Golf betting strategy: Success = talent + luck

Golf betting strategy - The rub of the green

Luck plays some part in how all individual sporting events pan out, but more so in golf than in almost any other - some might argue that it is baseball betting that is influenced by luck the most. Famous hustler and gambler Titanic Thompson summed it up neatly: "In poker, pool and dice you've got to worry about your game and the other man's. In golf there is also the weather". Of course, the weather is just one of many factors that make golf a hard sport to predict; getting the rub of the green can have a huge impact on an outcome in golf betting.

It's a general rule in sports that the greater the number of interacting elements (like the weather in soccer betting) the harder it is to predict the outcome. Once bettors know how to bet on golf, they should consider the following characteristics:

Given such a large number of random variables that can impact a golfer'€s score, it is no wonder that golf betting appears to offer much higher odds - something that is highlighted by the current US Masters betting odds.

In poker, pool and dice you've got to worry about your game and the other man's. In golf there is also the weather. Famous Gambler, Titanic Thompson.

Despite a small selection of players dominating the overall PGA and European Tour standings, 28 of the last 43 major winners going back to the 2009 Masters have been unique. To further illustrate this point, see the following list of big outsiders that won majors in the last decade and the particular circumstances in which they were won in:

Golf betting - Analysing both talent and luck

Any successful golf betting strategy will be able to analyse a player's talent and ability, but also understand how luck can influence results. A bettor's view shouldn't differ that of a player, something that can be summarised by:

If you accept the relevance of this to the world of golf, bettors must also take luck into account alongside handicap. But how do you quantify the element of luck?

One method would be to understand the importance of regression. For example, if you were to wait for completed Round 1 scores of any given major, you might infer from players scoring below par that their talent on the day -€ “judged on that narrow criteria" -€ was above the average participant. Using our formula for success, we should also appreciate that good fortune played some part.

By the same token, those players who shot over par would be judged to have performed below the average, but poor luck could also have contributed. This can produce these broad statements:

The aim of golf betting is to make accurate predictions. This means we need to use this analysis to predict what might happen in Round 2. If you assume that performances remain constant (and this is a broad assumption), luck becomes the variable element, which you have no way of exactly measuring other than to say that with a best guess that it would be very unlikely to be the same as on Round 1.

You can elaborate to say that those players that played above average in Round 1 would play equally well in Round 2, but that the luck they enjoyed wouldn'€t hold so their scores wouldn'€t be as impressive.

The inverse would be true of those under-performers from the first round, whose scores would (on average) marginally improve, as they would not experience the same degree of bad luck.

Why does a large number of the stars that appear on the cover of Sports Illustrated go on to suffer a decline in their fortunes? The statistical answer is regression.

The interesting observation for bettors is that regression suggests that scores of players for Round 2 are more likely to be closer to the average score than the evidence on which it is based (Round 1 for that player). This moderation is the influence of regression to the mean, which we should expect to be more noticeable with extreme scores.

It is important to note that regression doesn'€t guarantee anything, however. Some players who do well on Round 1 will do equally well or better on Round 2, and vice-versa. On average -€“ if we accept the role of luck -€“ scores will regress back towards the mean.

Regression & the Sports Illustrated Jinx

As stated throughout, we are dealing with average expectation, but regression is nonetheless a statistical fact – a particularly misunderstood one. A great illustration of regression in action is shown in the Sports Illustrated Jinx, an urban myth that suggests that a disproportionately large number of the stars that appear on the cover of the famous magazine go on to suffer a decline in their fortunes.

This has nothing to do with jinxes, however, the reality is more mundane and can be explained by simple regression. A large number of cover features should be expected to fall from their giddy heights as the performances that led to their feature are extremes from which they should statistically be expected to regress.

Regression is certainly something that should be considered for betting on major tournaments in golf, but not across a season where luck should average out and the impact of talent dominate. This is even more relevant over longer time periods, hence multiple major winners like Tiger Woods.

But extreme as their talent is, it doesn't insulate them from the impact of luck over the shorter timescale in what is such a uniquely challenging sport for both players and bettors.

Now that you understand the role luck can play in a golf betting strategy, take advantage of the best US Master betting odds online!