Friday, 31 May 2013

Hedge Betting

Friday, 24 May 2013

How Clay Courts Affect Tennis Players

One player has dominated the French Open like no other: Rafael Nadal. But why does the red clay favour the Spaniard so strongly? Find out what affect surface type has on the top 20 ATP players and how this knowledge can help your tennis betting?

Nadal is as short as 2.000* to win the 2013 French Open following seven wins at Roland Garros. The Spaniard’s dominance on clay, however is down to a simple piece of science: friction. The torn-up nature of the surface means that the clay particles generate a lot more friction when balls bounce off the ground – far more than grass or hard courts.

Clay court science

The resistance generated when the ball collides with the clay slows down the bottom of the ball, but doesn’t affect the velocity of the top of it, which continues travelling at the same speed. The disparity between the consistent speed (at the top of the ball) and the deceleration (on the bottom of the ball) forces a more vertical impact with the floor.

The increased vertical angle then causes a higher bounce, which coupled with an overall decrease in speed, ensures that it’s harder to hit a winner and easier to return shots. While this provides a distinct benefit for anyone returning serve, it also means the surface is ideal for consistent, powerful baseline players – like Rafael Nadal.
Taking a note of a player’s style is particularly important for tennis betting for the French Open and other clay tournaments, as the competition favours baseline players over attackers (Federer) and players who built their ranking on big serves (plenty of other players in the top 20).

Clay court aces: few and far between
One of the biggest statistics supporting the science behind the quirks of clay courts is ace percentages. Throughout the careers of all of the top 20 ATP players, every one has hit noticeably fewer aces on clay than on hard courts. On average, the ATP top 20 has hit 43.5% fewer aces on clay than on hard courts.

Jo-Wilfried Tsonga is the biggest victim of the curse of clay, hitting 79.5% fewer aces over his career on the crushed brick than on hard courts. The Frenchman averages just 7.3 ace serves out of 100, compared with 13.1 on hard.

Milos Raonic has recorded the highest career ace percentage on the surface (12.9 per 100 serves), which is still a massive 52.7% drop on his hard court performances.

Service stopper
Nineteen of the 20 top ATP players win fewer points on their first serves on clay than on hard courts. While this is partially accounted for by a reduction in aces, the fact that clay courts gives receivers a better opportunity to return the ball is also vital.

Only Juan Monaco manages to win more points on his first serve on clay – 0.9% more – than on hard courts. He also wins more points on clay on his second serve – 3.2%. Such tidbits are useful for tennis betting, as not many people would consider anyone to win more points on their serve on clay than on a hard court. This fact suggests that Monaco could easily be underrated on the surface.

Returners’ revenge
Every player in the ATP top 20 has an improved “return points won” percentage on clay. While the improvement can be as little as 0.8% (Janko Tipsarevic), it’s also the statistic that shows Nadal’s dominance. With a 14.3% increase in return points won on clay; the Spaniard wins an incredible 46.9% of points served at him.

Spanish supremacy
All three Spanish men inside the top 20 boast exceptional clay-court performance. Nadal and David Ferrer win more return points on clay than any other player, winning 46.9% and 44.2% respectively (Djokovic is at 43.9%).
Taking note of a player’s style is vital for tennis betting on the French Open This is almost certainly helped by the fact that clay is the primary surface in Spain, largely because of the hot, dry climate. This could be why Andy Murray, who spent a lot of his youth training in Spain, has the fifth highest return point percentage of the top 20 at 43.6%.

In terms of the performance difference between clay and hard courts, Nadal and fellow Spaniard Nicolas Almagro top the table, successfully returning on 14.3% and 10.7% more points on clay than hard courts.
It could also be argued that Nicolas Almagro is the most surface-agnostic of the top 20 players, hitting just 18.9% fewer aces on the surface (the second smallest drop), and winning just 0.5% fewer points on his first serve and 0.4% on his second – the smallest differences of any player.

Other clay outliers
Investigating the performance of the 20 top ATP players also revealed some other interesting facts about players not usually associated with their clay-court performances:

Kei Nishikori: Nishikori actually wins the third-highest percentage of return points of any of the top 20 players at 43.9%. Only Nadal and Ferrer do better. Despite this success, he also has the lowest ace rate – the Japanese star achieves just 2.5 aces per 100 serves.

Stanislas Wawrinka: The Swiss ace doesn’t have much luck winning his first serve on clay – he wins 21.8% fewer points on his first serve on the surface.

Janko Tipsarevic: Tipsarevic’s return point performance is pretty much constant between the clay and hard courts – he only wins 0.8% more return points on clay, the lowest of any of the ATP 20.
Almost no other sports have the variety that tennis’ different court surfaces bring, nor witness as profound an effect. Therefore for any serious tennis bettor, it is vital to treat the clay, hard and grass courts as separate entities, each with its unique quirks that should be built into betting analysis.

Tuesday, 21 May 2013

Why The Framing Of A Bet Is So Important - Learn How Framing Affects Betting

If World No. 1 Novak Djokovic was playing World No. 60 Paul-Henri Mathieu in a five set Grand Slam tournament, what respective odds would you expect for this game? How about Djokovic 1.72, Mathieu 2.40? Does that seem realistic?

If these odds appear a bit off, it’s probably because you typically wouldn’t give Djokovic a slim 58% chance of winning and the Frenchman a somewhat generous 42% chance. These are real odds, however, but just not for the match outcome.

Instead, these are the odds of winning each point, accurate for this pair’s encounter in the first round of 2013 Australian Open, which Djokovic went on to win (6-2, 6-4, 7-5).

Let’s break the numbers down. The game featured 163 points, of which Djokovic won 95 and Mathieu 68. From this we can produce a probability per point of 95/163 for Djokovic and 68/163 for his opponent. The actual odds for the entire match were entirely different at:

  • Djokovic 1.01
  • Mathieu 41.00

Both sets of odds are accurate, but are looking at the game from entirely different perspectives or “frames”: the narrow frame (one point) vs. the broad frame (the entire match).

People struggle to reconcile the differing probabilities of the two perspectives – even though they are for the same event – and this can have significant consequences, especially in live tennis betting.

Live betting effectively looks at the game point-by-point, and at the scale Mathieu truly does have a 42% success rate. This can lead bettors to overstate his overall chance, however, especially if they get caught up with the emotion of the crowd and the commentators.

People struggle to reconcile the differing probabilities of two perspectives

A 42% win percentage per point, extrapolated over all 163 points, however, translates to a chance of 41.00 for overall success as suggested by the odds (which suggests that if the pair played 40 times the Frenchman would win once).

Framing: a market for success

The phenomenon of framing bias has been documented by decision-making theorists and is seen where someone is averse to an isolated gamble, because subjective reason believes it to be risky despite the expected value being positive. A famous example is:

Would you take the following gamble on a single coin toss?

Heads loses you $100, tails wins you $200

The majority of people, displaying common risk aversion, reject the offer, focusing on the potential loss in the single toss scenario, even though the Expected Value, and therefore the probability of making money, is $50:

Objective Expected Value = (0.5*200)-(0.5*100) = $50

The academic reasoning for this is that people tend to feel the loss of $1 twice as much as the gain of the same amount. Applying this factor of two for losses, the Expected Value for the single gamble to zero and hence it is rejected:

Loss Averse Expected Value = (0.5*200)-(0.5*100*2) = $0

By expanding our framing to more than a one-off, however, we can get a better understanding of how much we’re likely to win or lose. Compare this slightly larger frame of two coin tosses:

Two tosses Heads lose $100 – Tails win $200

25% lose $200; 50% win $100; 25% win $400. The EV is $100

As above, but with losses doubled due to loss aversion:

25% lose $400; 50% win $100; 25% win $400 – EV is $50

Even with a heightened fear of loss, the Expected Value of two coin tosses is still more positive when viewed with a wider frame. Had you simply used the narrow-frame to analysis the outcome of the two tosses, the opportunity to benefit would have been missed.

The loss adverse approach to this bet tends to remain consistent when considering multiple tosses, but as the cumulative odds of losing diminish with aggregate gambles, loss aversion correspondingly diminishes.

If asked the same question based on a large number of tosses – a broader frame – people tend to be more comfortable with the gamble.

At 100 coin tosses, this bet (without the doubling) has an EV of $5,000 with only a 1 in 2,300 chance of losing any money and a 1 in 62,000 chance of losing $1,000. However, by rejecting the isolated bet in the first instance – the narrow frame – you miss out.

Wider examples

The issues around framing are frequently observed in environments where frequency of data change is high, e.g. financial indexes. The more often you check the market – and therefore the narrower the frame you take – the more likely you are to see noise rather than signal.

Nassim Nicholas Taleb summarises it neatly in his book Fooled By Randomness by illustrating that a portfolio of stocks with a 15% return and 10% volatility returns surprisingly different chances of success at ever narrowing frames. If you were checking this portfolio every second the chance of success would be only 50.02% yet the broad frame – over a year – is 93%.

Friday, 17 May 2013

Calculating Expected Value For Sports Betting

The Expected Value of a bet tells us how much we can expect to win (on average) per bet, and as such is the most valuable calculation a bettor can make when, for example comparing bookmakers. So how do you calculate EV – and how does it affect sports betting?

“Expected value” – or EV – is the amount a player can expect to win or lose if they were to place a bet on the same odds many times over. For example, if you were to bet $10 on heads in a coin toss, and you were to receive $11 every time you got it right, the EV would be 0.5.

This means that if you were to make the same bet on heads over and over again, you can expect to win an average of $0.50 for each bet of $10.

How to Calculate Expected Value

The formula for calculating Expected Value is relatively easy – simply multiply your probability of winning with the amount you could win per bet, and subtract the probability of losing multiplied by the amount lost per bet:

(Probability of Wining) x (Amount Won per Bet) – (Probability of Losing) x (Amount Lost per Bet)

To calculate the expected value for sports betting, you can fill in the above formula with decimals odds with a few calculations:

1. Find the decimal odds for each outcome (win, lose, draw)
2. Calculate the potential winnings for each outcome by multiplying your stake by the decimal, and then subtract the stake.
3. Divide 1 by the odds of an outcome to calculate the probability of that outcome
4. Substitute this information into the above formula.

For example, when Manchester United (1.263) play Wigan (13.500), with a draw at 6.500, a bet of $10 on Wigan to win would provide potential winnings of $125, with the probability of that happening at 0.074 or 7.4%.

The probability of this outcome not occurring is the sum of Man Utd and a draw, or 0.792 + 0.154 = 0.946. The amount lost per bet is the initial wager – $10. Therefore the complete formula looks like:

(0.074 x $125) – (0.946 x $10) = -$0.20

The EV is negative for this bet, suggesting that you will lose an average of $0.20 for every $10 staked.

How Does Expected Value for Sports Betting Help?

Remember, a negative EV doesn’t mean you’re going to lose money. Unlike a coin toss, sports betting odds are subjective, and therefore if you outsmart the bookmaker, you’re likely to make money.

If you calculate your own probability for a match that differs from the implied probability of the odds, you could see where to find a positive EV, and therefore the best chance to win.

For example, the odds imply that Wigan only have a 7.4% chance of winning. If you calculate (maybe using a system like Poisson Distribution) that Wigan has a 10% chance of winning, the EV for betting on a Wigan win jumps to $3.262.

It’s also a perfect measure for comparing odds in arbitrage betting.

Tuesday, 14 May 2013

Cricket Betting Tips & Strategies

When it comes to betting on cricket, there are a few tips that come in handy. Join us as we breakdown cricket betting, helping you make the best predictions on upcoming matches.
Betting on cricket, if you do it correctly, is a very simple way for sports bettors to make money. Because it is a game played over several hours there is always plenty of time to reverse a losing position and to even improve a winning one. All it takes is a little knowledge and a lot of attention to detail. Here are a few tips to help you along when it comes time to make your sports picks:

Know your formats
At heart, there are only two versions of cricket - one day and ‘multi-day’ - but there are three different formats under each of those headings. ‘Test’ cricket is played over five days and only played at international level. Other multi-day games are over usually four and sometimes three days and are normally referred to as ‘first class’ matches. One day games may be played over 50, 40 or 20 overs per team, with abbreviations such as ‘ODI’ being used to refer to a 50 over game between international sides, T20 to refer to the 20 over version and (sometimes) T20i used to refer to international 20 over matches.

It is important to know which kind of game you are betting on for any number of reasons. The most obvious comes when you are betting in a win market, because even at international level a team will normally be better at one format than another. There are less obvious areas where this applies, too. For example, you can often bet on how many runs a batsman will score in a match, either as an under/over bet or in a spread. It then becomes vitally important to factor in whether it is a one day game or not, because each team only bats once in a one day game but can bat twice in a longer format.
Which leads us neatly on to...

Do your research
This isn’t exclusive to cricket, but it is particularly important when betting on this sport. Cricket grounds differ wildly and some teams simply do better on their own ground than on others. India, for example, are usually very difficult to beat when they are playing at home, even when their side is comparatively weak. England recently won a series there for the first time in almost 30 years, but the Indians then went on to beat Australia 4-0 in their next home series, and with substantially the same players.

As well as considering that, some sides don’t tend to do well in particular match-ups. Looking at the example above, Australia have a particularly poor record in India and that was the case even when they were on a decade-long run of being ranked number one in the world. England’s record in India wasn’t great until this year, and last year they lost to Pakistan and drew with Sri Lanka away as well, whilst they were supposedly the best in the world, so it is fair to assume that the betting odds on them winning anywhere on the sub-continent should be long.

Then there are player-to-player match-ups that you need to be aware of, particularly if you are betting in play. England’s Kevin Pietersen, for example, is one of the best batsmen in the world and you might well be considering backing him in one of those runs markets I mentioned above. Pietersen, though, is famously vulnerable to left-armed slow bowlers, who dismiss him a disproportionate number of times. If you know that Pietersen is going to be facing a side who have such a bowler in their team, you might want to pitch your estimate of how many runs he might score a little lower. And if you are betting in-play, you might want to consider laying off your bet (or taking the ‘cash out’ option that some markets have) when the left arm bowler comes into the attack.

Watch the weather
Ah, cricket and the weather. Two of the biggest cliche’s about cricket are that it is the only sport which stops for a meal break and the only one you can’t play in the rain. Now, the first is true (but if you were playing a sport that can last all day you’d at least want a bathroom break at some point), but the second isn’t. However, cricket does stop for rain and for bad light, largely because whether you are batting or in the field you don’t want a leather missile hurtling towards you at 80mph when you can’t really see it for rain or gloom (if you’ve never seen a cricket ball, it is a red version of a field hockey ball, the latter sport having been invented by cricketers).

These factors can make a big difference to the outcome of a cricket match, although the way depends upon the sort of game you are betting on. For a multi-day game, a prolonged rain break may cause one side to declare their innings closed, in the hope of having enough time to bowl out their opponent. You therefore need to again pay attention any run market bets which you may have, and to watch the odds shift in the win market so that you can take advantage - especially if you can make your move before any official announcement of what is going to happen, which will get you the best odds. In fact, it can rain so much that play for the rest of the day is washed out, so again you’ll want to try to take advantage if you’ve been betting on the number of runs to be scored that day.

In one day games, on the other hand, rain can lead to one side or both having fewer overs to bat for and this can be very significant in a number of ways. For example, the smaller the number of overs, the more chance the outsider will have, because pure chance begins to play more of a role in the result. Second, every competition will have a minimum number of overs to be bowled before the game is valid. In the 2010 T20 World Cup Ireland were on the verge of beating England but because they did not bat for the required 5 overs to constitute a game the match was declared void; as a result England went through to the next round and won the tournament.
Not only is it vitally important to know just what the weather rules are, it is important to know what the rules are if a game is declared void. Do you get your stake back, or not?

Who the hell are Duckworth-Lewis?
The Duckworth-Lewis method is a way used to calculate the impact that a stoppage in play has upon the result of a one day game. It is a very complicated thing to try and explain (and resulted in the dullest book ever written about cricket -I know, because I had to review it) but basically it is the way that the number of runs scored is recalculated after that stoppage. If the stoppage occurs in the first innings of the game then that recalculation will take place at the end of the innings and this is a good place to make some money. Get hold of a copy of the tables and the instructions for using them. You should then be able to calculate what that revised total will be long before the announcement is made, and so get into the over/under and spread markets before others do.
Those tables will also be handy in the second innings. You will often see television coverage (or, if you are at the game, the scoreboard) flash up the figure ‘D/L Par’. That is how many runs the side batting needs to have scored to win the game. There are a lot of options here. If they are way ahead or behind that figure, you can back or lay them in the win market if the odds are right, for example.

Finally, there’s one last way that Duckworth-Lewis can help you, and it is because of something that the tables don’t do. In one day cricket, each bowler is only allowed a certain number of overs. That number of overs gets reduced as the number of total overs goes down and this can mean that a side has no overs left of their best bowlers (or far fewer of them). That might give more of a chance to the batting side than either the par score or the odds might suggest, again giving you a chance to clean up whilst realising that cricket may be a complictated game to bet on, but it can be a very profitable one, too.

Friday, 10 May 2013

What Can Baseball Betting Teach Soccer Bettors? How Soccer Analysis Can Improve Soccer Betting

To the minds of many soccer bettors, the eye test is the one true method of understanding the fluid game of soccer. ‘Go with what you know’ is the attitude, but without supporting data, do we know much at all? Perhaps taking some tips from stats-heavy baseball could improve our soccer betting, so we asked Senior Traders from both sports for their insights.
Lead EPL Trader: “The big difference between soccer and most other sports is that the concept of applying statistical analysis to soccer is quite a bit more immature than it is in baseball, basketball, or hockey,”

“A lot of bettors are pretty familiar with the analytics applied to fantasy sports in those areas and are ready to adapt them to betting, while in soccer the entire analytics concept is still picking up steam.”

Baseball is alien to many of Pinnacle Sports’ bettors, in part because it deviates so completely from soccer. Each play has a start and end point, with a focus on the battle between pitcher and hitter.

It’s that focus that makes baseball easier to analyse than a sport like soccer. Baseball is also noteworthy for its meticulous recording of every season, game, inning, at bat and pitch, which provides the kind of data availability soccer bettors can only dream of.

It’s not just a lack of information that the trader thinks is a problem – and not only for soccer. “I would suggest most bettors rely on gut too much, not just soccer bettors.” A human’s gut instincts are scientifically known as heuristics. Essentially, our heuristics – developed to help us survive and evolve with limited information – can actually play against us in our modern world.

How baseball helps soccer bettors

Lead Baseball Trader: “There is a lot of data in a form that is easier to utilize than in any other sport, there are so many different angles that the data could be looked at in order to find a pattern that a smart bettor could take advantage of.”

“You could look at something on the league level (Teams play better coming off of flights of less than 2 hours), the team level (a certain team might struggle when they face left-handed pitchers), and the player level (some pitchers have more success pitching indoors, and others vice versa).”

“Since there is so much data available in baseball, a smart bettor may be able to figure out a real trend that in other sports you wouldn’t be able to tell if it’s a small sample size.”

The soccer trader agrees that similar patterns exist in the soccer world, listing Pythagorean expectation models and Simon Gleave’s ISG Coefficient as examples where data has offered predictive power in soccer circles. We’ll discuss these models in the coming weeks.

“The causation chains are much longer and more complex in soccer, and a lot of the current work in the field is trying to work out what really matters. On the other hand, the betting odds in soccer probably don’t take nearly as many stats into account as the ones in baseball, so if you develop new ways to look at the game, you stand a reasonable chance of profiting from it.”

…And there’s the point. By equipping yourself with data alongside the eye test, you better position yourself for success, especially when so few bettors are applying a valuable tool.

The data protects the user from faulty eye tests, while the eye tests act as both a starting point and confirmation – just ask baseball bettors. Apply the attitude to one sport, and you can then apply it to all.

Tuesday, 7 May 2013

Break Points In Tennis Betting - The Secret Strength Of Break Point Receivers

Break points are some of the most exciting moments of tennis matches, but does the added pressure of a game-winning point affect the players as much as the viewers?

Break points play an important role in every tennis competition. In fact, it’s only a tiny minority of Grand Slam matches that finish without a break point being played. A study of 528 men’s singles matches over eight Grand Slam competitions (by Gareth Knight and Peter O’Donoghue of the Cardiff School of Sport) showed that an incredible 97.2% of performances involved a break point.

The most important observation from their study, however, was in comparing the winners of break points with the winners of other points. Players receiving a serve performed better than average when they were attacking a break point.

Their research showed that a player receiving a serve won on average 38% of points fired against him. When those same receivers were attempting to win a break point, however, their success rate rose to 42%.

Break points more influential than surface type?

A difference in scoring success between being at break point and facing a regular point at 4% could actually have a greater impact on receiving than courts’ surfaces – a much more popular discussion point for fans and commentators alike.

It’s widely accepted that a tennis court’s surface affects play. The grass of Wimbledon favours big serves, as the ball is harder to return when bouncing off the low-friction grass, while at the other end of the spectrum, Roland Garros’ clay slows the ball and launches it higher into the air, giving receivers more time to return the serve. The hard courts of the US and Australian Opens fall somewhere in between.

However, the impact of these is actually less than the difference between break points/normal points. Receivers on Wimbledon’s grass courts achieved a win rate of 41% on break points in 2008 and 2009, while normal points were successfully returned on just 35% of occasions. This means the server was – on average – winning 65% of normal points and 59.5% of break points.

Compare this to the other end of the spectrum – the return-friendly clay of the French Open. This competition saw 41.5% of break points won and 38.5% of normal points. This means 61.5% of normal points were won by the server, and 58.5% of break points.

Therefore the French Open service success rates are just 3.5% and 1% worse for the server than on the traditionally serve-friendly grass court. Compare them to the difference between serving on a normal or a break point – 5.5% and 3% – and we can see that the difference between normal points and break points is potentially more important than the difference of surface in terms of affecting who wins the point.

The US Open and Australian Opens – both on hard courts – are 42% (break point) 37.5% (normal) and 43% (break point) and 38.5% (normal) respectively.

Of course, the surface type plays an important role in every point, not just break points, and therefore it would be naïve to claim that the difference between break points and normal points is more significant than the surface over a whole match.

For the outcome of break points, however, merely the fact that it is a break point could be more important than whatever is under the player’s feet.

Friday, 3 May 2013

Horse Racing: Knowledge Of Draw Bias Wins One Bettor Over £400,000

There is more than one way to skin a cat so the story goes, and being a professional gambler can be achieved in many different ways. Paul Cooper had his own unique way of gambling for profit, and he used his knowledge of draw bias at British racecourses coupled with an unusual bet called the Tricast to win over £400,000 on a number of bets at Thirsk racecourse.

Cooper noticed before virtually anyone else that horses drawn high over the straight sprint course at Thirsk appeared to have a distinct advantage. There are a number of racecourses with distinct draw biases around the country. Chester and Beverley probably being the most prevalent but the difference at Thirsk was that the bias was just as marked on fast ground as it was on soft ground. The reason for this was that the watering system at Thirsk left a lot to be desired, and it left a strip of ground next to the stands rail which was unwatered and therefore significantly faster than the rest of the track.

Cooper would perm those 5 or 6 horses drawn highest in tricasts, and therefore the ones who would be running on the favoured fast ground these 5 or 6 often included several complete outsiders and when his bet came in which it did more often than not the return was massive.

Cooper is certainly not a £10,000 win single guy, and is fascinated by the returns which you can get from multiple bets. He believes that the Lucky 15 is a value bet. A Lucky 15 is a Yankee (6 doubles, 4 trebles and an accumulator) plus 4 win singles. The major bookmakers normally often some form of concession with the bet. For instance if you only have one winner they will double the odds. So one 7/1 winner means that you will just about get your money back.

Here are Paul Coopers tips for successful betting on the horses:
  1. Always stay cool, calm and collected when making a selection. Don't let your emotions affect your selection.
  2. Only bet when you believe that you are getting good value.
  3. Look to back horses with winning form, be very wary of maidens.
  4. Concentrate on Sprint races the form is often more reliable than longer distance flat races.
  5. Try and find a small competent yard to follow. You will get much better prices on their horses than those of the larger stables.
  6. Don't back odds on favourites.