Monday, January 31, 2011
Isn't gambling risky?
I don't believe that the term 'gambling' applies to what I do. I sell information to subscribers, with which they can take positive expectation positions in uncertain markets. With correct financial optimization and bankroll management, long term risks are nominal compared to the risks of investing in other, more conventional markets. Just as a single stock may go up or down in a day, any one team may win or lose a given game. But as long as the investor maintains a long-term perspective, understands variance, and doesn't over-extend themselves or bet more than they can easily handle, risk can be highly mitigated, and they can earn a very attractive risk adjusted return.
Monday, January 24, 2011
What is a Point spread?
Before I delve into rigorous explanations of how a bettor can gain an advantage against the point spread, it is important to understand what the spread actually represents. Point spreads were invented to keep bettors interested in games between teams of different talent levels - if a perennial powerhouse like Florida plays a mid level team such as Southern Miss, you'll find very few people willing to bet on which team will win the game since Florida would be such a prohibitive favorite. However, most are willing to bet on whether Florida will 'cover the point spread' and win by a certain number of points. If the point spread is 21.5, then Florida must win by 22 or more points for their side of the bet to cover, while USM must either win outright or lose by 21 or less to cover their side. Point spreads are designed so that the probability of each outcome is roughly equal, and are generally set so as to approximate the median score differential between the two teams.
However, skewed public perception, results-oriented analysis, and unsound metrics result in point spreads that are often slightly biased one way or another. While the casual bettor does not possess the capacity to exploit these advantages, I have used mathematical models, situational analysis, significant trends and quantitative player analysis that are far more complex and accurate than anything else on the market to gain an advantage, which is why I have won 54 to 59% of my Best Bets (depending on the sport) over the last 22 years.
How are the lines set?
While the odds makers do to try approximate the median margin of victory between two teams, they also try to reduce their exposure to risk by setting lines such that the public money will fall evenly on both sides of a game, so that they can offset the bets against each other and earn a profit on the juice (cut of winnings taken by the house, explained below) without exposing themselves to large potential losses. Thus, odds makers are often in the business of gauging public perception rather than team performance, and therefore the betting public actually sets the line. If Georgia is 4 points better than Georgia Tech according to my advanced metrics and analysis, but the aggregate public perception is that Georgia is 7 points better than Georgia Tech, then the posted point spread is likely to be closer to 6.5 or 7 points (public perception) than it will be to 4 points (the realistic difference between the teams). This makes my job as a professional handicapper much less daunting; not only can I exploit lines where the odds makers leave an edge, but I can also exploit the uniformed opinions of the general betting public.
However, skewed public perception, results-oriented analysis, and unsound metrics result in point spreads that are often slightly biased one way or another. While the casual bettor does not possess the capacity to exploit these advantages, I have used mathematical models, situational analysis, significant trends and quantitative player analysis that are far more complex and accurate than anything else on the market to gain an advantage, which is why I have won 54 to 59% of my Best Bets (depending on the sport) over the last 22 years.
How are the lines set?
While the odds makers do to try approximate the median margin of victory between two teams, they also try to reduce their exposure to risk by setting lines such that the public money will fall evenly on both sides of a game, so that they can offset the bets against each other and earn a profit on the juice (cut of winnings taken by the house, explained below) without exposing themselves to large potential losses. Thus, odds makers are often in the business of gauging public perception rather than team performance, and therefore the betting public actually sets the line. If Georgia is 4 points better than Georgia Tech according to my advanced metrics and analysis, but the aggregate public perception is that Georgia is 7 points better than Georgia Tech, then the posted point spread is likely to be closer to 6.5 or 7 points (public perception) than it will be to 4 points (the realistic difference between the teams). This makes my job as a professional handicapper much less daunting; not only can I exploit lines where the odds makers leave an edge, but I can also exploit the uniformed opinions of the general betting public.
Tuesday, January 18, 2011
NBA Basketball Season Update
I thought I'd run down the week by week records for the season, based on Stars won and Stars lost with the profit/loss being based on -1.10 odds. 
week 1 5-3 on Stars for +1.7 Stars
week 2 5-0 for +5.0 Stars, Season 10-3 for +6.7 Stars
week 3 2-5 for -3.5 Stars, Season 12-8 for +3.2 Stars
week 4 26-13 for +11.7 Stars, Season 38-21 for +14.9 Stars
week 5 8-8 for -0.8 Stars, Season 46-29 for +14.1 Stars
week 6 16-23 for -9.3 Stars, Season 62-52 for +4.8 Stars
week 7 14-6 for +7.4 Stars, Season 76-58 for +12.2 Stars
week 8 18-2-2 for +15.8 Stars, Season 94-60-2 for +28.0 Stars
week 9 12-9 for +2.1 Stars, Season 106-69-2 for +30.1 Stars
week 10 8-11 for -4.1 Stars, Season 114-80-2 for +26.0 Stars
week 11 18-2 for +15.8 Stars, Season 132-82-2 for +41.8 Stars
week 12 17-25 for -10.5 Stars, Season 149-107-2 for +31.3 Stars
As you can see, the week's following my 3 weeks when I was under 50% were 26-13, 14-6, and 18-2, so don't overreact to last week's 17-25 star record. I do the same analysis when I'm winning as I do when I'm losing. The difference between a winning week and a losing week is nothing more than random variance and I'm likely to be profitable going forward regardless of my season record, or how I did last week. This season has actually been pretty consistent, as my worst week of -10.5 Stars. Last season I had 3 weeks worse than that and still ended with a good profit for the season.
week 1 5-3 on Stars for +1.7 Stars
week 2 5-0 for +5.0 Stars, Season 10-3 for +6.7 Stars
week 3 2-5 for -3.5 Stars, Season 12-8 for +3.2 Stars
week 4 26-13 for +11.7 Stars, Season 38-21 for +14.9 Stars
week 5 8-8 for -0.8 Stars, Season 46-29 for +14.1 Stars
week 6 16-23 for -9.3 Stars, Season 62-52 for +4.8 Stars
week 7 14-6 for +7.4 Stars, Season 76-58 for +12.2 Stars
week 8 18-2-2 for +15.8 Stars, Season 94-60-2 for +28.0 Stars
week 9 12-9 for +2.1 Stars, Season 106-69-2 for +30.1 Stars
week 10 8-11 for -4.1 Stars, Season 114-80-2 for +26.0 Stars
week 11 18-2 for +15.8 Stars, Season 132-82-2 for +41.8 Stars
week 12 17-25 for -10.5 Stars, Season 149-107-2 for +31.3 Stars
As you can see, the week's following my 3 weeks when I was under 50% were 26-13, 14-6, and 18-2, so don't overreact to last week's 17-25 star record. I do the same analysis when I'm winning as I do when I'm losing. The difference between a winning week and a losing week is nothing more than random variance and I'm likely to be profitable going forward regardless of my season record, or how I did last week. This season has actually been pretty consistent, as my worst week of -10.5 Stars. Last season I had 3 weeks worse than that and still ended with a good profit for the season.
Monday, January 17, 2011
Money management
Money Management is as critical to a sports investor as picking winners. I have devoted many hours of careful analysis and math to optimal money management systems, which I have painstakingly outlined in my Money Management articles. Sports betting is more high risk (higher volatility and standard deviation of return) than stocks, and also much more high return. When compared with stocks or bonds or real estate, it also has a much higher risk adjusted return (Sharpe), and is a more attractive overall investment. (My investments have a Sharpe Ratio of 0.715 compared to the S&P 500's SR of 0.406)
My Money Management articles outline how to adjust your bet sizing based on your goals (expected return vs. probability of positive returns), your investment length (one season or many), your growth preference (flat or compounding), your risk tolerance (high or low) and the proportion of your overall bankroll which is made up by sports betting.
In general, I would recommend that beginners wager 1.5% of their initial bankroll per star in football. I have won 56% of my Football Best Bets over 22 years, and while I continue to improve my methods I will use 56% as my expected win percentage. I anticipate approximately 160 Best Bets, which should add up to around 400 stars. For basketball, I would recommend about 1.1% of initial bankroll per star. Over 22 years, I have won 54.6% of games, and I will conservatively set my win expectation at 54% going forward into 2009, and I expect to bet approximately 400 Best Bets and 1,050 stars. It is always better to set conservative expectations to avoid over betting. For subscribers who purchase the Combo package, I recommend 1.4% per star in football and 1.0% per star in basketball, as overall variance is greater (although variance as a percentage of total wagers is lower).
Factoring in the Cost of my Service
The cost of my football service is $1,295, so you must factor in that cost when doing the above analysis. If my expected win percentage is 56% (my long term percentage) on 400 Stars per season, then the average profit would be +30.4 Stars per season. If you had $10,000 that you invested in a football season and $1,295 went to pay for my service, then you would have $8,705 left for wagering. At 1.5% per star, you have an expected profit of 45.6%, and with a bankroll of $8,705 that's an expected net of +$2,675 after factoring in the cost of my service.
Many subscribers save money by buying my Football-Basketball Combo package each year for $2495 (rather than $1295 for football and $1695 for basketball, or $2990). If you have $12,000 to invest for the year and decide to pay for my Football-Basketball Combo package for $2495 then you have $9,505 remaining for your working bankroll. When using the Combo package, I recommend 1.4% of your bankroll per Star for football and 1.0% per Star for basketball if you plan on using one bankroll to cover both seasons. I expect about 30.4 Stars of profit per year in football and about 35.7 Stars of profit per year in basketball, which translates into an expected profit of +42.56% of your bankroll in football (30.4 stars times 1.4% per star) and an expected profit of +35.7% of your bankroll in basketball (35.7 stars times 1.0% per star). That's a total expected profit of +78.26% of your bankroll, which is about $7,438 in the case of a $12,000 total investment ($9,505 * .7826). After taking out the cost of the service ($2495), you still would have $4,943 total profit, which is an astounding 41.2% expected return on 56% winners on my Football Best Bets and 54% winners on my Basketball Best Bets. Of course, there are going to be years better than that and some years worse than that, but it doesn't get much better than an average return of 41.2%.
My Money Management articles outline how to adjust your bet sizing based on your goals (expected return vs. probability of positive returns), your investment length (one season or many), your growth preference (flat or compounding), your risk tolerance (high or low) and the proportion of your overall bankroll which is made up by sports betting.
In general, I would recommend that beginners wager 1.5% of their initial bankroll per star in football. I have won 56% of my Football Best Bets over 22 years, and while I continue to improve my methods I will use 56% as my expected win percentage. I anticipate approximately 160 Best Bets, which should add up to around 400 stars. For basketball, I would recommend about 1.1% of initial bankroll per star. Over 22 years, I have won 54.6% of games, and I will conservatively set my win expectation at 54% going forward into 2009, and I expect to bet approximately 400 Best Bets and 1,050 stars. It is always better to set conservative expectations to avoid over betting. For subscribers who purchase the Combo package, I recommend 1.4% per star in football and 1.0% per star in basketball, as overall variance is greater (although variance as a percentage of total wagers is lower).
Factoring in the Cost of my Service
The cost of my football service is $1,295, so you must factor in that cost when doing the above analysis. If my expected win percentage is 56% (my long term percentage) on 400 Stars per season, then the average profit would be +30.4 Stars per season. If you had $10,000 that you invested in a football season and $1,295 went to pay for my service, then you would have $8,705 left for wagering. At 1.5% per star, you have an expected profit of 45.6%, and with a bankroll of $8,705 that's an expected net of +$2,675 after factoring in the cost of my service.
Many subscribers save money by buying my Football-Basketball Combo package each year for $2495 (rather than $1295 for football and $1695 for basketball, or $2990). If you have $12,000 to invest for the year and decide to pay for my Football-Basketball Combo package for $2495 then you have $9,505 remaining for your working bankroll. When using the Combo package, I recommend 1.4% of your bankroll per Star for football and 1.0% per Star for basketball if you plan on using one bankroll to cover both seasons. I expect about 30.4 Stars of profit per year in football and about 35.7 Stars of profit per year in basketball, which translates into an expected profit of +42.56% of your bankroll in football (30.4 stars times 1.4% per star) and an expected profit of +35.7% of your bankroll in basketball (35.7 stars times 1.0% per star). That's a total expected profit of +78.26% of your bankroll, which is about $7,438 in the case of a $12,000 total investment ($9,505 * .7826). After taking out the cost of the service ($2495), you still would have $4,943 total profit, which is an astounding 41.2% expected return on 56% winners on my Football Best Bets and 54% winners on my Basketball Best Bets. Of course, there are going to be years better than that and some years worse than that, but it doesn't get much better than an average return of 41.2%.
Monday, January 10, 2011
Juice, and the power of 56%
Even though most sports bettors are losers in their own right (as a whole, bettors actually win an average of only 48% of their bets - less than they would expect to win if they just flipped a coin for every game), their losses are compounded by the fact that the house takes a cut of winnings, also known as the 'juice' or 'vig.' Most sports books charge a 10% commission on wins, which means that a bettor must actually win 52.4% of his games just to break even. (Wagering $100 per game, a bettor loses $100 with a loss and wins $90.91 with a win, so he must go 11-10 (11/21 = 52.38%) to break even). Recently, some online books have started to offer lower juice, betting exchanges and deposit bonuses, which reduce the house edge.
In order to beat the juice and win in sports betting, a bettor must employ a disciplined approach in their analysis of each game using methods that have proven to be successful in the long run. I discuss my math models and analytical metrics in my Handicapping Methods essay, but you must realize that only the best and most knowledgeable handicappers can win 55% of their games. In their 2007 two page article about my handicapping success, the Wall Street Journal wrote, "...fewer than 100 people can sustain (win rates of 55%) over time. Most of them belong to professional betting syndicates that hire teams of statisticians, wager millions every week and keep their operations secret." Even fewer bettors can hit 56-57% over a 20 year period as I have.
Touts often claim to be able to hit 60% or higher, but as I explain in my essay on Bayesian Probability, anyone who tells you that their long term expected winning percentage is higher than 60% is deluding themselves. For a bettor to claim a greater than 60% long term expected win percentage, that would be mean that Vegas would have to consistently release lines with egregious errors, and that simply just does not happen often enough for claims of greater than 60% long term expected win percentages to be caused anything other than blind, short-term luck.
I often hear amateur gamblers erroneously claim that winning 56% of games isn't even enough to beat juice. As demonstrated above, a bettor only needs to win 52.4% to break even, and a 56% bettor will be profitable in the long run if they pursue an optimal money management strategy.
Of course, as in any game of chance, there is variability in the actual results and just because you have won 56% in the past and expect to win 56% in the future doesn't mean that you're going to win 56% this upcoming season. There is variance in sports betting, as there is in most investments, and I calculate the standard deviation to figure out how much of my bankroll I can safely wager on each game during the season to accommodate potential negative swings while having very little chance of exhausting my bankroll. I have extensively quantified the variance that exists in sports betting, and use mathematical formulas to dictate the exact optimal amount to invest so as to maximize the ratio of profits to variance.
A football season with 56% winners (my long term percentage) on 400 units or 'stars' would on average yield +30.04 stars ( (400*.56) - (400*.44)*1.1 ). Even using a very conservative 1.5% per star (in the past, I have recommended 2%), that's an expected return of 45.06%.
A basketball season with 54% winners (my long term percentage) on 1,050 units or 'stars' would on average yield +35.7 stars ( (1050*.54) - (1050*.46)*1.1 ). Using a conservative 1.1% per star (in the past, I have recommended 1.5%), that's an expected return of 39.27%. So, despite a lower overall winning percentage, I expect a season's worth of basketball wagers to be almost as profitable as a season of football in the future. Over the last ten years, my basketball wagers have actually been more profitable than football, but I have done a lot of analysis this summer and I expect my football wagers to be even better next year than they have been in the past.
In order to beat the juice and win in sports betting, a bettor must employ a disciplined approach in their analysis of each game using methods that have proven to be successful in the long run. I discuss my math models and analytical metrics in my Handicapping Methods essay, but you must realize that only the best and most knowledgeable handicappers can win 55% of their games. In their 2007 two page article about my handicapping success, the Wall Street Journal wrote, "...fewer than 100 people can sustain (win rates of 55%) over time. Most of them belong to professional betting syndicates that hire teams of statisticians, wager millions every week and keep their operations secret." Even fewer bettors can hit 56-57% over a 20 year period as I have.
Touts often claim to be able to hit 60% or higher, but as I explain in my essay on Bayesian Probability, anyone who tells you that their long term expected winning percentage is higher than 60% is deluding themselves. For a bettor to claim a greater than 60% long term expected win percentage, that would be mean that Vegas would have to consistently release lines with egregious errors, and that simply just does not happen often enough for claims of greater than 60% long term expected win percentages to be caused anything other than blind, short-term luck.
I often hear amateur gamblers erroneously claim that winning 56% of games isn't even enough to beat juice. As demonstrated above, a bettor only needs to win 52.4% to break even, and a 56% bettor will be profitable in the long run if they pursue an optimal money management strategy.
Of course, as in any game of chance, there is variability in the actual results and just because you have won 56% in the past and expect to win 56% in the future doesn't mean that you're going to win 56% this upcoming season. There is variance in sports betting, as there is in most investments, and I calculate the standard deviation to figure out how much of my bankroll I can safely wager on each game during the season to accommodate potential negative swings while having very little chance of exhausting my bankroll. I have extensively quantified the variance that exists in sports betting, and use mathematical formulas to dictate the exact optimal amount to invest so as to maximize the ratio of profits to variance.
A football season with 56% winners (my long term percentage) on 400 units or 'stars' would on average yield +30.04 stars ( (400*.56) - (400*.44)*1.1 ). Even using a very conservative 1.5% per star (in the past, I have recommended 2%), that's an expected return of 45.06%.
A basketball season with 54% winners (my long term percentage) on 1,050 units or 'stars' would on average yield +35.7 stars ( (1050*.54) - (1050*.46)*1.1 ). Using a conservative 1.1% per star (in the past, I have recommended 1.5%), that's an expected return of 39.27%. So, despite a lower overall winning percentage, I expect a season's worth of basketball wagers to be almost as profitable as a season of football in the future. Over the last ten years, my basketball wagers have actually been more profitable than football, but I have done a lot of analysis this summer and I expect my football wagers to be even better next year than they have been in the past.
Friday, January 7, 2011
Monday, January 3, 2011
The power of compounding return
Some investors choose to start each year by investing a fixed percentage of their overall holdings (maybe $10,000, or 5% of their liquid assets) and take a profit every year. This conservative approach has yielded incredible results - in the last ten years, I have had an average return of 73%. My best year was +211%, and my worst year was -77%. If you carefully invest year after year without being intimidated by short term variance, then you will eventually see fantastic returns.
Other investors choose much longer periods of investment - they lock in their money for five, or even ten years. Rather than bet a fixed percentage of their initial bankroll per star, their bet sizes fluctuate each week. Since my investments have a long-term upward trend, these investors earn a compounding return on their money. The swings get larger as the bankroll grows, but the trend is always upward. An investor who invested $10,000 in my picks in 1999 and pursued an optimal growth strategy would have seen their portfolio value swell to $349,112 by the end of the 2008-2009 seasons. This concept of optimal growth is discussed in much greater detail in my Money Management Articles.
Other investors choose much longer periods of investment - they lock in their money for five, or even ten years. Rather than bet a fixed percentage of their initial bankroll per star, their bet sizes fluctuate each week. Since my investments have a long-term upward trend, these investors earn a compounding return on their money. The swings get larger as the bankroll grows, but the trend is always upward. An investor who invested $10,000 in my picks in 1999 and pursued an optimal growth strategy would have seen their portfolio value swell to $349,112 by the end of the 2008-2009 seasons. This concept of optimal growth is discussed in much greater detail in my Money Management Articles.
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