пятница, 1 августа 2014 г.

Europa League Treble: Expect goals as Trencin v Hull

Steve Bruce is leading Hull on an unlikely European adventure

Goals for Hull, Lyon and Aberdeen on their continental travels are required for a 7/1 winner...

As the Europa League qualifying clientele become more glamorous, we're adopting a different approach to this week's treble, being led by the matches rather than the odds and picking out the best bets for three of the more attractive encounters...

Trencin v Hull
Thursday, 18:00
Back over 2.5 goals @ 2.186/5

European debutants Hull were regular visitors to under 2.5 goalsville last season, but that started to change in the spring, with four of their closing five Premier League games and their final four FA Cup ties all delivering three goals or more.

Their first ever Europa League opponents Trencin should harness that growing sense of adventure. The Slovakians' last five fixtures in the competition served up over 2.5 goals (three clearing 3.5 too), with their clash with Serbia's Vojvodina seeing them win the first leg 4-0 then lose the second 0-3.

Mlada Boleslav v Lyon
Thursday, 18:00
Back over 2.5 goals @ 2.3611/8

Lyon have spent far more time in the Europa League than they would have imagined possible during their 12-season stint as Champions League furniture between 2000 and 2012, with this their 21st outing in the B league in under two years.

The fact that they have played so much in that period is at least evidence that they are pretty skilled Europa League navigators, though their true area of expertise is earning bucks for overs backers, having done so in their last six road trips to have produced a winner. Mlada Boleslav have fired one blank in 18 home matches.

Real Sociedad v Aberdeen
Thursday, 19:30
Live on Premier Sports
Back Real Sociedad not to keep a clean sheet @ 1.9310/11

Curiously, Real Sociedad haven't competed in the UEFA Cup/Europa League all century, despite qualifying for the Champions League twice, hinting that prior to last term, their campaigns were always either exceptional or abysmal, rather than just plain good.

Aberdeen aren't exactly regulars either, yet they are making the most of this latest chance, thrashing Daugava Riga 8-0 on aggregate before surprising Eredivisie side Groningen. In those two ties, they accumulated five away goals, a tally they can add to against a team without a home shutout in four, having obtained a mere two in nine.

A 10 treble provides a 70.70 profit if successful

Examining the factors behind corner betting

Examining the factors behind corner betting

By Mark Taylor Jun 13, 2014

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Read this World Cup corners betting article, which examines what drives the propensity of corners during a game and how to calculate total or individual corner counts for a soccer match. If you want to be successful, understanding the factors behind corner betting is vital.

Are corners valuable?

Despite his love affair with the English game, Jose Mourhino has struggled with the fans obsession with corner kicks. The award of a corner is met with unique enthusiasm by English fans, and Mourhino’s remark was the precursor to an ongoing debate within the burgeoning soccer analytics community regarding the real value of corner kicks.

Argument against the importance of corners, hinge on their low goal conversion rate, coupled with a largely anecdotal threat of being caught by a rapid counter attack from the defending team.

Supporters of the corner kick counter with a favourable comparison between a corner kick and the comparable alternative, a final third pass. Also, even an unsuccessful corner can still result in the attacking side retaining possession of the ball.

Typically goals from corners account for just over 10% of the total goals scored in the EPL, with their importance varying across different teams. Sides such as Stoke can be grateful that their prowess from corner kicks has helped them establish themselves in the top flight and both Manchester teams have maximised their return from the humble corner.

Meanwhile, major domestic and European finals continue to feature game deciding goals from corner kicks, though may contribute to a gut based assessment of their value that stats simply don’t support.

The recent FA Cup final witnessed two goals from corners, following on from the only goal in Wigan’s victory over Manchester City in 2013. And Europe’s most prestigious match has featured game changing scores from corners by eventual Champions League winners, Chelsea and Real Madrid in two of the last three finals.

So despite Mourhino’s reservations, corners, at the very least provide a significant goal scoring subset to enhance open play goal totals and fans will continue to celebrate their award in a sport where scoring is both difficult and relatively uncommon.

Is team ability a factor?

Along with many secondary markets, such as bookings, the number of corners a side is awarded tends to go hand-in-hand with more fundamental indicators of relative team ability. Bookings accumulate more rapidly for a team that is forced to defend and by a similar logic, a side that is involved in the majority of the attacking intent during a match will also be more likely to accumulate more of the game’s share of corner kicks.

Soccer’s singular approach to scoring is responsible for many of the statistical trends that are observed within matches. For example, an NFL team can turn territorial advantage readily into points on the scoreboard by field goals.

In soccer, there is no secondary prize on the scoreboard for gaining territory. All a soccer team gains from being higher up the pitch is the right to try and create a goal scoring opportunity, and until a goal is scored both teams are still equal, regardless of territory or possession.

What a soccer team does tend to accumulate, through attacking intent, are the products of attacking their opponent’s goal, most notably, shots, but also corners. Corners are successfully defended goal attempts or threatening situations that have been temporarily neutralised and just as penetrating, but ultimately thwarted offense in the NFL yields field goals, soccer’s constant attacking tends to yield corners.

Using the EPL as an example

If we average the number of corners won by EPL teams with multiple seasons since 2006 we find that corners do correlate reasonably well to attacking prowess. The better sides, which we would expect to do more overall attacking, such as Manchester United, Chelsea, Liverpool and Arsenal each appear at the top of the table, while relegated, weaker or recently promoted sides dominate the foot of the table. Overtly attacking wing play may be able to tweak a side’s corner count upwards, but general weight of attacks appears to be the dominant factor.

“Better teams win more corners” is a pleasingly simple and intuitive conclusion, but as with many apparently obvious statements in soccer this one has issues of causation and context. The pregame talent gap between teams gives an indication of how a match is likely to finish, but because of the low scoring nature of soccer, underdogs sometimes win outright or hold a superior side to a draw, while the actual match outcome appears to be a partial driver of corner counts.

As we’ve seen better sides as a group, denoted by a higher pregame win probability accumulate more corners. But the conclusion has to be qualified because almost universally, teams win even more corners in similar matchups when they go onto lose the match compared to when they win it and the disparity is greatest when the gulf in class is at its highest. Massive pregame favourites win an average of six corners when they win, but nearly eight and a half when they lose.

When they trail, the best also have the ability to press their opponent’s goal even more and if they spend a large part of the game attacking, but not scoring, they gain even larger numbers of corners. It is also common to see a corner successfully defended by the concession of a further corner.

So corner counts come about through a mixture of pre-defined talent and in game effects – and we can only be reasonably well informed about the former. Using the matches played in the EPL from 2002 to 2012 as a proxy for the less common and relatively data poor international competitions, the proportion of corners won in a neutral venue game by a side that could be expected to score (P) proportion of the total goals is given by:

Proportion of Corners=0.1818+(0.6365*P)

So if a tournament game was expected to have an average of 2.6 goals and team A was expected to score 2 or proportionally 0.77 of those goals, they would expect to win 67% of the corners awarded.

In the graph below, we’ve plotted the distribution of individual corner supremacies from the perspective of the pre-game favourite. On average, that’s a side with just over a 50% chance of winning the match.

The favoured side in this sample wins just under two more corners than their weaker opponents, but the range of possible outcomes is large, with a significant minor chance that the inferior side may win more corners. Bettors may gain an edge in Corner markets but understanding how factors like last minute formation, line-up or tactic changes might influence such variance.

The plot also illustrates how the chances of increasingly larger corner handicaps being covered falls away for the average Premiership favourite.

Total match corners in the EPL over the same period averaged around 11 and the distribution of possible outcomes is also shown below. Typical with all of the major leagues there is a very slight skewing of the distribution caused by a lower limit of zero, but the possibility for totals to occasionally reach well into the twenties.

These corner characteristics, while not drawn from international competition are likely to exhibit the broad characteristics of international tournament soccer. Of the various international websites, UEFA, alone provides even the slightest of corner statistics for individual sides and only partly for individual matches.

We can begin to bring together all these strands to create general pointers when estimating corner predictions.

Predicting corner count at the World Cup

Some teams may exhibit the apparent ability to either win more than the expected proportion of corners or participate consistently in matches with many or few corners than normal. This may be a real effect of tactics or squad make up. However, unless it is backed up by copious amounts of data, it is also likely to be an artefact of reduced sample size at international level.

If you feel that the effect is real, be prepared to temper that conviction by combining these estimates with the expected averages for the tournament. For example, at Brazil 2014 the present consensus is that games will average 10 total corners per 90 minutes. This is exactly where it landed for the opening game (Brazil did however gain four more than Croatia).

Accept that international data is sparse and therefore may be prone to outliers skewing the figures. Spain will not play the likes of Georgia at the finals of a major tournament, but they may do in qualifying. That Spain can accumulate more corners than their opponents might not be a surprise, but their 83% share in qualification owes a lot to the 16 corners with just a single reply against Georgia.

Similarly, Argentina’s qualifying record appears to indicate that they gain fewer corners on average than their opponents, despite being second favourites to lift the World Cup. But once again a deeper look at the statistics shows a 20-2 corner defeat in Ecuador.

A single outlier can quickly produce misleading averages in limited samples.

England vs. Italy

Italy will begin their World Cup against England in Manaus on the 14th of June. Italy will be slightly shorter than England to win the match therefore the strong trend for favoured sides to gain most corners will favour the Azzurri.

Qualifying results offer England some comfort. Both Italy and England participated in games that, on average produced above average total corners, but England gained around 70% of the available corners, whilst Italy’s share was split virtually 50/50.

England’s lion’s share may have resulted from a tactical approach, possibly based around pressuring the second ball in the box. But a more visible cause are two matches against San Marino and one against Poland, where the corner contest was won by a combined 47-5, boosting both totals and supremacy in the type of matchups that won’t be available at the World Cup. Italy gained similarly, but to a lesser extent, most notably against Malta.

So we have a strong general trend, slightly favouring Italy and observations based on a limited amount of games, which may contain a proportion of atypical contests that suggest England have recently done well in gaining and avoiding the concession of corner kicks, while Italy may struggle to dominate in terms of corners.

Available quotes suggest that Italy will be narrowly favoured to take more corners than England, indicating that the bookmakers are siding with the more general trend. This result would repeat the outcome at Euro 2012, when Italy “won” the corner count 7-3. Although by delving into reports, it is likely that at least one of Italy’s seven corners came in extra time, reinforcing the need to verify data sources wherever possible.

Click here to see latest World Cup corner data odds

*Odds subject to change

If you have feedback, comments or questions regarding this article, please email the author or send us a tweet on Twitter.

How valuable are direct shots from a free kick?

How valuable are direct shots from a free kick?

By Mark Taylor Jul 16, 2014

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Where do goals come from? The question is the Holy Grail of managers and bettors alike, and increasingly shot frequency models are being used to find an answer. Here we make the case that for anyone making that quest spatial and tactical differentiators should be taken into consideration.

Rarity of goals makes them hard to predict

A soccer team’s quality is most conveniently measured by the rate at which they score and concede goals. Goal difference shows a strong correlation to overall success as measured by league position or points accrued per game and Poisson based approaches can be used as a basis to predict future score lines and ultimately match odds.

One drawback with goals is their relatively rarity. English Premier League teams in a typical season average around 1.4 goals per match compared to ten times that amount for shots, including blocked efforts. Therefore, shots – partly because of their greater frequency – are increasingly being used as an alternative to goals as a way of measuring team ability. Sample size is an important consideration in analysis and shots provide more copious amounts of data over the same timeframe than do goals.

The use of shots, in such crossover stats from ice hockey as total shot ratio, does present renewed challenges. Although larger sample sizes are useful, not all shots are created equally, especially in a sport where the playing surface is large and attempts can be made with both the feet and the head. Consequently, different tactical approaches may not be fully picked up by counting simple shot numbers.

How tactics can skew shot data

For example, Stoke City under Tony Pulis regularly found themselves outshot and appeared to over perform in terms of goals scored and allowed. The temptation was to attribute this over performance greatly to luck, rather than the advantageous positions from which Stoke took their shots and their tactical setup that saw opponents forced into taking more frequent attempts from distance, where the chance of scoring was greatly reduced.

Similarly, QPR in their relegation year in 2012/13, shot often, but mainly from distance. 78 of their shots had between a 1 and 2% expectation of resulting in a goal. The cumulative goal expectation from these efforts was just a single goal and that was the return they achieved.

Goals – How, where & why

How, where from, and under which circumstances, an attempt is made can have a huge influence on the chances of a goal being scored. An appreciation of the likely success rates of different types of shots is therefore, useful when assessing teams solely on their shooting record.

The major factors that contribute to a shot being successful are:

shot type – foot or a header

distance from goal – vertical distance from the goal line & horizontal distance in yards from the centre of the goal

Logistic regression can be used to formulate the relationship between a categorical dependent variable and a variety of inputs. So it is useful in predicting how likely it is that a certain type of shot from varying positions on the pitch will result in a goal.

Intuitively, greater distances, wider angles and headers rather than shots with the feet, will reduce the chances of scoring and this is confirmed by using a logistic regression approach to shot location data from the English Premier League.

Goal propensities by shot type

As an illustration, a typical shot in open play from the penalty spot has about a 24% chance of being successful, but this generic probability falls to just below 10% if the chance is taken with the head. If we move out to the 18 yard line, while maintaining a central position, the expected conversion rate for a shot tumbles to just over 13% compared to less than 5% for a headed attempt. So even with very little defensive pressure, Robin van Persie’s equalising World Cup header against Spain was both brilliantly executed and comparatively rare.

Actual penalty kicks are converted at much higher rates than ordinary shots and headers from 12 yards out, typically slightly under 80%. So the absence of any defensive pressure and the choice of kicker would appear to contribute this increased rate.

Penalties are rare, but high value events and their award makes a goal more likely than not, but attempts directly from free kicks are much less clear cut in their worth to sides. The conversion rate from direct free kicks in the EPL is around 5%.

If we take 2011/12 as typical, 5.2% of direct shots from free kicks resulted in a goal, 25% required a save to be attempted, not always successfully, 36% missed the target and 39% were blocked. In 2012/13 scoring rates was slightly higher at 5.7%

Goals & free kicks

There are numerous pre-shot advantages of taking a direct shot from a free kick compared to a similar effort from the same position in open play. The choice of taker lies with the attacking side, so the best dead ball striker gets the chance and there is tentative evidence that finishing ability is a repeatable skill. He is allowed time to prepare and take the shot at his leisure and the box is unusually well populated with team mates, who may act as decoy runners to confuse the keeper. The defence can counter with a defensive wall and a ready keeper.

The 5.3% conversion rate in the Premier League from 2007/08 to 2012/13 for direct shots from a set play compares poorly to a general conversion rate for all shots of between 9 and 10%. This has led to suggestions that direct shots from a free kick is an inefficient use of good field position and they would better serve the success of a team if they were taken short to maintain possession and attempt to create a shot closer to the goal.

However, as with all statistics, context is essential. The clearest comparison to shots taken directly from a free kick is open play shots from outside the penalty area, where the average shot location in each case is broadly similar. Under these conditions the direct free kick becomes a valued, if rare addition to a team’s scoring potential. Success rates for open play shots from outside the box rarely improve beyond 3%, making a direct free kick upwards of 70% more likely to result in a goal than a similar effort from open play.

Therefore, for a player to spurn the opportunity to win a free kick by staying on his feet when fouled or a team to resist the temptation to attempt a direct shot, a chance must be generated that is appreciably closer to the goal than the position of the original offence.

This analysis also omits any residual value of shooting from a free kick, such as goals scored from rebounds or maintaining good possession from the initial shot.

These simple mathematical models that use readily available, if tedious to collect inputs, such as shot type and location can not only highlight the true relative value of a variety of scoring methods, such as shot taking from direct free kicks, they are also reconnecting shot volume to goals.

Goals & predictive models

Predictive models that use goal expectations of actual shots and headers are becoming increasingly useful, especially if additional variables, such as shot placement are included. A team’s cumulative goal expectation based on their much more numerous chances created may be a better indicator of team talent than their actual record of goals scored and conceded over the same period, which may owe much to the vagaries of chance. The important application for betting on soccer outcomes should barely need emphasising.

Mark Taylor is a freelance soccer and NFL writer who, along with producing expert content for Pinnacle Sports, also runs his own soccer analytics blog, thePower of Goals.

If you have feedback, comments or questions regarding this article, please email the author or send us a tweet on Twitter.

Premier League: Everton striker hits top-scorer frame

Romelu Lukaku is unlikely to be daunted by a 28 million price tag

Everton's 28 million investment in Romelu Lukaku will be vindicated by another 15 goal-plus season ...

The statistic that Everton fans are rightly quoting back at those ridiculing their decision to spend a club transfer record-shattering 28 million on Romelu Lukaku is that he has scored more Premier League goals than any player besides Luis Suarez and Robin van Persie in the past two years.

It is also one of the reasons why the Belgian international looks a gorgeous bet to be one of the division's top four scorers in 2014/15 at 6.25/1.

Lukaku has never endured a mediocre season let alone a barren one, notching at least 15 times in all four of the campaigns in which he was granted more than two starts.

The 21-year-old - and it never stops feeling absurd that he can still be so young - was the Belgian Pro League top scorer in his breakout year with 15 regular competition strikes (in future editions, play-off goals would also count) and followed up with a fourth place-earning 16 in 2010/11.

2011/12 was a non-event, with Chelsea ruling that the best use for an alleged 20 million signing was to sit him on the bench or in the stands, granting him just one Premier League start and seven substitute runouts.

As soon as he was allowed to showcase his talent on loan, his quality instantly shone as he netted 17 times in 20 starts at West Brom then 15 in 29 at Everton, with Suarez the only other person to fire at least 15 times in both 2012/13 and 2013/14.

Lukaku didn't quite crack the top-scorer top four on either occasion, but he was two efforts short in each attempt, which is some achievement given that he was always adapting to new surroundings, teammates and playing styles.

Now, he finally has some stability, a manager who is his biggest advocate and a near-guarantee of a starting place, which are all ingredients that should ensure that he is better than ever before in his second season at Goodison Park.

The improved tally that Lukaku delivered in his second term at Anderlecht stands as evidence that consistency and trust are key to inspiring his finest form.

Recommended Bet: Back Romelu Lukaku to be one of the Premier League's top four scorers @ 6.25/1

Euro U19 Championship: Portugal to thwart Germany

Germany U19 coach Marcus Sorg's grip on the trophy is still loose

Michael Lintorn thinks Germany U19 are worth taking on in the European U19 Championship final...

Portugal U19 v Germany U19
Thursday, 18:00
Live on British Eurosport

Match Odds: Portugal U19 4.57/2, Germany U19 1.845/6, The Draw 4.03/1

Germany U19 were fancied pre-tournament to piggyback their senior side's World Cup success and are favoured again now following their 4-0 semi-final dismissal of Austria U19. However, in between those two checkpoints, Portugal U19 were the participants providing all the entertainment.

The three-time champions won each of their Group A games, the majority of them emphatically as Israel U19 were dismissed 3-0 and Hungary U19 ate a 1-6 reverse, with their one stutter coming in the last round against Serbia U19, when they required penalties to progress after a 0-0 draw.

However, Serbia U19 were the defending champions and best team in the competition besides the two finalists, and Germany U19 couldn't conquer them in regulation time either, spoiling the Group B shares 2-2, so Portugal U19's failure to beat them appears to have been overanalysed.

Portugal U19 have remained unbeaten throughout the whole process, with the Serbia U19 clash the first time in their ten fixtures that they didn't prevail in 90 minutes after flawless records in qualifying and their group, so there is no way that they should be odds-on to lose.

Germany U19 meanwhile finished as runners-up on three of the last four occasions that they reached the final, with Portugal U19 being the ones to deny them in 1994.

Both Teams to Score

The carefree atmosphere of the early group games has intensified as the tournament has developed, with four of the most recent seven encounters delivering under 2.5 goals and five of those rewarding punters who bet against both teams scoring.

Both the 2012 and 2013 finals of the European U19 Championship were decided by one goal, with Serbia defeating France 1-0 last year and Spain serving Greece the same dose in 2012.

Best Bet: Lay Germany U19 to win @ 1.855/6
Other Recommended Bet: Back Both Teams to Score? No @ 2.3211/8

Premier League: Barkley plus Lukaku equals top six for Everton

Romelu Lukaku will almost certainly be back at Everton in 2014/15

With Romelu Lukaku about to sign and Ross Barkley staying, Everton have all the tools for another top-six finish...

No matter how impressive Everton are in the Premier League, you will almost always find them at odds bigger than evens to finish in the top six the following campaign. The latest opportunity to back them at 2.486/4 to deliver in 2014/15 might just be the most attractive yet.

The Toffees have earned top-six billing in six of the last ten years, including each of the last two, with the 72 points that they collected in 2013/14 obliterating their prior Premier League best by a seven-point margin. It was their highest total since the 86-point haul that saw them last crowned top-flight champions in 1986/87.

One justifiable reason for punter scepticism is the suspicion that Man United and Tottenham will be far more competitive under their new managers, Louis van Gaal having won titles with every club he has ever coached and Mauricio Pochettino gaining many admirers with his work at Southampton.

The other less verifiable statement flung out as rationale for opposing Everton is that their squad won't be as strong this time as they were too reliant on loan recruits last term.

However, the two loanees who had the greatest impact of their four are both going to be back at Goodison Park for more, with Gareth Barry signing a three-year contract and Romelu Lukaku about to join permanently for a club record fee. Lacina Traore might return to add attacking depth too.

On top of that, they won't lose any of their prize assets either. Ross Barkley ignored links to the likes of Man City, Chelsea and Man United to apply biro to A4, committing himself to his boyhood side until 2018. Leighton Baines and Seamus Coleman had already penned extensions.

Given that they have achieved top-six finishes in seasons following the exits of Marouane Fellaini (2013/14), Jack Rodwell (2012/13) and Wayne Rooney (2004/05), imagine the potential for progress after a summer in which they keep their key players together.

Recommended Bet: Back Everton to finish in the top six @ 2.486/4

Do Grand Slam conditions affect favourite’s success and correct score outcomes?

Do Grand Slam conditions affect favourite’s success and correct score outcomes?

By Dan Weston Jun 25, 2014

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With the best of five set format, ATP Grand Slam Tennis betting is a completely different proposition to normal ATP Tour Tennis betting, with those matches being the best of three sets. This article examines the Grand Slam statistics for the four tournaments, to give bettors an insight into correct score betting and how often favourites win in Grand Slams.

As has been mentioned in previous articles, the best of five set format in Grand Slams gives favourites – the player perceived to be better – a higher chance of winning an individual match than in the normal three set ATP Tour format.

This is because the favourite has more time to recover from a poor start and with fitness often being a big facet in why a player is highly ranked, the longer format gives the favourite a better chance in longer matches.

If a player wins the first set in the best of three set format, he’s won 50% of the sets required to take the match win. However, if that player wins the first set in the best of five set format, this figure drops to 33.3% of sets required. Therefore taking an early lead in the match has much less impact on the likelihood of winning, due to the lower time decay of the match.

If a cross-section of the Tennis betting and watching public were surveyed and asked how often the various correct score scenarios occurred in Grand Slams, it’s highly likely the answers would be extremely contrasting, with it being probable that the percentages of 3-1 and 3-2 correct scores being over-estimated.

This is due to the fallacy whereby people subconsciously remember notable events, such as long, epic, five set matches. Even casual tennis fans would be able to recall Nicolas Mahut’s defeat to John Isner at Wimbledon in 2010, where the big-serving American took the final set 70-68, with that set alone lasting an incredible 8 hours, 11 minutes. It is far less likely that tennis fans and bettors have longstanding memories of a routine 3-0 win for the likes of Nadal or Djokovic in the early rounds.

ATP: Correct score betting & Favourite win %

The following table illustrates the correct score percentages for Grand Slams from 2011-2014, including the recent French Open:

Overall Grand Slam statistics

Correct Scores

2011

2012

2013

2014

3-0

55.1

46.9

53.2

56.7

3-1

29.6

31.2

26.6

27.3

3-2

15.3

21.9

20.2

16.0

Favourite win %

2011

2012

2013

2014

%

80.5

78.5

78.8

80.7

As can be seen in the above table, the figure for the 3-0 correct score is generally just over 50% of the completed Grand Slam matches, with 3-1 being generally more likely than 3-2, and these figures may be of some surprise to readers.

It can also be seen that favourites consistently won a high proportion of matches in comparison to other tournament types. For example, a three set 250 level tour event has around just 63% of favourites winning, and this figure rises to around 70% in 500s and Masters 1000 events. This is clear evidence that the five set format benefits the favourite.

Certainly the lack of five set wins in the recent French Open contributed to the low 2014 figure. This event was notable with just 13.9% of matches ending in this scoreline – the second lowest in the 14 Grand Slams surveyed. The lowest was 12.9% in 2011 – also in the French Open.

The French Open percentages can be viewed below:

French Grand Slam statistics

Correct Scores

2011

2012

2013

2014

Overall

3-0

54.0

49.6

55.8

61.5

55.2

3-1

33.1

28.9

24.2

24.6

55.2

3-2

12.9

21.5

20.0

13.9

17.0

Favourite win %

2011

2012

2013

2014

Overall

%

79.1

83.1

80.8

86.1

862.2

It’s clear that the French Open has less matches ending in a 3-2 scoreline than the average Grand Slam. Comparing the two tables above, the French Open had a lower percentage of matches than the ATP mean ending in five sets every year. However, it also generally had higher win percentages for favourites (it has been the best overall tournament for favourite success since 2011), and this would indicate that the clay surfaces exaggerates the ability difference between favourites and underdogs.

The following percentages for Wimbledon will be of great interest to bettors:

Wimbledon Grand Slam statistics

Correct Scores

2011

2012

2013

Overall

3-0

54.1

43.4

61.7

52.9

3-1

31.1

34.4

24.3

30.1

3-2

14.8

22.1

13.9

17.0

Favourite win %

2011

2012

2013

Overall

%

82.0

75.8

77.6

78.5

Compared to the French Open, there is a notable rise in the percentage for 3-1 correct score wins. The most likely reason for this is the faster grass surface giving more tiebreaks and one-break style sets, which increases the chance of several key points deciding the outcome of a set. This gives the underdog a bigger chance of taking a set, and the ‘choke factor’ of them failing to serve out a break lead is reduced due to the advantages that the surface gives to servers.

The favourite win percentage at Wimbledon was the second highest across the four Grand Slams, although it was very similar to both hard court events – the Australian and US Opens – and the statistics for these events can be seen below:

Australian Open Grand Slam statistics

Correct Scores

2011

2012

2013

2014

Overall

3-0

57.0

50.8

50.8

51.7

52.6

3-1

25.6

26.3

24.6

30.2

26.6

3-2

17.4

22.9

24.6

18.1

20.8

Favourite win %

2011

2012

2013

2014

Overall

%

80.0

76.9

81.1

75.0

78.3

US Open Grand Slam statistics

Correct Scores

2011

2012

2013

Overall

3-0

55.2

43.9

45.9

48.2

3-1

28.4

35.0

33.6

32.4

3-2

16.4

21.1

20.5

19.4

Favourite win %

2011

2012

2013

2014

Overall

%

80.9

78.0

75.4

78.1

One statistic immediately noticeable is the lower 75.0% win percentage in the Australian Open in 2014. This was the lowest favourite win percentage across all Grand Slams from 2011-2014, and there is little doubt that this figure was related to the oppressive heat that the players endured in Melbourne this year.

It will also be interesting to see whether the US Open continues its downward trend of lowering favourite win percentages when the event takes place in August, and it can also be seen that this event has the lowest percentage of 3-0 correct score results, with it being the only Grand Slam to have an average below 50%.

With the five set format of Grand Slams making for very different conditions to the normal three set ATP format, bettors should treat the events very differently, and as can be witnessed from the statistics above, all Grand Slam events are also not equal. A detailed knowledge of likely conditions and trends is vital for successful correct score betting.

Click here for the latest ATP Grand Slam betting odds

*Odds subject to change

If you have feedback, comments or questions regarding this article, please email the author or send us a tweet on Twitter.