 12-Nov-2011
Rice is better with Nick Fanuzzi at quarterback, as he's averaged 6.8 yards per pass play on 111 passes against teams that would allow 6.3 yppp to an average quarterback, and Fanuzzi should put up big numbers against a horrible Northwestern pass defense. Rice, however, also has a horrible defense and my math model favors the Wildcats by 14 points. The line value is with Rice but the Owls apply to a very negative 128-230-7 ATS situation and a 19-61-2 ATS situation based on their bad defense. I'll lean with Northwestern based on the angles.




Wisconsin (-27.0) 46 MINNESOTA 16

Over/Under Total: 63.5
12:30 PM Pacific Time Saturday, 12-Nov-2011
Wisconsin has dominated weaker teams all season, going 5-1 ATS as a favorite of 14 points or more and the Badgers are 8-1 ATS in that role since the middle of last season with the median win margin being 45 points. Minnesota is improving, but my math favors Wisconsin by 26 1/2 points, so the line is fair, and the Gophers apply to a negative 61-140-3 ATS situation.




Michigan 26 ILLINOIS (-1.0) 23

Over/Under Total: 49.5
12:30 PM Pacific Time Saturday, 12-Nov-2011
My math model picks this game even but Illinois applies to a negative 39-118-2 ATS situation that will have me leaning with the Wolverines.

Cincinnati vs. TENNESSEE (-2.5)



Over/Under Total: 42.0

01:05 PM Pacific Time, Sunday, 06-Nov-2011

I usually post my NFL football free analysis after 10:15 AM Pacific on Friday. Please check back later.

Average Team Stats for 2011

		Rushing Stats				Passing Stats							Total
	Pts	Atts	Yds	Ypr	Fum	Comp	Att	Int	Yds	Ypp	Sack	Yppp	Yds	Yppl
CIN-Offense	24.4	27	105	3.8	0.13	20	33	0.88	212	6.3	1.6	6.0	317	5.1
CIN-Defense	17.5	24	87	3.5	1.13	20	34	0.38	214	6.2	2.5	5.8	302	4.9
League Average	22.3	26	116	4.4	0.58	20	33	0.98	234	6.8	2.3	6.4	350	5.6
TEN-Offense	19.5	21	68	3.1	0.38	22	35	0.75	240	6.7	1.5	6.4	308	5.2
TEN-Defense	21.1	29	127	4.2	0.38	23	37	1.00	227	6.1	1.8	5.8	354	5.1

Ypp = Yards per pass attempt
Ypp = Yards per pass play (attempts + sacks)
Yppl = Yards per play (rushes + passes + sacks)

Cincinnati Bengals: SU: 6-2-0, ATS: 7-1-0

GAME LOGS 2011

RUSHING

PASSING

Opp

Scr

Sprd

Tot

Atts

Yds

Ypr

Fum

Comp

Att

Yds

Int

Sac

Ypp

TOT

09/11 @Brow

27-17

+6.5 W

35.5 O

31/25

139/84

4.5/3.4

0/0

15/19

27/40

155/202

0/1

4/2

5.0/4.8

294/286

09/18 @Bron

22-24

+3.5 W

40.0 O

19/35

74/133

3.9/3.8

0/2

27/15

41/25

310/187

0/0

2/2

7.2/6.9

384/320

09/25 49ers

8-13

-2.5 L

40.5 U

20/28

79/68

4.0/2.4

1/1

17/20

32/30

149/176

2/0

1/5

4.5/5.0

228/244

10/02 Bills

23-20

+3.0 W

43.5 U

32/21

171/83

5.3/4.0

0/0

18/20

36/34

287/190

2/0

2/1

7.6/5.4

458/273

10/09 @Jag

30-20

+2.0 W

36.5 O

31/26

77/97

2.5/3.7

0/2

21/14

33/27

162/180

1/0

2/3

4.6/6.0

239/277

10/16 Col

27-17

-7.0 W

41.0 O

29/23

95/94

3.3/4.1

0/2

25/23

32/34

264/179

0/1

0/1

8.3/5.1

359/273

10/30 @Sea

34-12

-2.5 W

37.5 O

27/20

92/61

3.4/3.1

0/1

18/25

29/47

160/350

2/1

1/4

5.3/6.9

252/411

11/06 @Tit

24-17

+2.5 W

42.0 U

30/20

109/78

3.6/3.9

0/1

22/24

39/41

210/250

0/0

1/2

5.3/5.8

319/328

Notes:

1. Spreads shown relative to the Bengals. 2. Stats read as Offense/Defense or Bengals/Opponent.

Tennessee Titans: SU: 4-4-0, ATS: 3-4-1

GAME LOGS 2011

RUSHING

PASSING

Opp

Scr

Sprd

Total

Atts

Yds

Ypr

Fum

Co

Att

Yds

Int

Sac

Ypp

TOT

09/11 @Jag

14-16

+2.0 T

37.0 U

13/46

43/164

3.3/3.6

0/1

21/17

33/24

249/160

1/0

2/2

7.1/6.2

292/324

09/18 @Rav

26-13

+5.5 W

38.0 O

29/17

74/45

2.6/2.6

0/1

30/15

42/32

358/184

1/2

0/3

8.5/5.3

432/229

09/25 @Bron

17-14

-6.5 L

42.5 U

20/23

19/59

1.0/2.6

2/0

27/24

36/39

295/172

0/2

2/1

7.8/4.3

314/231

10/02 @Brow

31-13

0.0 W

39.0 O

29/22

112/84

3.9/3.8

0/0

10/40

21/60

220/332

1/1

0/4

10.5/5.2

332/416

10/09 Stee

17-38

+3.0 L

39.5 O

18/28

66/174

3.7/6.2

0/1

29/24

49/34

240/224

1/1

3/1

4.6/6.4

306/398

10/23 Tex

7-41

-3.0 L

44.5 O

15/47

53/222

3.5/4.7

0/0

15/18

31/23

95/296

2/0

2/0

2.9/12.9

148/518

10/30 @Col

27-10

-8.5 W

43.5 U

30/26

97/158

3.2/6.1

0/0

23/26

33/49

215/241

0/2

1/2

6.3/4.7

312/399

11/06 Beng

17-24

-2.5 L

42.0 U

20/30

78/109

3.9/3.6

1/0

24/22

41/39

250/210

0/0

2/1

5.8/5.3

328/319

Notes:

1. Spreads shown relative to the Titans. 2. Stats read as Offense/Defense or Titans/Opponent.

What can Dr. Bob do for you?

My monthly and season sports analysis subscriptions give you access to my Best Bets (and Strong Opinions in football) at a discounted price and allow you to use my Best Bets release page – which releases each Best Bet simultaneously to everyone, one at a time, on a countdown.

While my success in sports handicapping over the years has led to movement in the point spreads shortly after releasing my Best Bets, most of my clients that use my Best Bets release page have successfully gotten their plays in before the line moves on each Best Bet. Being able to get down before the lines move is a major benefit to purchasing one of my season packages rather than buying my weekly or daily packages, which are only available after all Best Bets are released to subscribers on the Best Bets release page.

Given the long history of success on my Best Bets (73% annual returns), the cost of my sports betting advice is very affordable. In fact, if you’re going to be wagering on sports you probably can’t afford not to use my service since most amateurs, and most other professional handicappers, don’t even win 50% of their bets.

Make sure to read my Sports Betting as an Investment article for more information on how good of an investment Dr. Bob Sports has been and whether you can afford the cost of the service based on your bankroll.

The Origins of Dr. Bob

My illustrious sports handicapping career began at Berkeley when I entered a $2 NFL pool and, after doing a few minutes of simple math, won $100. I was pretty much hooked right out of the gate.

From that point on, I started using my statistics classes as excuses to feed football data through the campus mainframes. In those first three years I won a respectable 63% and decided I'd had enough of school. I quit and became a tout.

The first thing I did was publish a betting guide. After that was released I started advertising a 900 number, writing columns for gambling publications and appearing on radio shows. It wasn't all easy street though, believe me. I was forced to wait tables for a long time on the side. Finally, in 1998, as 900 numbers began to fall out of vogue, I decided to make a desperate move: I equipped my new website to take credit cards. This turned out to be the best bet of my career. Over the next six weeks I made $30,000 "and that was that!"

For most of my career I handicapped teams by looking for situations or "angles" that had a way of predicting future results. If a college football team was favored by seven points or more in a minor bowl after losing their last game, for instance, I would know that the last 36 teams who met that criteria had covered the point spread only eight times. If one of these strong angles applied to a team, I would bet accordingly. This became the basis for my sports betting advice at the time.

However, I suffered a pretty bad losing season in football in 2003, and decided to tweak my method with another layer of rigor. For NFL games, I built a mathematical model to project how many points each team was likely to score in a coming matchup. Eventually, with three years of data and hundreds of hours of tinkering, I built a similar math model for college sports betting.

As well as these methods have worked, they have done nothing to my workload though. I'm constantly looking for ways to improve my win percentage and pass them on to my subscribers. In the months when basketball and football overlap, I tend to work about 18 hours a day nearly every day, sleeping in bursts of no more than four hours. The carpet below my desk chair has been worn bald! My wife has to come in and remind me to stand up periodically so I don't get blood clots in my legs!

Most of my time working is spent making tiny adjustments. If a team loses 12 yards on a running play, I check the game summary to make sure it wasn't a botched punt. I also try to compensate for the strength of every team's opponent. It typically takes me around eight hours just to calculate a rating I invented to measure special teams! Trivial as this seems, all this work makes predictions at least 4% better, and that 4% can have a huge effect when spread out over an entire season. It can sometimes be the difference between finishing with a winning percentage and a losing one.

As always, check out www.DrBobSports.com for picks on every game, every week.

Why the house always wins

Tired of losing his money to the house, a bored millionaire in Las Vegas turns to you and offers you a proposition that you can't refuse. He pulls out a stack of casino chips and declares:

"I've got a 100-sided, evenly weighted die, which I am going to roll. If it comes up 1 through 57 you win, if it comes 58 through 100 I win. We're playing for even money. How much do you want to bet?"

How would you respond? Obviously you accept, but you are uncertain as to exactly how much you should wager - you are a solid favorite, but not an overwhelming one. The answer to this question is much deeper and more important to an investor's bottom line than the average sports bettor ever realizes.

Now let's say that the bored millionaire had one constraint. He tells you you could start with no more than $500 (your bankroll) and if you ran out of money, you couldn't re-load. Also, every roll of the dice costs $100, or essentially 20% of your bankroll on each bet. Would you still take it? Think you could still come away with a profit?

You had better not! You are virtually guaranteed to go bankrupt in this situation. Over the long haul, you will win about 57% - it's a mathematical certainty. But, over the short term, you are not guaranteed a thing. You'll have ups and downs that not even the most sophisticated football analysis computers in the world could predict. On your first twenty rolls you could easily go 2-18! If I forced you to bet 20% of your bankroll, you'd be crazy to do it because I would take your money like taking candy from a baby.

Yet,if you think about it, most bettors routinely do the equivalent of taking this bet every day! Nearly every sports bettor bets too much per game relative to the size of their bankroll. It's insanity, to me, to think that someone would risk half of their "stack" (to borrow a term from poker) on one game of Football. But that's exactly what the house banks on...

THE HOUSE WINS BECAUSE YOU BET TOO MUCH PER GAME.

The average sports better runs out of money before they have a chance to let the odds work for them. They bank on you not knowing this simple rule. It's the main reason why they win time and time again.

It is very tempting to put down a lot on each game, especially when you are winning. Most betters do it for the added excitement it gives you when you watch the event. I'm telling you though, if you want to win money, the only way to do this is to BET BORING. Everyone goes through good and bad streaks in sports handicapping. No one can win EVERY bet. Do yourself a favor though and allow yourself to "stay in the game." Don't miss out on that late-season run of luck because you dropped you whole roll on a "lock" that busted!

To me, knowing that I control the biggest impediment to my winning is empowering! Regardless of whether or not you follow my other sports betting advice, this is the single biggest thing you can do to prevent yourself from going broke. Be disciplined. Bet boring. And win more money.

Maximizing your utility in sports betting

When deciding on your sports betting picks, you should seek a strategy that maximizes their utility. For the uninformed, utility is a measure of relative satisfaction (ie. success or value for your bet). In other words, it is a term referring to the total return that you can expect to receive from your bet.

In all of my sports handicapping strategies, I aim for utility maximization, because depending on a bettor's long-term financial goals, they can have very different marginal values for their money. Betting strategies can be aggressive or conservative, although in reality even my aggressive strategies are somewhat conservative compared with the ridiculous over betting advice that one will often find online.

Sports betting advice can also either be flat (where every unit is the same) or progressive (where units grow or decrease with the bankroll). For both flat and progressive strategies, bet sizing is correlated to confidence (more confidence = larger bets). Yet where other touts' unit sizing is arbitrary, I size all my wagers as described by mathematically optimal ratios for growth as correlated with win percentage confidence. Furthermore, all necessary precautions have been taken to avoid over betting, which can be dangerous to your bank roll and your bottom line.

You can learn more about this and all of my other strategies for sports investing at DrBobSports.com!

Looking To Make A Little Money Doing Sports Betting Handicapping

There are bettors everywhere hoping to earn some cash placing winning bets, but the seasoned ones knows that simply looking at the spreads on games is not enough to make an informed decision. They understand a sure thing is never a sure thing. There are always other variables that must be studied before doing sports handicapping can be effective.

Some of these people will tell you that one of the first things to understand is how well the players play together and work as a unit. Did someone special that most of them relied on recently get traded, or did someone that most dislike get signed to their team?

Another consideration is what their track record has been over the past few games they have played. Are they on a losing streak or on a winning streak? These things have a tendency to go in spurts.

Of course, knowing what your team is doing is important, but it is just as important that you study the team you are betting against. Do they have a tendency to always perform poorly against your team, or do they seem to dominant them every time they play each other?

Everybody has issues and problems in their lives and athletes are no different than the rest of us. There are things that can happen that affect their emotions that will determine how well they play. Maybe they recently lost a loved one and are either inspired or depressed. Perhaps they are suffering from an injury that will let them still play, but not at their best level.

When it comes to sports betting advice it is as much a science as it is in understanding human emotions. If you are going to be good at it you will need to understand the dynamics that goes into creating a spread.

Are you tired of making poor sports betting choices? Would you like your friends and colleagues to value your wager decisions? Then check out Dr. Bob Sports for the best in sports handicapping! The world famous Bob Stoll offers wagering tips on collegiate and pro football as well as the NBA. Free analysis is available on the site, along with essays on sports betting, money management, football analysis, and other useful information.

Week 3 College Recap Recap: Turnovers and Variance

There’s a difference between a bet that loses and a bad bet and this week I had 3 Best Bets that lost that were no doubt good bets. There are weeks when I lose because I happened to be on the wrong side of some games but this week I was on the right side of 6 of my 7 Best Bets and went 3-4 on those Best Bets thanks to random bad luck. In the tough world of sport betting advice, the only thing you can do is chalk this up to variance.

The bad fortune started on Friday night as my Best Bet on Central Florida +3 lost by 7 despite UCF out-gaining BYU 400 yards at 6.3 yards per play to 260 yards at 5.4 yppl. You can lose games when your team dominates when you lose 2 fumbles and the other team loses none, which happened in this game, and when the other team returns a kick for a touchdown. Fumbles are 90% random, so being -2 in fumbles lost is just bad luck and there is no doubt that UCF was the right side in that game and should have won easily as the underdog if not for the random miscues. On Saturday Ohio, a 4 ½ point underdog, averaged 7.1 yppl while Rutgers averaged just 5.3 yppl but the Bobcats fumbled 4 balls away (just 1 lost fumble for Rutgers) and didn’t cover despite dominating from the line of scrimmage by 1.8 yppl. Despite those two undeserved losses I still had a chance at a winning record for the week with my late game on Utah State but the Aggies managed to lose despite out-gaining Colorado State 5.5 yppl to 3.1 yppl. The reason, as you may have guessed, was 4 fumbles lost by Utah State and just 1 turnover by Colorado State. A difference of 2.4 yppl would normally result in a 13 or 14 point win, so it was certainly no guarantee that the Aggies would have covered at -9 ½ without the -3 in fumbles, but it is certainly at least 60% likely that they would have covered had it not been for the randomness of fumbles working against them. This is what can sometimes make sports analysis frustrating.

So, there were 3 games that I had the right side on and lost and the randomness of fumbles was the difference between a great 6-1 day a losing 3-4 day on my Best Bets. Overall, I was a ridiculous -11 in fumble margin on my 7 Best Bets, worth about 44 points (a turnover is worth about 4 points), and my teams still were a combined +11 in point spread differential. I’m not making excuses for losing, as I readily admit when I lose a game in which I had the wrong side in, but fumbles are a reason for losses that in the case of the 3 games mentioned above were undeserved losses in which I certainly had the right side. That’s why there is no such thing as a lock and I will win considerably more games than I lose over the long run when turnovers tend to even out.

In other Best Bets, SMU -21 ½ dominated Memphis 42-0 while out-gaining the Tigers 522 yards at 7.2 yppl to 139 yards at 3.4 yppl and covering easily despite being -3 in turnover margin. Illinois -12 ½ only won by 3 points although they played pretty close to expected with 463 yards at 5.9 yppl while allowing 341 yards at 4.9 yppl but being -1 in turnovers hurt their chances of covering – although I don’t consider that an unlucky loss. Georgia -9 won 27-13 over Ole Miss but the Bulldogs dominated by more than that score, as they out-gained the Rebels 475 yards at 5.8 yppl to 183 yards 3.3 yppl. That game was closer than it should have been because Ole Miss returned a punt for a touchdown and Georgia missed 3 field goals, but at least Georgia covered despite their special teams meltdowns. My Best Bet on Bowling Green +4 ½ was an easy winner, as the Falcons won 37-23 while out-gaining Miami-Ohio 310 yards at 5.0 yppl to 308 yards at just 3.8 yppl. Overall, a very good day of handicapping with my Best Bets being the right side in 6 of 7 games, but good handicapping doesn’t always lead to good result when the randomness of fumbles is -11 against you. I’ll have a great year if I keep betting games like the 7 Best Bets I played this weekend, as it’s highly unlikely that turnovers will be against me in the future like they were this weekend.

I was a frustrating 3-4 on my week 4 Best Bets and 7-11 on a Star Basis and just 1-3 on my Strong Opinions. For the season my Best Bets are 6-7 on 14-19 on a Star Basis and my Strong Opinions are 12-13. Thanks to my bad fortune on turnovers in week 4 I am now down 6.9 Stars at -1.10 odds (instead of being 22-11 on Best Bets and +9.9 Stars had I won the 3 Best Bets I lost due to fumbles) but I'm going to have about 100 Best Bets over the course of the season and I'm going to have a great season if I keep picking games like I picked last weekend. That's pretty likely given my 57% lifetime record on my College Best Bets

Of course for all of your college football analysis needs, you can always visit DrBobSports.com

Marquee Week 3 Matchup: Eagles vs. Giants

Eagles QB Michael Vick left last week's game against the Atlanta Falcons after a vicious hit, in which he was clocked and then fell awkwardly into his own lineman. He struggled to stand and then spit blood as he walked to the sideline. It goes to show the toughness of professional athletes, however, as Vick has been all but cleared to play this weekend. In a fierce rivalry, Vick's Eagles will face Eli Manning and the Giants in a conference matchup.

With Vick healthy and the triple threat of RB LeSean McCoy, DeSean Jackson and Jeremey Maclin, the Eagles will simply be too much to handle. The offensive weapons on the Giants side of the ball pale in comparison, and the Eagles defense is much stronger. The 7.5-point spread should be easily covered by the Eagles as they run out to an early lead.

For more free analysis plus Best Bets for Week 3 of the 2011 NFL season, head over to the ultimate resource for sports handicapping.

New York Jets vs. Dallas Cowboys

Although the Dallas Cowboys have long been known as "America's Team," the sentimental favorite tonight may very well be the Jets as the entire world turns toward New York today to remember the tragic events of September 11, 2001.

After the somber and emotional pregame events conclude at MetLife Stadium in East Rutherford, N.J., though, two of the organizations boasting some of the most bombastic characters in the NFL will take the field.

Rex Ryan's Jets have reached back-to-back AFC Championship Games and are looking to finally reach the Super Bowl. For their part, the 'Boys are just looking to regain contender status. And a large, physically and otherwise, reason they feel confident that they can accomplish that goal is Rex's brother, Rob. The long-haired Ryan brother has come down to Dallas to take over the defense. But can Rob and the revamped Cowboys' defense embarras Jets QB Mark Sanchez any more than those GQ photos?

Follow us for the most recent football analysis and for sports betting advice. Dr. Bob is the expert at sports handicapping.

Read more at http://www.drbobsports.com/.

Dr. Bob's Big 12 Preview

My early season ratings have proven more accurate than the Vegas odds makers and last year I pegged Stanford as the 9th best team heading into the season (they were unranked), Oklahoma State rated 19th (also unranked) and had Texas (#5 ranked in the polls) as my 34th rated team. I've used my early season ratings to give me an edge over Las Vegas over the years and this year I want to share some conference previews with you. I will also have free analysis of almost every College game in the free analysis section at drbobsports.com.

Oklahoma
(projected Big 12 record: 7.5 - 1.5, 1st Place)
Oklahoma's fast break style of football leads to a lot of plays per game and more plays against bad teams usually leads to bigger blowout wins and makes the Sooners appear to be more impressive than they actually are when looking at their average point margin and computer ratings. However, Oklahoma is generally not as impressive when faced with a quality opponent. Last season the Sooners were very lucky to go 5-0 on games decided by 7 points or less and they only out-scored their 6 good opponents (Florida State, Air Force, Missouri, Texas A&M, Oklahoma State, and Nebraska) by an average of 3.2 points, a number that is was skewed by their 30 point win over Florida State. Aside from that early season blowout over the Seminoles, Oklahoma didn't beat a good team by more than 6 points. Oklahoma is the pre-season #1 team in the polls but I'm not convinced. I actually rate the Sooners as being considerably better on both sides of the ball than they were last season, as the rushing attack should finally contribute again after two seasons of bad rushing numbers (just 4.1 yards per rushing play last season against teams that would combine to allow 4.7 yprp to an average team) and quarterback Landry Jones should continue to improve with star receivers Ryan Broyles and Kenny Stills back for another campaign. The defense will be without their top defender, LB Travis Lewis, for the first part of the season due to a broken foot, but I still rate that unit as a bit better overall than they were last season. The Sooners should go from mediocre against the run (5.1 yprp allowed to teams that would combine to average 5.1 yprp) to better than average while the pass defense remains very strong (after giving up a ton of passing yards in week 1 against Utah State the Sooners yielded just 4.9 yards per pass play to quarterbacks that would combine to average 6.5 yppp against an average defense). Oklahoma should also be better in special teams this season after an off year in that department and overall I think the Sooners will be 3 or 4 points better than a year ago (and a bit better later in the season if Lewis returns to his old form after recovering from his injury). However, I thought the Sooners were an overrated team last season and they are not deserving of the #1 ranking (I rate them at #5).

Oklahoma State
(projected Big 12 record: 6.5 - 2.5, 2nd Place)
Oklahoma State was a team that I identified as one of the most underrated teams in the nation heading into last season and the Cowboys went from out-scoring their opponents by 6.7 points in 2009 to out-scoring them by 17.8 points last season. With 9 returning starters on offense, including All-Big 12 QB Brandon Weeden, All-American WR Justin Blackmon, and all 5 offensive linemen, the Cowboys should once again be one of the best offensive teams in the nation after ranking 10th in my ratings last season. The rushing attack may regress a little without RB Kendall Hunter (1548 yards at 5.7 ypr), but the offensive line should be even better and the pass attack will be potent again. What many don't realize is how good Oklahoma State's defense was last season. The Cowboys gave up a mediocre 26.4 points, but they only allowed 5.0 yards per play despite facing teams that would combine to average 5.6 yppl against an average defensive team. Oklahoma State defensive coordinator Bill Young only has 5 returning starters to work with but he had just 4 returning last season and just 5 in his first season running the defense in '09. Both of Young's previous defensive units were good (0.6 yppl better than average last year and 0.7 yppl better than average in 2009) with similar experience and talent and I expect this year's stop unit to be just as good as they were in 2010. Oklahoma State is a legitimate Top 10 team and they have a very good chance to be on top of the Big 12 this season after tying for the division title last year (getting Oklahoma at home to end the season helps).

Texas A&M
(projected Big 12 record: 6.3 - 2.7, 3rd Place)
Texas A&M returns 18 starters from last year's team that won 6 of their last 7 games with Ryan Tannehill at quarterback after veteran Jerrod Johnson struggled early in the season. Tannehill returns along with 9 other offensive starters and the Aggies' attack will be better. However, I don't rate A&M's offense as highly as other top teams in the Big 12 so it will be up to a very good defense to catapult the Aggies into the conference championship hunt. Texas A&M turned their defensive fortunes around last season with the hiring of defensive coordinator Tim DeRuyter, who had good defensive teams with lesser talent at Air Force. DeRuyter's switch to a 3-4 defense worked very well as the Aggies went from being 0.4 yards per play worse than average in 2009 to being 0.9 yppl better than average last season (4.9 yppl allowed to teams that would combine to average 5.8 yppl against an average team). This year's defense loses Butkus Award winner LB Von Miller to the NFL (a 1st round draft pick) but 8 defensive starters do return and my model projects a similarly good stop unit this season despite the loss of Miller. The Aggies are getting a lot of preseason hype this season and they may be a bit overrated, but playing 3 of their 4 toughest conference opponents at home (Oklahoma State, Missouri, and Texas) should keep them in the Big 12 race until their big game at Oklahoma rolls around in early November (and I don't think the Sooners are as good as others do).

Missouri
(projected Big 12 record: 5.8 - 3.2, 4th Place)
Most people think the loss of quarterback Blaine Gabbert, a 1st round NFL draft pick (what a bad move that was by Jacksonville), will lead to Missouri being a worse team this season after going 10-3 in 2010. However, I think Missouri's offense will probably be better without Gabbert, who averaged a modest 6.1 yards per pass play last season (against teams that would combine to allow 5.8 yppp to an average quarterback) after having a very good 2009 season. Missouri passing rating last season with Gabbert was easily the worst since 2005 and I expect the passing numbers to improve with James Franklin taking over behind center. The very good rushing numbers (5.3 yards per rushing play against teams that would combine to allow 4.8 yprp to an average team) should be better as well given Franklin's better running skills (Gabbert ran for 372 yards on 90 runs for just 4.1 yprp) and the return of all 3 of last year's running backs, who combined for 1376 yards at 5.5 ypr and 17 touchdowns. The defense has been 0.3 yppl better than average in each of defensive coordinator Dave Steckel's first two seasons and I expect that unit to be about the same this season -- although with a much better run defense and a worse pass defense. Missouri looks like a better overall team from the line of scrimmage this season but the Tigers probably won't be +11 in turnover margin again and last year's 16.1 points allowed per game was a mirage given how mediocre their defense was overall (their 22.2 yards per point was among the best (i.e. luckiest) in the nation). Missouri is certainly not as good as the top 3 teams in the Big 12, but getting Texas at home should result in a 4th place finish.

Texas
(projected Big 12 record: 5.6 - 3.4, 5th Place)
Texas started last season ranked #5 in the polls but my 2010 preseason ratings pegged Texas as an overrated team that shouldn't even have been in the Top 25. It turns out that the Longhorns were even worse than I thought they'd be and they ended the season rated 46th in my ratings. Texas has too much talent, and an overhauled coaching staff intent on getting the most out of that talent, and the Longhorns will be better. How much better depends on the quarterback play. Quarterback Garrett Gilbert has great tools but he made bad decisions and isn't good at reading defenses. The result was a pass attack that averaged just 5.7 yards per pass play (against teams that would combine to allow 6.2 yppp to an average quarterback) and 17 interceptions in 12 games. The receiving corps also hasn't lived up to expectations and that group has been thinned by graduation (2 of the top 3 in receiving yards are gone) and the decision of two projected veteran wideouts (Malcolm Williams and Marquise Goodwin) to take this season off. Gilbert reportedly has been horrible in practice and in the first scrimmage and he may lose his job to talented freshman David Ash, who has looked good in August. The running backs and offensive line are nothing special and I project the offense to be worse than average again (0.4 yards per play worse than average last season) if Gilbert is the starting quarterback. The Longhorns' defense was good last season, allowing 4.8 yppl to teams that would combine to average 5.5 yppl against an average defense) and that unit looks to be about the same this season with a better run defense and a worse pass defense. There is, of course, plenty of upside potential defensively. New defensive coordinator Manny Diaz greatly improved Mississippi State's defense last season in his only year on that staff and he's got great talent to work with on this team. Texas should also be better in special teams and an attitude change will keep the Longhorns from losing to mediocre teams like they did last season (UCLA, Iowa State, Baylor and Kansas State all beat the Horns in 2010). Texas is going to better and they could be very good if Gilbert loses his job and the defense plays up to their potential.

Baylor
(projected Big 12 record: 3.9 - 5.1, 6th Place)
Baylor had my 11th ranked offense last season and should be in the Top-15 or 20 this season despite losing top rusher Jay Finley and LT Danny Watkins, a 1st round NFL draft pick. RB Finley (1218 yards at 6.2 ypr) is gone but Jarred Salubi has racked up 513 yards last 2 seasons at 6.8 ypr and Terrance Ganaway ran for 295 at 6.4 ypr last season. Robert Griffin III came back last season after missing most of the 2009 season and he continued to be impressive both throwing the ball (7.2 yards per pass play against FBS teams that would allow 6.0 yppp to an average quarterback) and running it (755 yards on 129 runs ( for 5.9 yards per rushing play). Griffin has also thown just 11 career interceptions on 790 pass attempts and he may be the most talented quarterback in the Big 12 (Landry Jones and Brandon Weeden put up big numbers but they also have better supporting casts). Losing big play WR Josh Gordon, who quit the team after being suspended, will hurt, as his 17.0 yards per catch was by far the best on the team last season, and the offense probably won't be quite as good as it was last season (6.6 yards per play against teams that would combine to allow 5.3 yppl to an average team) but the Bears' attack will still be very good. Defense is the issue for Baylor, as that unit surrendered 32.8 points at 6.1 yppl last season (against teams that would average 5.4 yppl against an average defense). New defensive coordinator Phil Bennett should improve that unit but the Bears still figure to have a worse than average defense (on a national scale) and certainly one of the Big 12's worst stop units. If Bennett improves the defense more than expected then Baylor could pull a few surprises and have a winning conference record for the first time in memory, but I'll call for them to fall a game short of that accomplishment.

Texas Tech
(projected Big 12 record: 3.3 - 5.7, 7th Place)
Texas Tech was 8-5 last season but the Red Raiders were a pretty average team (out-gained by 14 yards per game) that was lucky to win all 4 games that were decided by 7 points or less. The Red Raiders look like a better team this season with an improved ground attack (all 5 offensive linemen return and the talent at running back is good) and what should be a better pass attack after last season's mediocre numbers (5.9 yards per pass play against teams that would allow 6.0 yppp to an average team). The Red Raiders' biggest improvement should come on the defensive side of the ball, as former TCU assistant Chad Glasgow was brought in to install the Horned Frogs' successful 4-2-5 scheme after last year's Tech stop unit gave up 5.9 yards per play to teams that would combine to average 5.6 yppl against an average team. I expect improvement but the talent level on defense is pretty average and I'm not sure the new scheme can hide that fact. Overall, Texas Tech should be a better team in year 2 of the Tommy Tuberville era but they probably won't win 8 games again unless they continue to win every close contest.

Kansas State
(projected Big 12 record: 2.8 - 6.2, 8th Place)
Kansas State managed to go 6-6 and out-score their FBS opponents 32.4 points to 29.5 points last season despite being out-gained 370 yards at 5.7 yards per play to 450 yards at 6.7 yppl allowed. That Bill Snyder is a heck of a coach to pull off that sort of trick but Kansas State isn't likely to make it back to a bowl game this season despite being a better team. The offense probably won't be quite as good as it was last season unless new quarterback Collin Klein becomes a proven passer. Klein has only 18 pass attempts on his resume while running the ball 69 times for 465 yards. Klein reportedly has looked good in camp and his running ability will help offset the loss of RB Daniel Thomas, who ran for 1585 yards at 5.3 ypr last season. Klein will probably do a decent job throwing the football and the rushing attack should be good, so the Wildcats' offense should be good again (I rate them slightly worse than last season). Obviously the problem is on the defensive side of the ball, but that unit should be much better with experienced defensive backs and the addition of Miami transfer LB Arthur Brown, who figures to make a huge impact in the middle of the field. Kansas State should be considerably better defensively this season, but they will still probably be worse than average on the stop side of the ball and just a point or two better than average overall this season. That's not likely to be enough to get them to the .500 mark this season unless Snyder has more magic tricks up his sleeve.

Iowa State
(projected Big 12 record: 2.3 - 6.7, 9th Place)
Iowa State offense was bad last season (4.8 yards per play against teams that would combine to allow 5.3 yppl to an average team) and lose the Cyclones will be without last year's top back Alexander Robinson (946 yards at 4.7 ypr) and 3 year starting QB Austen Arnaud. The rushing attack should be decent even without Robinson, as the other backs actually had a slightly high ypr and new lead back Shontrelle Johnson ran for 218 yards at 6.2 ypr as a freshman. Arnaud had his worst season last year (5.2 yards per pass play against teams that would allow 6.0 yppp to an average QB) and backup Jerome Tiller continued his horrible career performance when Arnaud was injured. Tiller has completed only 52% of his 155 career passes while getting sacked way too often and averaging a pathetic 3.7 yppp on 172 pass plays (against teams that would allow 5.8 yppp to an average QB). Tiller runs pretty well (406 yards on 69 runs for 5.9 yprp) but that's not enough to make up for his horrendous passing numbers. Junior Steele Jantz should get the starting gig and I expect his numbers to suffer, despite his cool name, thanks to a poor receiving corps with no big play threats. Jantz probably will be a bit worse than Arnaud was last season but the Cyclones overall pass rating will be slightly higher than last year's team numbers, which were dragged down by Tiller. The offense should be just as bad as it was last season and it will be worse if Tiller gets under center. The Iowa State defense has improved significantly in each of head coach Paul Rhoads' first two seasons, going from 1.1 yards per play worse than average in 2008 to 0.6 yppl worse than average in Rhoads' first season to just 0.1 yppl worse than average last season. The Cyclones have 7 returning defensive starters, including 5 of last year's top 6 tacklers, and I rate the ISU defense at 0.2 yppl better than average heading into this season with potential to be better. Iowa State does have better than average special teams and overall the Cyclones look like an average to slightly worse than average FBS team, which isn't nearly good enough to compete in the Big 12 most weeks.

Kansas
(projected Big 12 record: 1.0 - 8.0, 10th Place)
Turner Gill turned around the dormant program at Buffalo, but Kansas was horrible in Gill's first season in Lawrence. The Jayhawks started the Gill era with a 3-6 home loss to Division 1AA North Dakota State and they were outscored by an average of 17.1 points to 34.4 points for the season. The Kansas offense was horrible last season (4.3 yards per play against FBS teams that would combine to allow 5.6 yppl to an average team) but the pass attack should improve in Gill's 2nd season. Gill's first team at Buffalo in 2006 was 1.3 yards per play worse than average, 1.5 yards per pass play worse than average and was sacked 9.6% of time on pass plays. Last year the offense was 1.3 yppl worse than average the pass attack was 1.9 yppp worse than average and the quarterbacks were sacked 9.5% of the time (6.5% is average). Gill's 2nd season at Buffalo showed a major improvement of 0.7 yppl and 0.9 yppp as the pass protection went from horrible to average. With 5 veteran linemen the Jayhawks' pass protection should improve and I expect the offense to go from 1.3 yppl worse than average to 0.6 yppl worse than average, with the potential to be better if strong armed freshman QB Brock Berglund wins the job and lives up to his potential. The defense should also improve with 8 starters returning along with LB Huldon Tharp, who was a 1st Team Frosh All-American in 2009 but missed last season due to injury. Kansas was 0.8 yppl worse than average last season (6.5 yppl allowed to teams that would average 5.7 yppl against an average team), but the Jayhawks should be about 0.4 yppl worse than average this season defensively and could be better than that. Kansas is still likely to be the worst team in the Big 12, but they'll be considerably better than last season's horrible squad.

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