Perth Scorchers - a Batting Order Dilemma

After 17 overs of the second innings, this morning's Big Bash match looked to be all but over. Perth Scorchers required 18 runs off 17 balls and knew that one of the remaining overs would have to be bowled by Aaron Finch due to an injury to Dwayne Bravo. However, after the wicket of Michael Klinger, the Scorchers would somehow leave themselves needing 7 off the final 3 balls and ended up winning it with a six off the final delivery.

The almost choke from Perth Scorchers led Dan Weston of CricketRatings.co.uk to tweet the following:

Interested to know who is deciding Perth's batting order.

Whoever it is, he shouldn't be...#BBL06

— Dan W (@Cricket_Ratings) December 29, 2016

This led me to wonder how the various options looked in the stats and what arguments we could make for each of the batsmen.

Scenario

Firstly, here is a quick overview of the situation. Michael Klinger's dismissal on the second ball of Sunil Narine's final over meant that the Scorchers required 18 runs off the final 16 deliveries. They had Mitchell Marsh at the other end on 25 off 16 balls. In terms of the remaining bowling, Sunil Narine had four balls left, Nathan Rimmington had one over remaining and either Aaron Finch or Tom Cooper were expected to bowl the final over in the absence of Dwayne Bravo.

Which batsman should have replaced Klinger following his dismissal?

Perth Scorchers effectively had five options in terms of who they brought in to replace Michael Klinger - Ashton Turner, Adam Voges, Ashton Agar, David Willey or Sam Whiteman. Let us look at each of them individually before we derives potential strategies.

Batting Options

Ashton Turner

• Batting rating of 0.91
• 7.79 balls per boundary hit
• 18.6% dot balls faced
• 9 runs off 12 balls with 0 boundaries in 7 innings when coming in during 18th over or later
• SR of 97.8, 38.0% dot balls and 18.4 balls per boundary during first 5 balls faced
• Explosive potential with SR of 160.7 in balls 6-10

Adam Voges

• Batting rating of 0.99 (but drops to 0.82 when chasing)
• 8.62 balls per boundary hit
• 22.4% dot balls faced
• 6 off 4 (2012) and 19 off 9 (2014) when coming in during 18th over or later
• SR of 106.1, 37.4% dot balls and 10.3 balls per boundary during first 5 balls faced

Ashton Agar

• Batting rating of 0.83
• 6.73 balls per boundary hit
• 33.3% dot balls faced
• 6 off 4 and 7 off 6 when coming in during 18th over or later
• SR of 86.3, 53.7% dot balls and 10.6 balls per boundary during first 5 balls faced

David Willey

• Batting rating of 1.16
• 5.05 balls per boundary hit
• 29.8% dot balls faced
• 44 off 26 balls when coming in during 18th over or later (although skewed by 25 off 9 in one innings)
• SR of 80.9, 50.8% dot balls and 13.8 balls per boundary during first 5 balls faced
• Much lower SR against pace than against spin
• Explosive potential with SR of 166.1 in balls 6-10

Sam Whiteman

• Batting rating of 0.86
• 7.98 balls per boundary hit
• 26.6% dot balls faced
• 9 off 4, 10 off 8 and 0 off 1 when coming in during 18th over or later
• SR of 76.0, 47.9% dot balls and 16.0 balls per boundary during first 5 balls faced

Potential Strategies

The advantage that Perth Scorchers had in this situation was the fact that they had Mitchell Marsh settled at the other end with 25 off 16 balls. Marsh is a decent batsman and also a reasonably fast scorer once he is in. Needing just 18 off 16 balls also meant that they didn't necessarily need to do much other than keep the score ticking over with the odd boundary.

Based on this, one potential strategy would be to look for a player to simply get singles to give Marsh the strike straight away. In this situation, we might look at Adam Voges and Ashton Turner as options given their 22.4% and 18.6% of dot balls faced, especially when you consider that this only goes up to 37.4% and 38.0% in their first 5 balls faced. Linked to this, they also have the highest strike rate during their first few balls. However, a concern around Ashton Turner might be the fact that he has struggled in the past when it comes to starting his innings in the closing overs with just 9 runs off 12 balls across 7 innings.

Another strategy might be to look for a big hitter to come in and effectively look to end the match as soon as possible. David Willey (5.05) and Ashton Agar (6.73) are the two options with the lowest balls per boundary stats, although one might also look at Adam Voges who, despite the worst balls per boundary stat overall, actually has the best balls per boundary early in his innings.

A third strategy could be to look for a player with explosive potential, particularly knowing that Nathan Rimmington is far from the best death bowler in the competition and that Aaron Finch or Tom Cooper would have to bowl the final over. In this situation, David Willey and Ashton Turner are the clear standouts - both have strike rates of over 160.0 for balls 6-10 once they have had a few balls to get their eye in.

Conclusion
I would suggest that we can rule out Sam Whiteman as an option in this situation. He is not the fastest starter, does not rotate the strike that effectively early on and does not have the explosive acceleration. Ashton Agar could have been an option, but I feel that even if you were looking for a hitter to end it quickly, there were better options.

This leaves David Willey, Adam Voges and Ashton Turner. With Mitchell Marsh at the other end, Ashton Turner seems like a reasonable option. The stats suggest that he is able to effectively rotate the strike from the start of his innings and he has done this against spinners in the past as well. He also has the benefit of being able to provide the acceleration in the last over or two if Mitchell Marsh falls. The major concern would be that he has struggled coming in late in the past.

David Willey gives the same potential acceleration as Turner, but may have run the risk of getting bogged down facing dot balls early on. This downside also means that if you do not bring him in at this stage, there might not be an optimal opportunity to use him. However, with Marsh at the other end and the upside once he gets his eye in, he is a solid option. Adam Voges brings plenty of experience and has performed well in this situation in the past and with what should be an easy chase from this point, his lack of explosive scoring was unlikely to be a real issue.

There is no obvious correct decision here from the basic stats, but it would be difficult to argue against any of Willey, Turner or Voges. It all really depends on what strategy you feel would give yourself the best chance of winning.

The results of a quick poll on Twitter suggested that people felt that Willey would have been the best option over Voges with just 10% agreeing on Ashton Turner, but that could potentially be affected by the actual outcome.

In the BBL match this morning, who would you have brought in at #5 when Michael Klinger was dismissed?

— Ian DW (@sportdw) December 29, 2016

What actually happened?

Perth Scorchers decided on Ashton Turner, who actually struggled to get off strike against Narine or Rimmington and was dismissed for a very disappointing 1 off 5. As it happened, it should not really have gotten to the 7 off 3 balls as Mitchell Marsh should have hit the ball on which he was dismissed for 6, but it was interesting that it was Voges, then Agar, then Whiteman that the Scorchers opted for as the wickets fell, ignoring David Willey.

Fixing in Tennis - The Public Perception in 2016

Twelve months ago, I ran a survey looking at the public perception of fixing in tennis. It asked people with a range of different interests in tennis, whether it being as a fan, as a trader, as a journalist or even as a current or former player, for their views on fixing in tennis, how it is being perpetrated and what could be done going forward to prevent it. Since then, fixing in tennis has hit the headlines several times - the Buzzfeed investigation in January and the reports that the Tennis Integrity Unit are investigating matches at both Wimbledon and the US Open in particular. Therefore, I thought it would be interesting to run the survey again to see whether the events of the past year have changed people's views. This article will focus on the responses to the set questions, while I will write a follow-up article based on a number of the excellent suggestions and replies in the additional comments section of the survey.

Vitalia Diatchenko is under investigation around suspicious betting patterns during her US Open match this year

Once again, the response to the survey was excellent with 310 completed surveys. Although this was slightly down on last year, it still provides a decent sample to analyse. Of those 310 people that completed the survey, 48.4% identified themselves as tennis fans, 40.0% as tennis gamblers or traders, 6.5% as journalists, 2.6% as current or former players and 2.6% as 'Other'. In addition, there were completed forms from 49 different countries - the majority being from the USA, UK and Australia, but there were completed forms from plenty of other countries, ranging from Costa Rica to Venezuela and Bulgaria to the Philippines.

How serious a problem is fixing?

The first question was simple - how serious a problem do you believe that tennis has with match fixing. This was broken down into five sub-categories: ATP, WTA, Challenger, ITF (Men) and ITF (Women).

The first thing to note is that the percentage of respondents that believe that there is no problem with fixing has decreased at every level of tennis this year. The WTA has the cleanest reputation it would seem, but there are still less than 20% of respondents that feel that it has no problem with fixing. At ATP and WTA level, it is also interesting that fewer people now believe that it has a serious problem, with more people moving to either minor or reasonable problem. The same is true at Challenger level with falls for both no problem and serious problem.

However, the image of the ITF tour has clearly been tarnished over the past twelve months. Over 50% of respondents believe that the men's ITF tour has a serious problem with fixing, up from 47% last year, while the 34.3% that believe the women's ITF tour has a serious problem is well up from last year, where it was below 20%.

What is relatively interesting is if we look at splitting it out based on how people classified themselves. Tennis fans seem to be more suspicious of the ATP and WTA Tours compared to tennis traders and gamblers, who are far more wary of the lower levels.

How many players have been banned?

The next question was simply to see if people were aware of how many players that have actually been banned for corruption offences since the TIU was established back in 2008. The responses are shown below:

In total, there have been 19 players that have been banned for corruption offenses, plus five officials. Of those 19 players, there have been six that have been banned for life (Koellerer, Savic, Krotiouk, Kumantsov, Jakupovic and Chetty) with a further five that have been banned for upwards of 18 months (Klec, Nalamphun, Olaso, Gadomski and Kocyla). The other eight players have been banned for periods of less than twelve months. The five officials that have been banned by the TIU have all been given life bans. Not all of the bans, particularly the shorter ones for the players have been for fixing matches, but they were all banned for what the TIU deemed as corruption offences.

What type of fixes occur?

The next question started to delve a little deeper into how tennis fixes were perceived to be carried out. While the most commonly known fix involves fixing the actual winner of the match, this arguably contains the greatest risk, given that the entirety of the match needed to be scripted. Whilst it may also be the easiest fix to hide due to the fact that there is more money in the betting market for this, it also generally marks the end of a player's involvement in the tournament and limits any further prize money from the event.

There are a number of alternative types of fixes though that can earn an unscrupulous player additional money, whilst not guaranteeing that he loses the match. This could vary from fixing individual sets, particularly the first set, fixing correct scorelines in sets, fixing individual games or points, or if both players are involved in the fix, fixing the opening two sets of the match before playing out the third set to determine who progresses in the tournament.

It is interesting to note that there are now fewer people that believe that the actual match winner is fixed either often or on a regular basis compared to last year. Instead, there is an increased belief that players are tending to fix specific sets and scorelines or individual games within the match. This suggests that people are beginning to acknowledge the idea that spot fixing is far more likely to be the biggest problem in tennis as opposed to the final outcome actually being scripted.

Who is behind the fix?

Having determined that the majority of people feel that fixing does happen in tennis, albeit to varying extents, the next question attempted to determine who was actually behind the fix. Obviously, the players on the court are the ones that actually carry out the fix, but who was the mastermind behind the plan? The percentages add up to greater than 100% because people were allowed to select multiple categories.

This is a very interesting question to compare with twelve months ago. In 2015, the vast majority believed that it was the players alone that were behind the fixes. However, we can see a huge increase in the people that believe that organised crime syndicates are behind fixes in tennis to the extent that it was the most popular answer to this question. Betting syndicates also come out of this looking bad with over half of respondents believing that they are behind certain fixes.

I would suggest that the changes in responses to this question may well have been significantly driven by the findings in the Buzzfeed investigation earlier in the year, which linked several groups based in Sicily, Northern Italy and Argentina to a number of fixes that took place around a decade ago. However, clearly people still believe that organised crime and betting syndicates are still behind fixing in tennis.

As noted last year, one respondent actually suggested that umpires might be behind some fixes and that has been proven accurate with four umpires having been banned in September for manipulating scorelines for betting purposes.

What would help to combat fixing?

The next question focused on a number of potential ideas for combating the problem with fixing in tennis:

The options that received the highest percentage of answers saying that they would definitely help were greater cooperation between the tennis governing bodies and bookmakers, approaching tennis traders to help identify fixes and increasing prize money on the minor tours.

The first option of banning betting on minor tours saw almost identical responses to last year with 28.4% of answers suggesting that it would definitely help, but as mentioned last year, this is simply not a feasible options in the current day. The fact that only 15.7% believed that increased funding for the TIU would definitely help is a fairly damning reflection on the trust that the public have in the TIU, which will be further explored later.

Logic would suggest that increasing prize money at the lower levels is likely to help reduce the incentives for fixing at that level. It would not eliminate fixing by any means as there are likely to still be plenty of players that choose to take the option of the additional income from fixing, but it might reduce the need that some players may feel to stray to that option. Indeed, some players have indicated that certain players have attempted to justify fixing due to the financial difficulties at the lower levels.

The two options that are most supported are the same as those that were indicated last year and are those that look to use existing knowledge of the betting markets and tennis trading - using bookmakers themselves and traders that regularly trade on the tennis markets.

As we learned in the Buzzfeed report earlier in the year, when the TIU was established, they decided not to employ any betting analysts and suggested that betting data and markets should not be treated as evidence of fixing. Given that fixing inherently involves the betting markets, it seems baffling that betting markets should almost be ignored according to the TIU and it seems that greater cooperation with the bookmakers could only help in terms of identifying suspicious matches. However, this has to be a two-way deal with the bookmakers looking to actively help the TIU by reporting suspicious matches, which they do not always appear to do.

As one might expect, of those that identified themselves as tennis traders or gamblers were strongly in favour of approaching tennis traders to help identifying fixes, but all groups were in favour of this option, with not one group falling below 30% answering that it would definitely help.

How much faith do you have in the TIU?

The Tennis Integrity Unit describe themselves as being 'charged with enforcing the sport's zero-tolerance policy toward gambling-related corruption worldwide' and claims it has a 'global brief to protect the sport from all forms of betting-related corrupt practices.'

However, they work in a very secretive manner and there appears to be little confidence in them to actually carry out this brief, not only among fans of the sport, but even among the players themselves. An unnamed player explained how he reported an approach to the TIU, but nothing ever came of it, while Peter Polansky said the following:

"From the chatter around the guys, it sounds like it's something that definitely happens, and quite often. It happens, and there's not a whole lot anyone can do about it"

When even the players do not believe that the TIU can do anything about fixing, it is difficult to see how the TIU can possibly act as a disincentive to fixing in its current form. This question was aimed at determining whether the public had any faith in the TIU to do their job:

The answer would seem to be not. It is telling that exactly zero answers said that they had complete faith in the TIU to reduce the problem of fixing in tennis. At the other end of the scale, almost 30% had no faith whatsoever in the TIU and another 38.9% had little faith. For a body whose sole aim is to protect the sport from betting-related corrupt practices, it seems that virtually nobody has any faith in them to actually carry out their goal.

Level of Proof

The final question focused on the level of proof that should be required for the TIU to impose a ban on a player. The two options were taken from the legal system. The first was 'Beyond Reasonable Doubt', which is generally the level of proof required to validate a criminal conviction in most legal systems. It places the burden of proof on the shoulders of the prosecutor, who must prove that a player has fixed an outcome to the extent that there could be no reasonable doubt in the mind of a reasonable person. The second option was 'Balance of Probabilities', which is more commonly used in civil disputes, which requires that the dispute be decided in favour of the party whose claims are more likely to be true.

To prove beyond reasonable doubt that a player has fixed an outcome is very difficult. Unless you have bank statements showing money from a bookmaker or phone or text records proving a fix took place, it is almost impossible to prove beyond reasonable doubt, even if the betting markets strongly suggest that the outcome was fixed.

There has been quite a large increase in those answering 'Beyond Reasonable Doubt' with a rise of over 10% from last year. One can only speculate as to the reason for this, but one suggestion could be the issues around the Buzzfeed investigation that falsely flagged up the likes of Lleyton Hewitt as likely fixers. The embarrassing nature of that might have led people to feel that stronger evidence is needed before banning players for corruption offences.

Over/Under 2.5 Goals Betting Based on Managers

When it comes to managers, it is pretty well-known that different managers have different styles. There are those managers that like open attacking football and aim to score one more than their opponents, regardless of how many their opponents score, while others prefer to keep it tight at the back and grind out low-scoring wins. Obviously, bookmakers know this just as well as the punters do, but I thought it would be interesting to look at whether it would be possible to look at particular managers and back either over or under 2.5 goals on a regular basis and make a consistent profit.

In this article, I am going to focus on La Liga in Spain. Using data from football-data.co.uk, I have taken every match since the start of the 2012/13 season up until the end of the 2015/16 season, so a total of four seasons of data. There are 34 managers that have managed for at least a season (38 games) in this period, so let us focus initially on those.

Just two managers have managed for the entirety of the four seasons or 152 matches - Atletico Madrid's Diego Simeone and the former Rayo Vallecano and now Granada manager, Paco Jemez. As a contrast in managerial playing styles, there could not be a more divergent pair. In those 152 matches, Diego Simeone's matches have averaged 2.47 goals per game compared with 3.16 for Paco Jemez. 84 of the 152 matches that Diego Simeone has managed in this period went under 2.5 goals, while 95 of the 152 matches for Paco Jemez went over 2.5 goals. We would expect the bookmakers to know this though and adjust the odds. However, did they adjust the odds enough?

It would seem that the answer is no. Had you backed Under 2.5 goals in every match that Diego Simeone had managed in La Liga since the start of the 2012/13 season, you would have made a 9.0% profit over the four seasons. Similarly, had you backed Over 2.5 goals in every Paco Jemez match, you would have made an impressive 15.0% profit in the same period.

Looking in slightly more detail, the vast majority of the return for Diego Simeone actually came in away matches. Simeone has actually seen over 50% of home matches go over 2.5 goals during this period and backing Under 2.5 goals would only have returned 2.9% in home matches. However, away from home, it is a different story. In these matches, backing Under 2.5 goals would have returned a huge 15.1% profit, which suggests that the bookmakers have consistently underestimated Atletico Madrid's tendency to grind out low scoring results away from the Vicente Calderon.

In contrast, backing Over 2.5 goals in matches involving Paco Jemez seems to show little difference whether the team is playing at home or playing away. At home, it would have returned an 18.2% profit, while away from home, it is slightly lower, but still an impressive 11.8%.

Further down the list, a couple of names stand out. The former Villarreal manager, Marcelino, would have returned 15.1% from Under 2.5 goals, driven by low-scoring games both at home and away, while Fernando Vasquez, Joaquin Caparros and Eduardo Berizzo have also shown profits of above 10% from the Under 2.5 goals selection.

In contrast, despite regular short-odds on Real Madrid scoring more than 2.5 goals, backing Over 2.5 during Carlo Ancelotti's reign would actually have returned 10.6% profit with 59 of 76 matches going over the line, while Unai Emery would have returned 7.7% profit from Over 2.5, driven particularly by matches at home.

Fran Escriba is a particularly interesting case. The former Elche and Getafe manager, who is currently at Villarreal appears to be nothing notable when you look at the overall figures. Indeed, a very small loss on both Over and Under 2.5 goals almost suggests that his matches are priced up accurately. However, if you split it down to home and away matches, there is a big difference. Backing Under 2.5 goals in matches than Escriba has managed at home would have returned a massive 31.0%, but away from home, backing Over 2.5 goals would have returned a similarly huge 27.2%. It seems that he oversees high-scoring away matches, but keeps things very tight at home. It might be one to watch at Villarreal this season.

This is obviously pretty basic analysis and it does not take into account anything apart from the manager. However, it throws up a few interesting angles that it might be worth thinking about when it comes to looking at the Over/Under 2.5 goals market in Spain.

The full table for all managers with 38+ matches is available here. If you want information on any other managers from Spain during this period, I have the stats, so just let me know...

How do players approach break points on their own serve?

Tennis is a sport that is often decided by the finest of margin and many times, we will see a match where there are barely a handful of points that separate the two players. However, some points are clearly more important than others and break points are some of the most important points of all. I thought it would be interesting to look in more detail at how players deal with break points on their own serve and how they go about trying to save them.

The data for this comes from the Match Charting Project at TennisAbstract. Now, while this is not a complete record of all matches for all players, for a growing number of players, there are enough matches charted to be able to start to look in more detail and begin to draw some conclusions. In total, there are 15,885 break points across 409 players and 2,475 matches, which is certainly enough of a sample to get going with.

The first thing to focus on is the first serve. Obviously, all players tend to win a higher percentage of points behind their first serve compared to the second serve. On a non-break point, the average first percentage of first serves in is 61.5%, which is higher than the 59.6% on break points, which is not really that surprising. We would expect the added pressure on break points to mean that players miss slightly more first serve. However, let us look in slightly more detail on a player-by-player basis:

The table shows the change between a player's 1st serve percentage on a break point compared to a non-break point. We can see that David Goffin has the biggest difference, increasing his 1st serve percentage by 5.9% on a break point compared to a normal point, followed by Juan Martin Del Potro, John Isner, Thomaz Bellucci and Bernard Tomic rounding out the top 5.

At the other end of the scale, we see Tomas Berdych at the bottom, with his first serve percentage dropping by 11.1% on break points. He is joined at the bottom by Viktor Troicki, Lleyton Hewitt, Fabio Fognini and Richard Gasquet.

What is interesting to look at in conjunction with the first serve percentage is the change in those points actually won behind the first serve. Here, we see a few interesting differences. We can see that David Goffin, despite hitting significantly more first serves on break point, actually wins far fewer points behind that first serve. Based on this, one might conclude that he looks to take a bit off his first serve and ensure that he gets the ball into the court and hopes that his superior ability in rallies will make up for the decrease in cheap points on serve. Indeed, we see that the percentage of aces and unreturned serves falls for Goffin, but so does the percentage of doubles faults that he serves. Basically, he goes for a very risk averse approach to serving on break point.

At the other end of the scale, we can look at someone like Viktor Troicki. We see that his first serve percentage drops by 7.3%, but he actually significantly increases the percentage of those points that he actually win. It seems as though Troicki is willing to risk going for a big serve on break point at the expense of missing a few and we do see that his ace and unreturned serve percentage does indeed increase on break points by 1.5%.

So, let us now look at how players win break points on their own serve once they are in a rally:

While we hypothesised earlier that David Goffin was very risk adverse when it came to getting the ball in-play, we can see that he balances this out with a slightly more dominant strategy once he is in a rally. The percentage of points won by Goffin hitting a winner or forcing an error increases by 6.3% on a break point compared to a normal point, suggesting that he looks to dominate the rallies slightly more and look to decide the point himself.

We also see Lleyton Hewitt, who appeared to look to go for a bit more on his first serve, presumably with the confidence that he would fancy himself in a rally if necessary on his second serve. We can see that Hewitt really boosts his percentage of winners on break point, suggesting that he prefers to decide break points himself, rather than rely on his opponent.

At the other end of the scale, we see Roberto Bautista-Agut and Gilles Simon, who appear to prefer to simply get the ball into play and wait for the error from their opponent, rather than risk going for the big shot themselves. However, it appears that the two players have very different success rates here. Gilles Simon sees a big increase in the percentage of points won via opponent unforced error, while Roberto Bautista-Agut actually sees a decrease. One wonders then whether Bautista-Agut takes this risk averse strategy too far and actually makes it easier for his opponent to hit plenty of winners on the big points, rather than giving them time to make mistakes.

We also see Roger Federer and Novak Djokovic at the bottom here - it appears that they both fancy themselves to outlast most players in a rally situation and are happy to cut down on any mistakes that they might make in exchange for waiting for their opponent to crack.

Finally, let us look at how players tend to lose points when we are in a rally on break point:

It is interesting to see that John Isner topping the list here. Isner actually increases his points won by aces and unreturned serves by 5.8%, but we also see here that he is able to reduce the percentage of points that he loses via unforced errors as well. It seems as though he goes big on the first serve to try and win the point early, but if that does not succeed, then he is happy to go more risk averse and make sure that he does not throw the point away himself with an unforced error.

The presence of David Goffin toward the bottom backs up our earlier theory that he plays conservative on the serve to ensure that he gets into a rally, then plays far more aggressive during the rally itself, increasing both his percentage of winners and unforced errors, which could easily increase as a result of looking to hit bigger shots.

One name that it is worth noting is Bernard Tomic. He appears near the top of all three tables - he hits more first serves, wins more of those first serve points, hits far more winners and hits fewer unforced errors on break points. That is a remarkable combination of statistics for a player that is not exactly renowned for his mental strength. Perhaps the pressure of break points concentrates his mind more?

On the flip side, Roberto Bautista-Agut does not come out of this looking great. He hits slightly more first serves, but a 10.2% decrease in first serve points won suggest that he takes a lot off the first serve. He hits fewer winners himself, but allies that with a big increase in unforced errors and also loses more points to opponent winners. It seems as though he simply plays far too passively and allows his opponent too many chances to hit winners and force the error.

Going forward, there are two areas that I intend to look at. Firstly, it would be interesting to look at serve placement in association with the first serve stats that we have seen already. One would imagine that those players that hit more first serves would hit more into the middle of the box as safer serves, but it would be interesting to see. The other thing is to look at how a player's risk profile translates to when they create break points on their opponent's serve. Do the risk averse players on their own serve also play conservatively on their own break point chances or are there difference?

Note: you can see the summary data for all players with 100+ break points faced here...

Looking at T20 Batsman-Bowler Combinations

Having looked previously at some of the top ranked T20 batsmen and bowlers in cricket based on my new ranking system, I thought it would be interesting to delve slightly deeper into a few of the players and take a more detailed look at how certain batsmen perform against certain bowlers, and vice versa.

Obviously, when we are looking at specific pairings of batsmen and bowlers, we are looking at relatively limited sample sizes, but it should still give us an idea of whether certain batsmen enjoy facing certain bowlers or whether they have particular bowlers that they struggle against.

Let us start off with the #1 rated batsman in T20 cricket - Chris Gayle. Being a player that has played a huge amount of T20 cricket over the past five years, there are actually no fewer than 38 bowlers in this period that have bowled 30+ legal deliveries at Gayle (as an aside, there are a grand total of 329 different bowlers that have bowled at least one delivery to the legendary West Indian in my database). The table below shows the highest strike rates for Gayle against particular bowlers:

Chris Gayle is a fearsome hitter of spin bowling, so it is no surprise to see a host of spin bowlers with some awful figures against him. Glenn Maxwell has conceded no fewer than 70 runs in 30 deliveries against Gayle, while Samuel Badree, the #1 rated bowler in the ICC ratings and #13 in my ratings, has also struggled, conceding a boundary every 2.33 deliveries. Dwayne Bravo has bowled a huge 79 balls to Chris Gayle, conceding 21 boundaries, but dismissing him on six occasions.

At the other end of the scale, Lasith Malinga has conceded just 29 runs in 53 balls at Gayle, which is really very impressive. Admittedly, he does benefit from bowling to Gayle early in his innings before he really gets going, but it is still hugely admirable.

Three spinners in particular here really stand out - Mohammad Hafeez, Sunil Narine and Ravichandran Ashwin. Given the way that Gayle can destroy spin bowling, the fact that the three of them combined have conceded just 102 runs in 144 balls at Gayle with just 9 fours and one six in those deliveries is very impressive. Whether Gayle has a real problem against those bowlers or whether he has the confidence in himself to just see off the star bowlers of the opposition, the data cannot tell us, but it is interesting.

So, if Chris Gayle struggles to score off Lasith Malinga, let us look at the batsmen that can. The table below shows the top 10 SRs of players to have faced at least 24 balls from Malinga:

In AB de Villiers, MS Dhoni and Shahid Afridi, we have a trio of three very destructive hitters at the end of the innings that have been able to score runs off Malinga, often mentioned in the debate about the greatest death bowlers in the history of T20 cricket. However, interestingly it is Marlon Samuels that tops the list, having hit a huge five sixes off Malinga in just 28 deliveries (all the other batsmen to have faced 24+ balls have 16 sixes combined off 956 balls). It was his memorable innings of 78(56) in the World Cup T20 Final in 2012 that did the damage here, when he took 39 runs off 11 balls from Lasith Malinga in what would be a match-winning innings.

So, we saw earlier that another bowler that Gayle struggled against is Sunil Narine, the #2 bowler in my ratings. However, he is far from the only batsman to struggle against Narine. Indeed, of the 29 batsmen to have faced at least 30+ deliveries from Narine, just 9 of them have a strike-rate of greater than 100.0. There are only four batsmen to have a strike rate of greater than 130.0 against Narine - JP Duminy and David Warner (both 133.3), AB de Villiers (140.0) and Suresh Raina (147.4).

There are actually no fewer than 7 of the 29 batsmen that Narine has over 50% dot balls against as well - Martin Guptill (51.5%), Dwayne Bravo (51.6%), Chris Gayle (51.9%), Marlon Samuels (53.1%), Naman Ojha (55.9%), Darren Sammy (57.6%) and Yuvraj Singh (64.4%). Interestingly, we find four of Narine's West Indian teammates in here, which suggests that facing him regularly in the nets does not seem to help in terms of being able to score runs off of him.

In Malinga and Narine, we have looked at two of the top T20 bowlers in world cricket. One name that has appeared in being able to score quickly off both of them is AB de Villiers, the #5 rated batsman in my rankings. Let us look at bowlers that he has scored particularly well against:

It is safe to say that there are more than a few bowlers that AB de Villiers has obliterated over the past five years. His South African teammate, Dale Steyn, is an interesting one - for a bowler than scored reasonably well in the economy part of the bowling ratings, he has been destroyed by AB de Villiers, conceding an extraordinary five sixes from just 19 balls.

It turns out that there are just six bowlers with 18+ balls at AB de Villiers to restrict him to a SR of less than 100.0. Indeed, Piyush Chawla has conceded just 27 runs from 30 balls against de Villiers, while dismissing him three times (joint-highest with Ashwin, Mathews and Balaji).

However, when it comes to destructive batsmen, there are few more devastating than Andre Russell. The table below shows the 11 bowlers that have bowled 20+ balls to Russell in the past five years:

With the exception of Sunil Narine, Andre Russell has a SR of upward of 150.0 against every bowler to have bowled regularly to him. Indeed, against five of the eleven, he has a SR of above 200.0, which is quite simply incredible. That Sunil Narine has only conceded a single boundary in 30 balls to Andre Russell just goes to show why he is undoubtedly one of the all-time great T20 bowlers.

Which T20 Batsmen Are Fast Starters?

In T20 cricket, getting off to a good start can be very important when it comes to setting a formidable total, but at the same time, different players need different amounts of time to really settle in before they can really start to play their shots.

In this article, I want to look at a selection of 20 different opening batsmen from seven different countries, all of whom have played plenty of T20 cricket across multiple different competitions over the past five years. In particular, I want to focus on the first 30 deliveries that they face. Obviously, the majority of T20 innings from opening batsmen are likely to last less than 30 deliveries and once a batsmen has reached his 31st ball, you would hope that he is in a position to really go on the attack, but we will look at that in more detail in a future article.

To begin with, let us get an overview of all 20 batsmen and their overall strike rate after each delivery in this 30-ball spell:

As we can see, virtually all the batsmen rapidly increase their overall strike rate over the first 10 balls that they face, at which point it begin to flatten out for the majority of batsmen. What this chart effectively shows is the score that we would expect a batsman to be on having faced a set number of deliveries. For example, with a strike-rate of 104.2 after 10 balls, we would expect Ahmed Shehzad to be on 10.42 runs, whereas with a strike-rate of 123.1, Aaron Finch would expect to be on 12.31 runs.

Obviously, the most aggressive batsmen also tend to have a higher risk of being dismissed, so in terms of an opening partnership, you might be looking to pair an aggressive batsmen that will get the scoreboard moving immediately with a slightly more gradual batsman, who may need a few balls to really settle before steadily increasing his strike rate.

If you have two slow starters, you potentially run the risk of finding yourself in a concerning position if they both fall after around 10-15 balls each at a run-a-ball and it increases the pressure on the players coming in afterwards.

So that initial chart is quite difficult to pick out individual players, so let us take a look at a few groups of players at a time. Firstly, we shall look at the four English players in the group - the current England opening pair of Alex Hales and Jason Roy, plus two former England internationals in Luke Wright and Michael Lumb:

We can see that the four players split into two pairings in this chart. The pair of Jason Roy and Alex Hales are both very fast starters, not only compared to the other English players, but compared to all of the opening batsmen in the sample. After five balls, Roy and Hales are 3rd and 4th respectively, but we can see that Luke Wright and Michael Lumb take a couple more deliveries to get moving.

Having said that, we can see that both Michael Lumb and, particularly, Luke Wright, increase their strike rate rapidly after the first couple of deliveries and it is also interesting to note that all three of Roy, Lumb and Wright are among some of the faster scorers through 20 deliveries. One concern for Alex Hales might be that his eventual strike rate is only around the middle of the pack, but at least he does reach that strike rate rapidly rather than eating up deliveries.

Next, let us look at the Indian batsmen. The immediate concern for India is that all their openers in this sample - Virat Kohli, Shikhar Dhawan, Rohit Sharma and Ajinkya Rahane - are all close to the bottom of the group in terms of strike rate. None of them are particularly rapid starters and none have a particularly high top gear in terms of making big scores in general. Admittedly, Rohit Sharma has hit a couple of incredible innings over the years, but those are not all that common.

The fact that none of the openers are able to constantly get India off to a flying start and with Rohit Sharma having the highest strike rate of the quartet after 30 balls at just 124.7, there is a lack of real dramatic acceleration, it puts a lot of pressure on the middle-order batsmen to score quickly from the start.

Chris Gayle have long been known as a relatively slow starter, but once he gets going, he accelerates well and importantly, continues to accelerate throughout the innings. Beyond the 30 deliveries in the chart, he continues to speed up reaching a final strike rate of an incredible 153.0. The concern here for the West Indies is finding an opening partner that can get the innings moving to give Gayle the time that he seemingly wants to get his eye in.

Neither Dwayne Smith or Lendl Simmons would appear to be the ideal foil for Gayle. In particular, Lendl Simmons is a very slow T20 opening batsmen and does not even break the 100.0 strike-rate mark until his 15th delivery. When partnered with Chris Gayle, this can lead to a very slow start to the innings, which then puts pressure on Gayle to convert his innings. With the big hitting further down the order, they can often get away with this, but finding a fast starting opening batsmen could improve them further. Time will tell whether Evin Lewis or Johnson Charles can be that player.

When it comes to fast-starters, there are very few in T20 cricket that are better than Aaron Finch. He is regularly able to get the innings off to a flying start, which gives his partner the opportunity, if needed, to build into his innings. The fact that he seemingly plateaus very quickly might raise the odd question about his stamina, but he is still a valuable opening batsman. He also makes a good foil for David Warner, who we can see starts slightly slower, but builds to a very good strike rate.

Another fast-starting opener, which will come as a surprise to very few, is New Zealand's Brendon McCullum. Now retired from international cricket, he is a very effective and fast-scoring opening batsman, who will undoubtedly be in great demand from franchises around the world, particularly given his ability either behind the stumps or in the field.

While he is pipped slightly over the first five deliveries, there is no opening batsman that can live with AB de Villiers. The South African is one of the greatest T20 batsman in history and the strike rate that he peaks at after 30 deliveries is streets ahead of his closest contender, Jason Roy. His rapid start is a perfect foil for his South African partner, Quinton de Kock, who is one of the slower starters in this sample, but he steadily builds to a very solid strike rate as his innings progresses.

The Effect of Different Grounds in T20 Cricket

Given all of the many T20 competitions that take place around the globe in the modern day, there are a huge number of matches taking places each year at many different grounds. While it sounds obvious, there are very few grounds that play similarly with pitches varying in preparation, boundaries being of different lengths and even different weather conditions affecting the score that teams should be aiming for.

In recent articles on both batting and bowling ratings, I have mentioned that I adjust expected runs by the ground at which the match is being played and in this article, I intend on looking in a little more depth at how different grounds vary in a number of ways. Even grounds at which the par score are the same can look quite different once you look in detail at how that par score might be expected to come about.

Firstly, a quick mention of the data used in this article. In my database of ball-by-ball information, there are just over 150 different cricket grounds that have hosted matches in the past five years - of these 150+ grounds, there are 96 that have seen at least 600 first innings deliveries (i.e. five full innings of deliveries), so we shall narrow the data down to these grounds for the analysis here.

So, let us first look at the average first innings scores at these grounds. The table below shows both the top 10 and the bottom 10 highest-scoring T20 grounds and the average first innings scores:

Now, most of the grounds at the top of this list are not likely to be too much of a surprise. The M Chinnaswarmy Stadium, home to the Royal Challengers Bangalore in the IPL, is renowned as a batting paradise, while Seddon Park was the venue for Richard Levi's record-setting T20 century back in 2012. Similarly, the likes of St Lawrence Ground, Eden Park and Trent Bridge are ground that are well-known to suit batsmen.

At the other end of the scale, we see an interesting number of grounds located in the West Indies. Providence Stadium in Guyana has an incredibly low average first innings score, while the Beausejour Stadium in St Lucia and Sabina Park in Jamaica also feature in the bottom 10.

Now, let us look at which grounds see the most sixes. Logically, we might imagine that there is a pretty strong relationship between high-scoring grounds and six-hitting. To an extent, this is true. The top five grounds in terms of balls/6 are Seddon Park (12.9 balls/6), Central Broward Regional Park Stadium (14.6), Eden Park (14.6), M Chinnaswarmy (15.0) and Wanderers Cricket Ground (15.0), all of which appear in the top 10 highest-scoring grounds.

However, there are a couple of interesting ones to look at. St Lawrence Ground in Canterbury actually only ranks 41st out of the 96 grounds in terms of balls per six, only seeing a six in the first innings every 24.0 deliveries, implying that there will be an average of five 6s in each first innings.

In contrast, we find the Beausejour Stadium, ranked 92nd out of 96 in terms of average score appearing at number 22 in terms of balls per six, seeing a six every 21.5 deliveries, while Sabina Park follows at 23rd in balls per six.

The table below shows the top 10 and bottom 10 grounds in terms of deliveries per six:

So, if there are a relatively low number of sixes being hit at St Lawrence Stadium in Canterbury, one might surmise that there are plenty of singles, twos and boundaries being hit and this does seem to be the case. We find that Canterbury shows up ranked 3rd in terms of balls/4, which could either be a reflection of the type of batsmen that Kent tend to select in their T20 team or the fact that there are long boundaries that it is hard to clear. It also appears ranked 1st in terms of the fewer dot balls at just 33.2%.

The next question is whether facing spin or non-spin bowling tends to make a difference at certain grounds. The table below shows a selection of seven grounds and the balls/6 against spin and non-spin bowling:

Being one of the biggest six-hitting grounds, it is no surprise to see that the M Chinnaswarmy Stadium is a ground where it is relatively easy to hit sixes off almost any type of bowling, particularly when you have the likes of Chris Gayle and AB de Villiers playing there regularly. Similarly Warner Park is a ground where sixes can be easily hit off all types of bowling.

The Dr Y.S. Rajasekhara Reddy ACAVDCA Cricket Stadium, a venue used by a number of IPL franchises over the past five years, is a ground where we can see a large discrepancy between the ease of six hitting off spin bowling compared to non-spin bowling. The Maharashtra Cricket Association Stadium in Pune is another ground where we see this discrepancy between spin and non-spin bowling.

The Brisbane Cricket Ground interestingly appears to be easier to hit big shots off the quicker bowlers - a trend that we also see at the Sinhalese Sports Club Ground in Colombo, which may reflect the fact that Sri Lanka are generally known for producing quality spin bowlers as opposed to quicker bowlers.

Finally, we see a ground like Grace Road, where it seems that it can be tricky to hit boundaries off any type of bowling with figures upward of 30.0 balls per six against both spin and non-spin bowling.

Who are the best T20 Bowlers in World Cricket?

Recently, I looked at how we could rank the best batsmen in T20 cricket, comparing two existing rating systems and developing my own system to compare and contrast with the ICC ratings and the Cricket Ratings systems (here). Obviously though, there are two crucial elements to cricket though - batting and bowling.

In this article, I want to take a look at the best bowlers in T20 cricket. As before, let us first look at the ICC, who have developed their own rating system to grade bowlers. Their current rankings are shown below:

As with the batting rankings, this only takes international matches into account and arguably this top 10 might cause more arguments than the batsmen. One of the hardest aspects of grading bowlers in T20 is deciding on the balance between the weights given to economy and wicket-taking. As the ICC mention about their rankings, "while taking wickets is still important in T20 cricket, the T20 rankings give more credit to a bowler for economy. A bowler that takes 0-15 off 4 overs gets more credit than one who takes 2-35.

This weighting toward economy is perfectly valid, but if you are only taking the pure figures, one would therefore expect bowlers that bowl during the powerplay at the start and during the death overs to be overly penalised by this system. Indeed, we see that the majority of the bowlers in the top 10 of the ICC rankings are spinners that will bowl most, if not all, of their overs during the middle overs.

So, let us move on and take a look at the Cricket Ratings system. As described previously, this takes domestic competitions into account and adjusts for the quality of competition in each different event to allow performance to be compared across different countries. It breaks down performance into two aspects, adjusted average and adjusted economy. The rankings are shown below:

Now, we see that there are only two bowlers that appear in the Cricket Ratings top 10 that also appeared in the ICC top 10 - Sunil Narine and Ravichandran Ashwin. Here, we see an increase in fast bowlers appearing toward the top of the list with Lasith Malinga, Mustafizur Rahman and Bhuvneshwar Kumar in particular rating highly. There are also a couple of unexpected names in this list. Benny Howell, Kevin O'Brien and Rikki Clarke are names that have performed well in the T20 Blast in recent seasons that might have gone somewhat under the radar.

It is interesting here that there appears to be equal weighting given to wicket-taking and economy, which is in contrast to the ICC system.

Now, my system is based on my T20 database that contains almost every T20 match played around the globe in the past 5 years for which there is ball-by-ball data. As with both the ICC and Cricket Ratings systems, my system takes two aspects into consideration - wicket-taking and economy.

The economy aspect is based around the number of runs that a bowler concedes compared with the expected runs that an average bowler would concede on that delivery. For example, off the opening ball of the match, the average T20 bowler would be expected to concede 0.78 runs, while if he were bowling the final ball of the final over, he would be expected to concede 1.72 runs. By comparing what a bowler should concede with what he actually concedes, we can compare economy rates regardless of when during the innings the bowler was actually bowling.

In addition, I adjust the expected runs based on the ground at which the match is being played and for the batsman that is facing the ball. For example, if you were bowling the first ball of the 19th over to Khaya Zondo at Queen's Park Oval, you would expect to concede fewer runs than bowling the same ball to Chris Gayle at the M Chinnaswarmy Stadium.

For the wicket-taking aspect, I again compare the actual wickets taken to the expected wickets, taking into account once again, the batsman and the stage of the innings. For example, you would expect to take 0.024 wickets with the first ball of the first over of the innings, but bowling the last ball of the innings, you would expect to take 0.134 wickets. Similarly, you would expect that to vary depending on whether you were bowling to Virat Kohli or to a #11.

As with the ICC system, I have decided to weight my ratings slightly more toward economy, rather than wicket-taking, simply due to the fact that the confidence interval for economy is narrower than wickets due to the relatively low frequency of wickets compared to runs. The top 10 from my ratings are shown below:

Based on my ratings, Australia's Mitchell Starc is the best T20 bowler in world cricket. Interestingly, Starc did not show up in either of the previous top 10 rankings, but I imagine that plenty of people would not be surprised to see him near the top of the list. He performs well in economy and he is one of the most dangerous wicket-taking bowlers in T20 cricket.

Another Australian, although less-heralded, Jason Behrendorff, appears second in my ratings, as he did in the Cricket Rating system. It would be interesting to see Behrendorff tested outside of the Big Bash and, at only 26-years old, there is still time for a franchise in another competition to take a chance on what would likely be a relatively cheap player.

There is likely to be little surprise to see Sunil Narine rounding out the top 3. His economy rating is simply outstanding and his low wicket-taking performance is likely partially affected by batsmen simply looking to play out his overs without taking any risks.

The trio of Benny Howell, Azeem Rafiq and Liam Dawson represent the T20 Blast strongly here and Dawson's performances have been rewarded recently with a T20 England debut. Benny Howell is a name that has appeared on both my system and the Cricket Ratings system and he is one that England should maybe keep an eye on. Strong performances in both the economy and wicket-taking aspects suggest that he is a very talented T20 bowler.

As with the batsmen ratings, let us take a quick look at the bottom 10 in the ratings. These are shown below:

This does not make excellent reading for India with both Ishant Sharma and Umesh Yadav, both of whom have played internationally for India and who are both regulars in the IPL, showing up in the bottom 10. Indeed, Ishant Sharma scores very poorly on both aspects, suggesting that he is expensive and rarely takes wickets.

Regarding a couple of the other names that showed up highly in the ICC ratings, we find Samuel Badree at #13 in my rankings, Jasprit Bumrah way down at #123, Imran Tahir at #59 and Kyle Abbott actually shows up a long way down at #232, well below the average T20 bowler.

Comparing a couple of names from the Cricket Ratings system, Lasith Malinga is at #23, Kevin O'Brien is at #51, Bhuvneshwar Kumar is at #57 and Ravi Ashwin is at #24. Generally, there appears to be slightly more consistency between my ratings and the Cricket Ratings rankings than with the ICC rankings.

Finding the Best T20 Batsmen in World Cricket

In any team sport, one of the more difficult aspects is determining the influence of individual players within that team. In football, drawing out which players are really driving the team and which players appear good purely as part of being part of a successful system can be very difficult due to the fluid and interconnected nature of the sport. However, in T20 cricket, it is easier, particularly if we view a match as a series of individual contests between batsman and bowler.

The ICC has developed its own rating system to rank which the best international T20 batsmen are (available here). The current ranking from their system is shown below:

Now, while this system only takes into account international matches, it does not seem too bad. Given his form recently, there are not too many people that would argue with Virat Kohli topping the rankings, while we see Joe Root, Alex Hales and Chris Gayle in the top 10, all of whom appeared in the T20 World Cup Final earlier this year. However, it also feels as though there are a number of big T20 players that are missing from the top 10.

Recently, a new website, Cricket Ratings, set-up by Dan Weston, released their version of a top 10 T20 batsmen that uses data from domestic T20 competitions around the world as well as international matches. It also adjusts for the different level of quality in competitions around the world to enable, for example, performances in the IPL to be directly compared with performances in the T20 Blast. It also breaks down the performance into two aspects - adjusted average and adjusted strike-rate. The top 10 players from the Cricket Ratings system are shown below:

Again, we see Virat Kohli topping the ratings here, but there are a number of new names that appear here. Ab de Villiers and David Warner are the two standouts here that were missing from the ICC version and if you asked cricket fans, I would suspect that they would include those two names in their top 10. There are also a couple of more unexpected names appearing here, particularly Yusuf Pathan and Reeza Hendricks.

Now, over the past six months, I have been building up a database of ball-by-ball T20 data, which has enabled me to come up with my own rating system.

Similarly to the Cricket Ratings system, my rating system is built around two aspects - average and strike rate. Clearly, any top T20 batsman should be strong in both of these areas - it is no good having a high average if you only score at a strike rate of 100.0, but similarly, there is no point in having a strike rate of 150.0 if you generally only last a couple of balls.

In my model, the strike-rate aspect is based around the concept of comparing the runs that a batsman actually scored against the runs that a batsman would be expected to score. This run expectation is derived based on a number of factors, including the ground, the time of the innings and the quality of the bowler. For example, if a batsman is playing at the M. Chinnaswamy Stadium in Bengaluru, facing a ball in the final over of the innings bowled by Ishant Sharma, they would be expected to score more runs off that delivery than if the same batsman was facing the first ball of the seventh over at Sabina Park against Sunil Narine. By comparing the runs that a batsman scored off each delivery compared to the expected runs, we can see which batsmen score at a higher than expected rate.

The average aspect is based around looking at the runs scored per innings and the runs scored per dismissal, again adjusted by the ground and the quality of bowling. For example, if a batsman had averaged 30.0 runs per dismissal, but most of the bowling that he had faced was against low-quality county bowling, he would be marked down compared to a player with the same average, but who had faced the likes of Sunil Narine and Mitchell Starc on a regular basis.

Having explained the basics of how the rating system works, here are the top 10 T20 batsmen from my model:

Chris Gayle actually tops my rankings, although Virat Kohli maintain a top 2 place. It is the incredible strike-rate of Chris Gayle that draws him above the Indian in this ranking. Michael Klinger is a name that appears in third place in my ratings that was conspicuously absent in both the prior rating systems. I would surmise that his absence in the previous systems were due to Australia's bizarre reluctance to pick him at international level (ICC Rating) and the fact that the majority of his appearances have come in the T20 Blast and Big Bash, where the quality is deemed lower than the IPL (Cricket Ratings). David Warner and AB de Villiers round out the top 5 in my ratings.

As my data is based around a weighted average of performances over the past five years, the name of Phillip Hughes appears at number six. As all cricket fans will remember, Hughes tragically passed away in November 2014 having been struck by a bouncer, so unfortunately we shall never find out whether he would have gone on to become one of the T20 great batsmen.

We find the South African pairing of Quinton de Kock and Hashim Amla, England's Jason Roy and Australia's Usman Khawaja also appear in the top 10. Jason Roy is an interesting one as we can see that while his longevity in terms of his innings are nothing all that special, but he does have a remarkable strike-rate part of the rating, showing his ability to score at an impressive rate.

While the top 10 is interesting, we can also look at the bottom 10 to spot some of the worst T20 batsmen in world cricket. These are as follows:

We find the likes of Dinesh Chandimal, the former Sri Lanka T20 captain, who actually dropped himself during their successful 2014 World Cup T20 triumph, and Manoj Tiwary, who has been a regular in the IPL and has represented India at international T20 level. However, no player is ranked as badly as South African, Khaya Zondo, whose combination of dreadfully slow scoring and poor average means that he is officially the worst T20 batsman in the world based on my rating system.

From an England perspective, while Jason Roy was the only batsman in the top 10, there are a number of other Englishmen in the top 25 with Sam Northeast (#12), Luke Wright (#14), Joe Root (#21) and Michael Carberry (#23) also suggesting that England does have plenty of T20 batting talent at their disposal, although interestingly, Roy and Root are the only two that actual form part of England's T20 team. While the time has probably passed for Luke Wright and Michael Carberry, it will be interesting to see whether Sam Northeast gets an opportunity in the coming years to cement a place in England's middle-order.

Finally, let us see how some of the names that appeared in the other ratings perform in my system. In the ICC ratings, we saw the likes of Aaron Finch, Martin Guptill and Faf du Plessis in the top 5, although they drop to rankings of 11th, 42nd and 66th in my ratings. In the Cricket Rating system, it is interesting that while there is agreement on a number of names, there are strong differences on some of the others. In particular, we saw the Indian pairing of Yusuf Pathan and MS Dhoni inside the top 10, but they drop to 223rd and 155th in my ratings, which raises the question of how the IPL is weighted in the two different systems.

Tennis Stats Mailbag - Edition 1

It has been a while since I wrote much about stats in tennis. There are a number of reasons for this, but one being that I was struggling to think of topics to write about. As a result, it seemed like an interesting idea to ask around my Twitter followers for some ideas of what they might like to know. I got a number of responses and have picked a selection of them to answer in this article.

@sportdw do u know if there is a higher instance of set 2 bagels in tournaments the week before a slam? Lots of tanking going on seemingly

— Rory O' Keeffe (@rokky90) May 18, 2016

The idea that there is plenty of tanking going on the week before a Grand Slam event has been around for a long time. The theory is that higher ranked players will generally want to prioritise the slam events due to the better chance of picking up prize money and ranking points.

Firstly, if we address the actual question of whether there are more second set bagels, we find that in ATP events not in the week before a slam, 3.3% of matches that finish in straight sets see a second set bagel. In the week before a slam, 3.0% of matches that finish in straight sets see a second set bagel. There is very little different here, and indeed, we also see virtually no difference in 6-1 second sets either or even the percentage of matches that finish in straight sets.

However, one difference that we do see is the number of favourites that lose in straight sets. In an average ATP tournament not in the week before a slam event, we see 45.8% of wins by outsiders being completed in straight sets. However, in the week before a slam, this jumps to 59.1%, suggesting that there may be an element of favourites not putting everything into trying to fight back if they go down by a set and a break.

From a betting perspective, can we see any profit in backing against the higher ranked players in this week before a slam? Well, if you had £10 on every match since the start of 2010 where a non top-20 player was against a top-20 player in the week before a slam, you would have won £189.70 at an impressive return of 10.4%. Indeed, if we break this down further, if you had backed non-top 20 players against top 10 opponents, you would actually have lost £46.20. It seems that either the top 10 players only enter these events if they intend to try and win them or that even if the top 10 players are not giving it everything, they are still good enough to win. Instead, it is the players ranked between 11 and 20 that are the ones to oppose in this week - a strategy that would have returned £235.90 from £10 stakes at a 19.5% return since 2010.

@sportdw Murray vs Djokovic rally duration. Murray win more of the longer rallies?

— Mark Wilkins (@biscuitchaser) May 19, 2016

Novak Djokovic and Andy Murray are arguably the two best returners in the game and their fitness and ability gives them an advantage in long rallies. However, the question of which player tends to come out on top in long rallies between them is an interesting one.

Using the data from the Match Charting Project, we find 13 matches between the pair with information on rally lengths. The data can be summarised as below:

We can see that the longer rallies of 10-20 shots, there is virtually nothing between the two players. Of the 452 rallies of between 10 and 20 shots in the 13 matches, we find that both players have won precisely 226 points each. Djokovic appears to have a slight edge on the seriously long rallies, but a sample of only 109 points means that it could be slightly less reliable.

Instead, it is when Djokovic is able to keep the points shorter that he has the advantage over Murray. Of points between 4 and 9 shots in length, Djokovic wins 54.7%, which is a significant difference and is where his success over Murray has come from - Djokovic is able to attack early in the point and end them early.

@sportdw tie breaks; when serving on the first change of ends, do players have a higher likely hood of losing set? E.g. loss of rhythm

— TomDUK (@TomDUK1) May 20, 2016

If we look at the ATP, we find that the percentage of players that are serving at the first change of ends in a tiebreak goes on to win the tiebreak on 47.5% of occasions. This could possibly suggest that there is a very slight impact from this.

However, if we look at the percentage of points that are won by the player serving at this stage in the point before the change of ends and the point after the change of ends, we see very little difference. The server wins 64.2% of the points immediately before the first change of ends compared to 64.6% of the points immediately after the change of ends.

Indeed, we actually see that the percentage of aces increases from 8.0% to 9.6% following the first change of ends and the percentage of double faults drops from 3.3% to 2.7%, suggesting that the slightly longer break may actually benefit the server, giving him the opportunity to focus his mind on his upcoming serve.

@sportdw which players have had the largest increase in return points won and if it is sustainable?

— snag97 (@orichimaaru) May 20, 2016

The top 5 players with the biggest increases in return points won in the top 50 in the world rankings are Guido Pella, Ricardas Berankis, Milos Raonic, Richard Gasquet and Nick Kyrigos.

This is an interesting list. Guido Pella has won 6.9% more return points at ATP level in 2016 as he did in 2015, although he only played a handful of matches last year and mostly on his less favoured surface. On clay, he dominated at Challenger level in 2015, racking up a 45-14 record with four titles and he has really carried this form into 2016 reaching the final in Rio de Janeiro, the quarters in Nice and Bucharest and a third round run at Indian Wells.

As to whether he can keep up these improved number, it is debatable. He has been very efficient at beating players ranked below him this year with a 9-3 record and 40.8% of points won on return. However, against players ranked above him, he is just 3-8 and 34.8% won on return. So, it seems as though he has a level and while he may be able to keep up his improved return stats, there is not much to suggest that he can improve them significantly more.

It is tough to feel that the numbers for Ricardas Berankis have not benefited from the level of opposition that he has faced thus far in 2016. The average ranking of his opponents last year was 66.4 compared to 90.7 this year and in matches where he has won a significant number of return points, he has been aided by very poor first serve percentages from his opponents, such as Seppi's 49.5% 1st serves in Doha and 55.6% by Fritz in Memphis.

The improvements on return for Milos Raonic and Nick Kyrgios are impressive though. Two big servers that are still developing their return game, they have both posted significant improvements in their return numbers despite facing a higher average level of opposition in 2016. They are already two of the most effective servers in the game and if they can add an improved return game, they could be very dangerous.

However, they are still starting from a low level. Even with a 4.4% improvement, Milos Raonic still only has the 41st highest return points won percentage in the top 50, while Nick Kyrgios' 3.2% improvement moves him to 34th in the top 50. They both still have plenty of time to improve this aspect of their game and I see no reason why this improvement cannot be sustained.