Wednesday, November 23, 2011

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

Thursday, November 17, 2011

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.

Tuesday, November 15, 2011

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.

Tuesday, November 8, 2011

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.