Betting With An Edge
The house edge is the casino’s average profit on any bet.In craps, the house edge on the Pass Line bet is 1.41%. That means that for every$5 wager on the Pass Line, the casino will keep seven cents as profit on average.($5 x 1.41% = $0.07) This doesn’t mean on a single wager the casino will keep $0.07and pay you back $4.93. If you can confirm that you have an edge it is a big deal. It means that you can look ahead confidently to winning money on a regular basis. If you don’t have an edge then you will know that a new tactic is needed. Or you will eventually lose.
The fundamental challenge for serious bettors is to gain an advantage over whoever is laying their bet, whether that is a bookmaker, exchange or casino. In betting parlance this is called ‘getting an edge’ and if you want to be a profitable bettor, you need to understand what this means. This article explains how to get an edge in betting.
Margins Between Success & Failure
There is a well-worn cliché in sports journalism – the margin between success and failure is slim. In betting, the margin between making a profit or losing money is actually variable; it simply depends on which bookmaker you choose to bet with.
And while margins are fundamental to making money, a large percentage of bettors are oblivious to their impact. Margins are discussed at great length at Pinnacle, because it offers the lowest margins and therefore gives bettors a better chance to win.
This is obvious by looking at the different margins on long-term break-even rates:
Knowledge is Power
Once you understand margins, you have identified an advantage that a bookmaker holds over you. Now you need to find ways to counteract that edge. One way you can get a jump over a bookie is finding markets where you know more than the oddsmaker.
There is no magic bullet here. Bookmakers are experienced and have vast data at their disposal - but they have their weaknesses. Niche markets are a great example. Bookmakers often offer minor leagues, or novelty markets as a marketing ploy to differentiate from competitors, to boost acquisition or to gain exposure in new target territories. Not because they are experts in those areas.
Bookmakers are experienced and have vast data at their disposal - but they have their weaknesses.
They are not in a position to understand the dynamics of third division Russian women’s volleyball, but there is no reason why you cannot make yourself an expert in those areas where bookmakers’ knowledge is potentially weak.
The Olympics is an excellent example of this, with oddsmakers tackling sports with which they have little experience or useful data. Betting limits will be low, but this in itself should be taken as a potential indicator of the book’s lack of confidence.
Keeping Your Ear to the Ground
Knowledge is critical, but alone it doesn’t guarantee success. If what you’ve learnt is already common knowledge it will already be built into the odds. Real value comes from information as close to the source as possible – or in horse racing, “straight from the horse’s mouth”.
Twitter has opened up new opportunities here, speeding up the dissemination of information. However, it’s equally accelerated the time it takes information to become common knowledge. It has also increased the amount of rumour, speculation and noise.
Good examples of getting an edge through timely information can be identifying reliable Twitter feeds that might be leaking team formations, weather, pitch conditions, injury news or club finances. See below for examples:
Example A: On October 6th 2012 Kettering was forced to field 10 men in a Southern Premier League home game against Bashley. Players had issued an ultimatum on unpaid wages that ran out prior to the game. The word got out as Bashley’s odds continually contracted. Kettering lost 7-0; their previous four home games had resulted in two draws and two single goal defeats.
Example B:The Mascot Grand National is an annual hurdle race in England between sporting mascots, with odds offered by many bookmakers. The emphasis is certainly on fun, so entry criteria are loose, but big money has been made with numerous big gambles being landed. In 2001, Freddie the Fox won but later disqualified after he was found to be an Olympic hurdler; while in 2005 a huge gamble was landed on the Scoop 6 Squirrel representing the Sun newspaper. The impact of ‘ringers’ on the Mascot Grand National caused the race to be boycott in 2011.
Betting outside the Box
Given the chance, would you rather bet on the outcome of an event that was known – just not to many people – or unknown? The former is clearly more appealing.
Any kind of award falls into this category. So you have to find ways of seeing inside the winner’s envelope before the award is announced. Information leaks, sometimes inadvertently, sometimes non-verbally.
Given the chance, would you rather bet on the outcome of an event that was known – just not to many people – or unknown? The former is clearly more appealing.
Betting With An Edge Mike Maloney
Example C:The Church of England’s recent appointment of the Archbishop of Canterbury provides an excellent example of how supposedly classified information can prove porous. Even a revered establishment like the C of E wasn’t able to stop word getting out to the extent that market was closed early.
Sometimes the result isn’t known, but is entirely predictable because of motivation. Think of reality TV Shows, where talent is not the only consideration. A propensity for controversy is equally important so look beyond the narrow competition parameters and research things like programme ratings and channel competition.
Cross-correlations
Finally, understanding cross-correlations or dependencies is vital for betting. If you correlate poor weather with low scoring in rugby, and study long term forecasting, you may anticipate bad weather and focus on betting totals going under.
Betting With An Edge Pdf
You can go further and perm your totals bets for potentially lucrative accumulators. It’s important to remember, however, that when looking at dependencies, correlation doesn’t imply causality.