Here you will find detailed analysis highlighted from the CricViz app.

HALES MAKES HIMSELF AT HOME

Alex Hales is brimming with confidence. His 83 on day one of the second England v Sri Lanka Test was his third consecutive 50+ score in first-class cricket, his best such run since June 2011. Two near-misses in the search for a maiden Test ton do not prevent recognition that he belongs in Test cricket.

The Nottinghamshire man was a model of restraint in the first Test of the series. He left alone 28.6% of balls faced at Headingley, defending a further 28.1%. He played an assured opener’s innings, acclimatising to conditions – against bowlers who admittedly did not make him play enough – before showing more intent.

Hales played two attacking shots in first 20 balls in Leeds, four in his next 20 and 12 in the 20 subsequent deliveries. It was a knock that showed he could apply his natural game in the context of Test conditions.

That display helped produce an even more assured display at the Emirates Riverside. Sri Lanka bowled a tighter line in less helpful conditions, but a leave percentage of 11.7% showed Hales felt more at ease in imposing himself.

It was partly due to facing more spin in the second Test, but the touring bowlers attacked Hales’ stumps far more at Durham. 25% of deliveries he faced would have hit the stumps, compared with 4.3% at Headingley.

Less swing tightened their line, but Hales drew the bowlers into his hitting zone through his excellent judgment and concentration in the series opener.

In both his innings against Sri Lanka Hales has been dismissed attacking left-arm spin, errors of judgment that he should not be criticised for. Few can accelerate like the tall right-hander and whilst he will be frustrated in perishing after twice doing the hard work, it is that application which is notable.

RATING ANDERSON’S MASTERCLASS

Just how good was England’s bowling at Headingley? Sri Lanka’s batsmen struggled in tricky conditions against a skilled attack and CricViz can measure how much more dangerous the hosts’ seamers were than their counterparts.

The BatViz model analyses ball tracking data to produce wicket and run ratings for every ball. We conduct a nearest neighbour analysis of the six Hawk-Eye categories that comprise each ball: speed, line, length, seam, swing and bounce.

This process, counting the runs and wickets associated with the 1,000 most similar deliveries in our database based on those categories, allows the measurement of wicket threat and ease of scoring.

England’s bowlers had an average wicket probability of 1.87% per ball, Sri Lanka’s 1.38%. The top five bowlers in this ranking were members of the home attack, led unsurprisingly by James Anderson (2.13%).

Average wicket probability per ball bowled 
Bowler%
Anderson2.13
Stokes1.90
Vince1.83
Finn1.74
Broad1.71
Eranga1.60
Pradeep1.55
Chameera1.50
Herath1.45
Moeen1.18
Mathews1.13
Shanaka1.12

The Hawk-Eye data from the first Test testifies to Anderson’s mastery of seam and swing. Of the frontline seamers, only Shaminda Eranga had a lower average speed, but the Lancastrian’s 81mph is plenty when combined with lateral movement that no other paceman in the world can match.

Eranga actually swung the ball more on average, but Anderson’s ability to move the ball both ways is crucial. 16 of the 25 biggest inswingers (as faced by a right-hander) were delivered by England’s talisman.

Dangerous swing bowling is partly about controlling the movement in favourable conditions and Anderson is adept at finding just the right amount. Eranga bowled 13 of the 20 biggest outswingers (to right-handers) in the match, but these were not of the right line or length to trouble the batsmen.

Anderson can famously switch between inswing and outswing with little discernible change in action, a skill that is especially useful in the context of expert seam bowling. He possessed the highest average seam movement in the match.

Average wicket probability per ball faced 
Batsman%
Herath2.38
Mathews2.08
Karunaratne2.07
Mendis1.98
Finn1.94

Applying the wicket probability ratings to each batsman, the struggles faced by the visiting batsmen become clear. Of frontline batsmen the highest average wicket probability per ball was faced by Angelo Mathews (2.08%) and Dimuth Karunaratne (2.07%).

That the best was kept for the two most experienced opposing batsmen says much about the efficiency of England’s bowling. Anderson’s unique combination of seam, swing and accuracy, a combination that has brought him 443 Test wickets, was too good for the tourists.

MAKING USE OF THE NEW BALL

England’s decimation of Sri Lanka’s top order was based on accuracy and the application of pressure. James Anderson and Stuart Broad utilised similar conditions to those faced by Sri Lanka’s opening bowlers, but they gained reward for making batsmen play more regularly.

In the opening 10 overs of England’s innings, Alex Hales and Alastair Cook were able to leave 33 balls alone. Sri Lanka’s top order played no shot at 18 deliveries in the equivalent period on day two.

The result of such accuracy was indecision outside off stump. The five Sri Lankans who batted in the opening 10 overs played and missed eight times between them, edging nine deliveries. England’s openers played five false shots (play and misses and edges combined).

Anderson and Broad’s expertise in English conditions was apparent, with the latter particularly threatening in his two-wicket burst. Every single delivery in his opening five overs were either in line with or outside of off stump. In comparison, 10 of Shaminda Eranga’s opening 30 balls were on leg stump or wider.

Whilst they bowled slightly shorter as a pair on average, Eranga and Nuwan Pradeep actually extracted slightly more lateral movement than England’s experienced opening combination.

Dusan Shanaka went on to prove that enough seam and swing can be useful at a lower pace, but a lack of speed against watchful openers was problematic for Eranga – his average speed in his first five overs was 7 mph lower than Broad’s.

IPL PLAYERVIZ ANALYSIS – TEAM OF THE TOURNAMENT

As the IPL group phase nears completion, Patrick Noone takes a look at the players who have most positively affected their team’s chances of winning throughout the tournament.

Using CricViz’s PlayerViz statistics, it is possible to create a playing XI from the players with the highest impact scores. A player’s impact score provides a measure in runs of the impact that player’s performance has had on the match score. A player’s performance is measured against the average level of performance in that game and a positive or negative runs figure is produced to determine the extent that player has increased or decreased his team’s chances of winning. Scores are produced individually for batting, bowling and fielding, as well an aggregated overall figure that can be used to compare players by the same metric, regardless of their role in the team.

From the overall impact leaderboard, we are able to rearrange the top 11 players into a team as follows:

1. Quinton de Kock (Delhi Daredevils); Matches: 11, Runs: 383 (100s: 1, 50s: 2), SR: 144, Overall impact: +90 runs

The South African wicketkeeper has added consistency to his game to go with his obvious talent, with scores of 40+ in four consecutive innings before missing out against Rising Pune Supergiants. As he showed in his 108 against Royal Challengers Bangalore, he also has the ability to bat deep and convert those starts into more significant scores. de Kock’s preference to pick gaps in the field during the powerplay rather than go over the top have seen him hit 47 fours and just 12 sixes, with over 55% of all his runs coming in the first six overs.

IPL Fact: de Kock has been involved in five of Delhi’s 10 50+ partnerships this campaign.

2. David Warner (Sunrisers Hyderabad) Matches: 12, Runs: 567 (50s: 6) SR: 155.8, Overall impact: +187 runs

Warner tops our impact leaderboard thanks to a brilliantly consistent season at the top of the order for Sunrisers Hyderabad. With only three scores below 46, the skipper has relished his return to the opener’s spot after batting in Australia’s middle order at the ICC World T20. His side owe a lot to that consistency, with his 567 runs representing over 32% of the team’s total runs for the tournament, helping to overcome the stuttering form shown by their other top order batsmen.

IPL Fact: Warner is currently level with Ajinkya Rahane for the highest number of 50+ scores (6) without making a hundred.

3. AB de Villiers (Royal Challengers Bangalore) Matches: 12, Runs: 597 (100s: 1, 50s: 5), SR: 173.5, Overall impact: +145 runs

As Virat Kohli has taken most of the headlines in RCB’s star studded batting lineup, de Villiers had almost slipped under the radar for the first 10 games of this year’s IPL. That was until he hit 129 of his side’s 248 against Gujarat Lions to post the highest individual score of the season; and then followed it up with an unbeaten 31-ball 59 at Eden Gardens to help see off Kolkata Knight Riders. de Villiers’ record of batting with Kohli has been one of the stories of the IPL, with the pair putting on the top three partnerships of the tournament – the 229 in that game against Gujarat leading the way – and five century stands in total. De Villiers has also been electric in the field, taking 14 catches that represent a tournament high for non-wicketkeepers.

IPL Fact: de Villiers’ 129* against Gujarat Lions featured 112 runs from boundaries (10 fours, 12 sixes).

4. Aaron Finch (Gujarat Lions) Matches: 9, Runs: 313 (50s: 4), SR: 132.6, Overall impact: +92 runs

Three fifties in his first three innings at the top of the order for Aaron Finch hinted at a stellar tournament for the Australian, before an injury against RCB saw him lose his place to Dwayne Smith as Brendon McCullum’s opening partner. Since then, Finch has batted at three once and at five three times as the Lions have struggled for balance in their batting during the second half of the group phase. Nonetheless, Finch has still shown admirable resolve in his new role, most notably in match 34, when he made an unbeaten 51 against Sunrisers Hyderabad while his side stuttered to 126. Finch remains Gujarat’s top scorer with 313 runs and his strike rate is only bettered by McCullum and Smith, suggesting he will still have a big role to play for the new franchise in the knockout phase of the competition.

IPL Fact: Finch’s average of 52.2 is by far the highest of any Gujarat player in this year’s IPL. Dinesh Karthik is second with 29.8.

5. Shane Watson (Royal Challengers Bangalore) Matches: 12, Runs: 152, SR: 153.5, Wickets: 14, Economy: 8.5, Overall impact: +75.4 runs

Perhaps a surprise inclusion given his relatively quiet tournament with the bat – his high score is just 33 against Delhi Daredevils in match 11 – but Shane Watson has been a revelation for RCB with the ball. He leads his side’s wicket takers list with 14, picking up a wicket every 18.2 deliveries thanks to some canny changes of pace. Watson has only bowled 33 off-cutters in his 12 matches, but he has picked up 5-25 from those deliveries; the genuine variation proving enough of a surprise delivery to catch out batsmen on a regular basis.

IPL Fact: Watson is the only RCB bowler to have bowled three four-over spells with an economy of under seven runs per over.

6. Krunal Pandya (Mumbai Indians) Matches: 11, Runs: 233 (50s: 1), SR: 192.6, Wickets: 6, Economy: 7.1, Overall impact: +87.7 runs

The elder brother of India’s ICC World T20 squad member Hardik, Krunal Pandya has emerged as a genuine all-rounder for Mumbai Indians as they seek to defend their IPL title. Beginning the campaign primarily as a left-arm spin option to supplement Mumbai’s seam-heavy attack, Pandya has caught the eye with the bat in the middle order as the tournament has progressed. His unbeaten 49 from just 28 balls against Sunrisers Hyderabad in match 12 gave a glimpse of his potential before he repaid his side’s faith in sending him in at number three against Delhi Daredevils, blasting 86 from 37 balls to score his maiden IPL half century. Pandya’s versatility has afforded his side a flexibility that all T20 teams crave as he fulfils the coveted role of frontline bowler capable of batting in the top six.

IPL Fact: Krunal Pandya dismissed AB de Villiers in both matches between their respective sides.

7. Chris Morris (Delhi Daredevils) Matches: 11, Runs: 168 (50s: 1), SR: 184.6, Wickets: 12, Economy: 6.8, Overall impact: +80 runs

Another player who fits into the ‘genuine all-rounder’ category, Morris has lived up to his big price tag with his performances with both bat and ball during this campaign. A bowler of genuine pace – his speeds have consistently been around 85-88mph, with a tournament high of 89.2mph against Kings XI Punjab in match 36. A batting strike rate a fraction below 185 shows his prowess as a lower order hitter, with his undoubted highlight the 82* from 32 balls that saw him bring up the tournament’s fastest 50 (17 balls).

IPL Fact: Morris is ranked first and second in Delhi Daredevils’ leaderboards for batting average and bowling economy rate respectively.

8. Axar Patel (Kings XI Punjab) Matches: 12, Runs: 97, SR 149.2, Wickets: 11, Economy: 7.3, Overall impact: +81 runs

In another difficult season for Kings XI Punjab, Axar Patel has once again proved himself to be a consistent performer both as a canny left arm orthodox bowler and a reliable lower order batsman. He took career best figures of 4-21 against Gujarat Lions in game 28, a performance that included the only hat-trick of the tournament to date. Meanwhile his highlight with the bat came in a losing cause in Hyderabad against the Sunrisers as he smashed 36 off just 17 balls to propel his side to 143.

IPL Fact: Patel has hit more than twice as many sixes as fours in this competition (3 fours, 7 sixes).

9. Yuzvendra Chahal (Royal Challengers Bangalore) Matches: 9, Wickets: 12, Economy: 7.8, Overall impact: +66 runs

Chahal has become a key figure for RCB since his breakthrough IPL in 2014 and this year he is their second highest wicket taker behind Shane Watson, while in the tournament as a whole, Amit Mishra is the only spinner to have taken more wickets than RCB’s 25-year old legspinner. Chahal does not rely too heavily on variations – only three of his 12 wickets have come from googlies – preferring instead to beat the batsmen with subtle changes of pace and drift. Asked to bowl in the powerplay on five occasions this season, he is the highest ranked spinner on our bowling impact leaderboard in that part of the innings. He has only gone wicketless in one of his nine matches this campaign and is fast establishing himself as one of the leading young spin bowlers in the Indian game.

IPL Fact: No one has taken more wickets (3) through stumpings than Chahal in this tournament.

10. Jasprit Bumrah (Mumbai Indians) Matches: 13, Wickets: 14, Economy: 7.6, Overall impact: +87 runs

The young seamer is enjoying quite a year since he made his ODI debut at the SCG in January, going on to become a key part of India’s Asia Cup and World T20 sides. His ability to bowl yorkers has made him an excellent death bowler; in this tournament he has successfully landed 29 such deliveries, conceding just 27 runs. This, allied to his unusual action, has allowed Mumbai to play him in tandem with fellow seamers Tim Southee and Mitchell McClenaghan as part of a varied attack that has taken 42 of the side’s 60 wickets.

IPL Fact: When Bumrah took 3-13 against Delhi Daredevils on 15th May, he became the first Mumbai seamer to bowl a four-over spell with an economy less than four since Lasith Malinga in 2014.

11. Mustafizur Rahman (Sunrisers Hyderabad) Matches: 12, Wickets: 14, Economy: 6.7, Overall impact: 104.79 runs

Bangladesh’s most recent star is taking his first IPL by storm, sitting fourth in the wicket taker’s list and playing a major role in what is arguably the best seam attack of the IPL. The off cutter has been Mustafizur’s most potent weapon – his ability to bowl at such a reduced pace with so little change in action has brought him plenty of reward; most notably against Kings XI Punjab on 23rd April when his 10 off-cutters produced two wickets, conceding no runs.

IPL Fact: Mustafizur is only the fifth Bangladeshi to feature in the IPL after Mohammad Ashraful, Mashrafe Mortaza, Abdur Razzak and Shakib Al-Hasan.

Where’s Kohli?
One notable omission from the CricViz XI is Virat Kohli. Despite scoring 752 runs at an average of 83.6, RCB’s captain sits in 14th place in our overall impact leaderboard, with a cumulative score of +51 runs. The reason for this incongruity is because the PlayerViz model that is used to generate these scores is resource-based, meaning that credit is not given to performances that are expected in the context of variables such as balls faced.

An example of this aspect of the model penalising Kohli can be seen in RCB’s match against Rising Pune Supergiants, when he scored 80 off 63 balls. Kohli’s batting impact score for this match was -16, despite his contribution to his side winning the game. This is because an opener facing just over half the balls available in the innings should be closer to a hundred than Kohli was. By contrast, in the same match AB de Villiers batted at three and scored 83 off 46 balls to finish with a batting impact score of +22 runs.

ANALYSING THE LEADING IPL WICKET-TAKERS

Utilising CricViz’s hawkeye data archive Freddie Wilde has analysed in detail the five leading wicket-takers in this season’s Indian Premier League by examining their variations, lengths and lines. 

After 41 matches of the season the five leading wicket-takers are all seam bowlers: Mitchell McClenaghan (Mumbai Indians), Bhuveneshwar Kumar (Sunrisers Hyderabad), Andre Russell (Kolkata Knight Riders), Shane Watson (Royal Challengers Bangalore) and Mustafizur Rahman (Sunrisers Hyderabad).

Delivery-Type Analysis

PlayerNo MovementOff CutterSlower BallAway Swinger In Swinger Leg Cutter
Bhuveneshwar60%8%1%20%10%1%
McClenaghan86%11%2%1%0%0%
Russell87%11%1%1%0%0%
Mustafizur53%46%0%0%1%0%
Watson80%14%1%0%2%3%

For all five of the bowlers the majority of their deliveries are conventional. Mustafizur and Bhuveneshwar bowl the largest share of variations with Mustafizur bowling a very high percentage of off-cutters and Bhuveneshwar favouring swing—largely away from the batsman. Watson, Russell and McClenaghan have all utilised the off-cutter as their primary variation but have bowled them more sparingly.

PlayerNo Movement AverageOff Cutter AverageSlower Ball AverageAway Swinger AverageIn Swinger AverageLeg Cutter Average
Bhuveneshwar49.7510.00NA5.209.50NA
McClenaghan21.0039.00NANANANA
Mustafizur19.8314.85NANANANA
Russell15.6137.00NANANANA
Watson31.876.25NANA2.0014.00

Bhuveneshwar, Mustafizur and Watson stand out as the bowlers who use variations most effectively. While Russell maintains a low average from conventional deliveries. Bhuveneshwar’s strength is clearly his ability to swing the ball both in and away from the batsman – he has taken five wickets with away swingers and two with in-swingers. Mustafizur’s off-cutter average is higher than Bhuveneshwar’s and Watson’s but it has brought him most success earning him seven wickets at an economy rate of 5.88 and is the only delivery type, length or line to average less than 15 having been bowled at least 100 times. Watson’s off-cutter has also been effective giving him four wickets from 31 deliveries at an economy rate of 4.83. McClenaghan’s high averages for no movement deliveries and off-cutters is a reflection of his profligacy – he has been the most expensive of the five leading wicket-takers – rather than the deliveries themselves.

Length Analysis

PlayerFull TossYorkerHalf VolleyGood Length Back of a LengthShort
Bhuveneshwar9%6%6%52%21%6%
McClenaghan6%6%6%27%30%25%
Mustafizur14%15%17%41%11%2%
Russell7%6%9%33%26%19%
Watson8%6%14%38%18%16%

Mustafizur has the highest share of full tosses and half volleys and that is most probably a result of his consistent attempt to land his yorker, of which he also boasts the highest percentage share. Bhuveneshwar, who, as illustrated above, is often looking to swing the ball, unsurprisingly the highest share of deliveries bowled on a traditional good length. Impressively Bhuveneshwar rarely over-pitches when looking for swing having bowled just 6% of his deliveries as half volleys. McClenaghan, Russell and Watson, all less reliant on movement in the air and off the pitch, clearly favour bowling shorter than Bhuvenshwar and Mustafizur. More than half of McClenaghan’s deliveries are back of a length or shorter, while the figure for Russell and Watson is 45% and 34% respectively.

PlayerFull Toss AverageYorker AverageHalf Volley AverageGood Length AverageBack of a Length AverageShort Average
BhuveneshwarNA10.0030.0012.7023.00NA
McClenaghan8.005.00NA102.0013.4023.80
Mustafizur41.0022.0018.6614.009.00NA
Russell12.50NA17.5014.33NA9.50
WatsonNA13.0021.0026.0030.009.60

Given McClenaghan’s consistently short length the yorker clearly works as a successful surprise ball. He has conceded just ten runs from the 15 he has bowled and collected two wickets. Bhuveneshwar and Watson have both recorded similar figures from their yorkers, having bowled 14 and 15 deliveries respectively taking one and two wickets. Mustafizur has landed the most yorkers of the five, having successfully bowled 35 of them, taking the one wicket. As expected given his ability to swing the ball both ways Bhuveneshwar has the lowest average from deliveries bowled on a good length. Mustafizur’s good length has earned him three wickets from his 39 deliveries with such a length being ideal for his off cutters.  McClenaghan, who has bowled more deliveries back of a length than any other, has the best average from balls pitched there and has taken five wickets; he has, however, only taken one wicket when he over-pitches to a good length. Both Russell and Watson have been very successful bowling short – taking five and four wickets respectively, Watson, however, has a considerably lower economy rate from such a length. McClenaghan has taken five wickets from a short length but has conceded a boundary percentage of 27%.

The status of the yorker as the most effective delivery is reaffirmed by the statistics of the five bowlers with all of them recording economy rates of less than 5.21 from the delivery.

Line Analysis

PlayerWideOutside Off StumpOff StumpMiddle StumpLeg StumpDown Leg
Bhuveneshwar1%66%8%6%8%11%
McClenaghan0%65%3%5%8%19%
Mustafizur0%35%7%11%11%36%
Russell0%61%12%7%10%10%
Watson3%63%8%5%8%13%

Bhuveneshwar, McClenaghan, Russell and Watson all land more than 60% of their deliveries outside off stump – a traditional good line to bowl. Mustafizur, the most unorthodox of the five bowlers pitches as many balls down leg as he does outside off stump – this can largely be explained by his angle coming over the wicket to right-handers and angling the ball across them. Mustafizur and Watson both pitch 29% of their deliveries on the stumps, forcing the batsman to play.

PlayerWide AverageOutside Off AverageOff Stump AverageMiddle Stump Average Leg Stump AverageDown Leg Average
Bhuveneshwar0.0022.8523.00NA5.8042.00
McClenaghanNA21.10NA27.009.0069.00
MustafizurNA20.50NA17.0012.0013.40
RussellNA22.0046.009.503.7518.00
WatsonNA19.30NA10.0024.0022.50

Mustafizur and Russell are both conspicuously successful from balls pitched on leg stump and down leg. Russell has taken five wickets from the 40 deliveries he has bowled there while Mustafizur has taken seven from 108 balls bowled on those lines at an economy rate of just 4.84. Watson’s controlled line outside off stump has earned him ten wickets at the best average of the five.

Headline Statistics

  • Mustafizur has taken seven wickets from 108 balls that have pitched on leg stump & down leg at an economy rate of just 4.84.
  • Watson has bowled 39 short deliveries this season & has taken 5-48 with a dot ball percentage of 44% from them.
  • Bhuveneshwar has got 30% of his deliveries to swing this season and has an average of 6.42 from them.
  • 55% of McClenaghan’s deliveries have been back of a length or shorter and they have earned him 10 of his 15 wickets.
  • Russell’s 38 short balls have conceded 22 runs this season with a dot ball percentage of 58%.

Freddie Wilde is a freelance cricket journalist, @fwildecricket. 

Virat Kohli, down the track to success

Virat Kohli’s astonishing form with the bat has continued as the IPL reaches its halfway stage. At the time of writing, the Royal Challengers Bangalore skipper is the tournament’s second highest run scorer with 381 runs scored at an average of 76.20. The only man to have scored more than Kohli at this juncture is Sunrisers Hyderabad’s David Warner who has five more runs having played seven matches to Kohli’s six. Analysing the two players’ performances alongside Kohli’s team mate AB de Villiers reveals some interesting trends about how each batsman accumulates their runs.

What has stood out during Kohli’s scores of 75, 79, 33, 80, 100* and 14 is the way he has used his feet to both the spinners and pace bowlers. 87 of his 381 runs (22.83%) have come from shots played coming down the track, scored at a strike rate of 164.15. By contrast, Warner has only come down the pitch on five occasions across his seven innings, scoring just four runs. The Australian opener prefers instead to play aggressively on the back foot – 202 of his 386 runs (52.33%) have been scored from back foot shots at a strike rate of 165.57.

Kohli has had great success batting with AB de Villiers – the pair have put on stands of 157, 107, 59 and 155 in this campaign – and RCB’s number three currently lies third in the tournament’s top scorers with 316. Like Warner, de Villiers has been reluctant to go on the charge as our data shows him to have only played seven shots after advancing, scoring six runs in the process. Instead, de Villiers has attacked primarily on the front foot; using his ability to score all around the ground, the South African has plundered 164 runs (51.9% of all his runs) from that position at a strike rate of 159.22.

This contrast in approach between Kohli and de Villiers is perhaps a factor behind their success as a pair. Bowling attacks will struggle to find the correct lengths to bowl if a batsman’s footwork disrupts their rhythm; a problem only compounded when each batsman adopts such different methods of run scoring.

Despite Kohli’s scintillating form up to this point, his method of walking towards the bowler has proved his undoing on two occasions – significantly his two lowest scores of the IPL. Against Mumbai Indians, Kohli advanced on three occasions but was twice beaten by the away swing of Tim Southee and ultimately holed out failing to get to the pitch of a Krunal Pandya delivery. Then, in his most recent outing against Sunrisers he was unable to get on top of an off cutter from Mustafizur Rahman and picked out backward point.

Kohli’s approach is unlikely to change in light of these relative failures, and nor should it. However, they do offer a glimmer of hope to bowling sides in the remainder of the tournament that a player’s greatest strength can sometimes be their weakness.

ROBSON BOWLING OVER ENGLAND SELECTORS

Alastair Cook is nearing yet another notable landmark. The England captain is 36 runs short of 10,000 in Tests and will expect to raise his bat in acknowledgement against Sri Lanka at Headingley next month.

His opening partner will also be under scrutiny, for very different reasons. Another Test series, another debate about who will open with Cook. The man in possession is yet again under pressure, and the list of alternatives to Alex Hales is longer than ever.

If the selectors do move away from the Nottinghamshire man, it could well be towards a player previously tried and discarded. County Championship runs are expected of the candidates, and Sam Robson has started the season in a manner that is hard to ignore.

Robson plundered 231 and 106 against Warwickshire at Lord’s, maintaining his habit of heavy early season scoring. Batting in April and May is supposedly so tricky that it has contributed to a major change in competition rules. It is not an issue for Robson.

Facing the moving ball on juicy early summer wickets has held no problems for the Middlesex man. Since his Championship debut in 2010, Robson averages 47.6 batting in April and May. His average in these months from 2013 onwards is 59.4.

Seven of Robson’s 10 Championship centuries have come in April and May, with four of those tons seeing him pass 150. The Middlesex man is clearly adept at catching the eye early in the season, but if his headquarters haul against the Bears is not enough to edge out Hales, can he maintain this form?

Few of the possible partners for Cook have as many questions asked of their technique as Robson. Adam Lyth’s tendency to fall to an outside edge became apparent last summer, but Robson’s susceptibility to balls moving into him became even more damaging.

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Four bowled dismissals in 11 Test innings suggested to some a flaw that was unacceptable for a prospective Test opener. Nicking to the keeper and slips is one thing, missing straight ones is quite another.

However, perhaps too much was read into this mode of dismissal. 14.2% of Robson’s Championship dismissals have been bowled, compared with 23.3% for Hales. The incumbent England opener had his stumps disturbed eight times in 18 Championship innings last year. 22.4% of Nick Compton’s Championship dismissals have been bowled, largely batting in the middle order.

Openers have the hardest job to correct technical issues, as the new ball poses the most challenges. All have weaknesses to some degree and Robson knows what contributed to his England axing. His work in correcting a problem that was not exposed by express pace seems to be bearing fruit.

WORLD T20 2016, SUPER 10 PHASE ANALYSIS

A summary of venue and innings-phase statistics from the Super 10 stage of the ICC World Twenty20 2016

The following data is comprised of the 38 innings that were played over 20 scheduled overs in the Super 10 stage of the ICC World Twenty20 2016. Therefore the rain-reduced match between India and Pakistan is not included.

Phase Breakdowns:

  • Powerplay: 1-6
  • Middle Overs: 7-16
  • Death Overs: 17-20

Venue Analysis

VenueAverage RunsAverage WicketsAverage Boundary PercentageAverage Dot Ball Percentage
Bangalore142.166.6614.52%36.69%
Delhi140.506.6613.75%38.79%
Dharamsala1388.5012.50%37.08%
Kolkata1456.6616.00%37.95%
Mohali170.665.3317.09%30.52%
Mumbai200.836.1622.07%28.93%
Nagpur1157.838.64%43.58%

Mumbai clearly emerged as the best venue for batsmen with the highest average runs, highest average boundary percentage and lowest average dot ball percentage of all seven venues. Mohali also proved to be a good batting venue coming second to Mumbai in runs, boundary percentage and dot ball percentage and recording fewer average wickets than any other ground.  Nagpur was the toughest batting venue recording the lowest average score, second highest average wickets, lowest boundary percentage and highest dot ball percentage. Dharamsala only hosted one Super 10 match, while Bangalore, Delhi and Kolkata proved similar venues across all metrics and make up the middle of the table.


Powerplay Analysis: Batting

TeamAverage Runs ScoredAverage Wickets LostAverage Boundary PercentageAverage Dot Ball Percentage
Afghanistan40.252.0014.58%54.86%
Australia53.001.0018.41%47.89%
Bangladesh38.251.7511.80%43.05%
England54.502.2522.91%38.88%
India36.002.3312.03%45.37%
New Zealand46.250.7520.13%50.00%
Pakistan54.001.3325.92%45.37%
South Africa55.501.2527.77%46.52%
Sri Lanka40.752.2515.27%46.52%
West Indies42.661.3319.44%50.00%
Match Winners47.151.3620.61%45.17%
Match Losers44.891.8917.54%47.26%

The most striking set of data from this phase belongs to India who are one of the four Semi-Finalists despite recording the lowest average score, the highest average wickets lost and the second lowest average boundary percentage. Interestingly another Semi-Finalist, West Indies also struggled in the phase, recording the fifth lowest average score and third highest average dot ball percentage. South Africa and Semi-Finalists England both boasted high average runs scored and average boundary percentages largely due to their record-breaking aggregate Powerplay total in their match in Mumbai of 172. England did however record the second highest average wickets lost. Another intriguing set of data belongs to Pakistan, who despite becoming the first ICC Full Member to be unable to qualify for the Semi-Finals recorded the second highest average score, fourth lowest average wickets lost, second highest average boundary percentage and fifth lowest dot ball percentage. Fourth Semi-Finalists New Zealand have batted in all four of their matches and have been chasing modest totals in three of them which accounts for their mid-table average runs scored and high dot ball percentage. Notably they did record the lowest average wickets lost and a healthy boundary percentage. Australia had success in the phase with the fourth highest average score having scored more than 50 in each of their four Powerplays and second lowest average wickets lost.


Powerplay Analysis: Bowling

TeamAverage Runs ConcededAverage Wickets TakenAverage Boundary PercentageAverage Dot Ball Percentage
Afghanistan45.752.0022.91%51.38%
Australia42.251.5016.66%45.14%
Bangladesh46.750.7520.13%42.36%
England50.002.0023.61%49.30%
India45.661.3318.51%48.14%
New Zealand43.752.0017.36%43.05%
Pakistan50.661.3319.44%43.51%
South Africa59.252.2523.61%43.75%
Sri Lanka36.751.0014.58%44.44%
West Indies40.502.0013.88%51.38%
Match Losers47.151.3620.61%45.17%
Match Winners44.891.8917.5447.36%

West Indies emerge as the success-story of this phase, conceding the second lowest average runs, taking the joint highest average wickets, the lowest boundary percentage and the joint highest dot ball percentage. Their bowling statistics are boosted by virtue of being the only team to play two matches in Nagpur – the best bowling venue. Sri Lanka also recorded impressive data in this phase conceding the fewest average runs despite taking the second fewest average wickets. They were the only team who didn’t concede more than 40 in the phase.  Semi-Finalists New Zealand recorded impressive figures: the fourth fewest average runs conceded, joint second highest average wickets taken and the fourth lowest boundary percentage and they did so despite playing at four different venues including the relatively high-scoring Mohali. Australia recorded the third lowest average runs concede. Semi-Finalists England and India recorded high average dot ball percentages, the former’s average runs conceded is dented largely by conceding 83-0 against South Africa, India meanwhile, struggled to take wickets finishing with the joint third fewest average wickets taken alongside PakistanSouth Africa, who played twice at Mumbai where attacking cricket is encouraged by conditions, conceded the highest average runs but took the most average wickets.


Middle Overs Analysis: Batting

TeamAverage Runs ScoredAverage Wickets LostAverage Boundary PercentageAverage Dot Ball Percentage
Afghanistan66.753.2510.00%36.25%
Australia72.003.2510.93%36.67%
Bangladesh60.754.2512.16%43.76%
England77.252.2511.25%27.08%
India62.003.007.22%35.00%
New Zealand63.003.508.75%36.66%
Pakistan86.332.0016.11%25.55%
South Africa71.502.509.58%27.50%
Sri Lanka69.503.0011.25%35.83%
West Indies78.662.3315.00%38.33%
Match Winners74.102.6312.10%31.66%
Match Losers65.843.319.93%35.88%

Fascinatingly it is Pakistan who boast the most impressive middle over batting statistics ranking first in all four metrics. Of course, this data does exclude their match against India in which they scored 118-5 in 18 overs on a difficult pitch, and they did play two matches in the second highest scoring venue Mohali, but even considering these factors their numbers are still impressive enough to suggest the existence of a trend. Semi-Finalists England and West Indies both registered high average runs scored and low average wickets lost, England also had an impressive dot ball percentage. This is the phase where the Bangladesh batting came unstuck. They recorded the lowest average runs scored, highest average wickets lost and highest dot ball percentage. Interestingly unbeaten Semi-Finalists New Zealand also registered some poor figures in this phase: the third lowest average runs scored, second highest average wickets lost, second lowest average boundary percentage and fourth highest dot ball percentage. They were, of course, chasing relatively low totals in three of those four innings. India recorded a high average wickets lost having lost three and four wickets against New Zealand and Bangladesh respectively. India’s boundary percentage is dragged down by hitting none in the phase against New Zealand. Afghanistan and Australia both lost a relatively high number of wickets in this phase.


Middle Overs Analysis: Bowling

TeamAverage Runs ConcededAverage Wickets TakenAverage Boundary PercentageAverage Dot Ball Percentage
Afghanistan64.502.759.58%35.41%
Australia73.752.7512.08%31.25%
Bangladesh81.003.0015.00%29.16%
England90.503.0015.41%28.33%
India65.003.338.33%37.22%
New Zealand47.754.505.91%42.51%
Pakistan74.332.6614.44%33.88%
South Africa73.753.0011.25%27.08%
Sri Lanka68.252.0011.25%36.66%
West Indies60.752.757.08%37.08%
Match Winners65.843.319.93%35.88%
Match Losers74.102.6312.10%31.66%

It is in this phase that New Zealand clearly set themselves apart from the other nine teams in the competition. They are not only ranked first in all four metrics but are so by large margins, particularly in terms of average runs conceded and average wickets taken. Astoundingly in the four combined six over periods between overs seven and thirteen New Zealand conceded only two boundaries and took 12 wickets for just 89 runs. That is a boundary percentage of 1.38% across 24 overs. India were also impressive in this phase, recording the second highest average wickets taken, third lowest average boundary percentage and second highest dot ball percentage. Although they did not take a high number of wickets West Indies conceded very few runs in this phase and had low boundary and high dot ball percentages. Interestingly the fourth Semi-Finalist England conceded more runs on average in this phase than any other team. They did at least take the joint fourth average number of wickets in the phase. Sri Lanka had the lowest average wickets taken while Pakistan were second from bottom in terms of wickets and also had a high boundary percentage.


Death Overs Analysis: Batting

TeamAverage Runs ScoredAverage Wickets LostAverage Boundary PercentageAverage Dot Ball Percentage
Afghanistan36.753.0021.87%35.41%
Australia36.002.0519.85%27.65%
Bangladesh36.002.2521.66%27.70%
England49.501.7532.00%21.49%
India30.661.6626.47%38.06%
Match Losers34.502.6618.28%30.53%
Match Winners38.521.5725.15%24.67%
New Zealand39.002.7515.62%20.83%
Pakistan36.662.6615.27%16.66%
South Africa33.002.0011.17%25.04%
Sri Lanka29.252.5018.49%35.34%
West Indies23.501.5012.63%36.49%

Semi-Finalists England dominated this phase scoring the highest average runs and highest average boundary percentage and doing so by considerable margins. They also registered the fourth lowest average wickets lost and third lowest dot ball percentage. Despite completing their run-chases in this phase with relative ease in all four of their innings New Zealand recorded impressive results in all four metrics, particularly average dot ball percentage where they ranked second and did so despite not once facing the full four overs. They did have a high average wickets lost but of all four metrics in this phase wickets lost can be said to be the least important. Although the other Semi-Finalists India and West Indies recorded poor figures in this phase their data is to an extent excusable because India’s numbers are dragged down by being bowled out by New Zealand in the phase after scoring just 13 while West Indies didn’t once face a full four overs having completed their run-chases on three occasions and being bowled out on the other. Having recorded strong numbers for the other two batting phases it is here that Pakistan drop off. They set a mid-table average runs scored and had the lowest dot ball percentage but had the second highest average wickets lost and crucially the third lowest boundary percentage. Sri Lanka struggled in this phase with the second lowest average runs scored, the second highest average wickets lost and the fourth highest dot ball percentage.


Death Overs Analysis: Bowling

TeamAverage Runs ConcededAverage Wickets TakenAverage Boundary Percentage Average Dot Ball Percentage
Afghanistan 45.501.2528.61%20.46%
Australia41.752.0027.46%15.40%
Bangladesh34.503.0021.66%29.79%
England34.501.2518.75%34.45%
India33.002.6616.66%25.00%
New Zealand25.002.6618.28%30.53%
Pakistan48.001.0025.00%18.05%
South Africa 28.253.5019.04%42.43%
Sri Lanka38.251.0029.22%19.73%
West Indies36.002.7518.75%31.25%
Match Winners34.502.6618.28%30.53%
Match Losers38.521.5725.15%24.67%

After their sensational middle-over phase it is unsurprising that New Zealand dominated the following death over phase recording the lowest average runs conceded, joint third highest average wickets taken and second lowest average boundary percentage – and they did this despite bowling first in their four matches. India also fared well in this phase, registering the third lowest average runs conceded, joint third average wickets taken and the lowest average boundary percentage. Semi-Finalists England were relatively frugal, notably bowling a large number of dot balls. So too were West Indies who recorded the third lowest average runs conceded and third highest dot ball percentage. They were also potent too collecting the third highest average wickets taken. Pakistan, having struggled in the corresponding phase with the bat, did so also with the ball, recording the highest average runs conceded, joint lowest average wickets taken  and second lowest dot ball percentage. Sri Lanka struggled to collect wickets and had high boundary and low dot ball percentages. Afghanistan had a high average runs conceded.


Innings Analysis: Batting

TeamAverage Runs ScoredAverage Wickets LostAverage Boundary PercentageAverage Dot Ball Percentage
Afghanistan143.758.2513.75%41.66%
Australia161.006.5016.81%32.03%
Bangladesh142.166.6614.52%36.69%
England181.256.2518.85%29.43%
India128.667.0011.68%36.88%
New Zealand148.257.0013.54%37.50%
Pakistan177.006.0018.88%29.72%
South Africa146.007.5011.75%36.96%
Sri Lanka139.507.7513.40%38.60%
West Indies137.505.5013.76%41.31%
Match Winners159.785.5716.88%31.13%
Match Losers143.427.7313.70%38.13%

Having performances well across all three phases England top the batting rankings in terms of average runs scored and average dot ball percentage. Strong showings in the Powerplay and middle over phase from Pakistan as well as two matches in Mohali see them end up with the second highest average runs scored, third lowest average wickets lost, highest boundary percentage and second lowest average dot ball percentage. The runs scored data for New Zealand is somewhat skewed by them having batted second in all four innings but they still managed to be ranked fifth. New Zealand’s high average wickets lost is their weakest performance across phase metrics; they also struggled to hit boundaries – but this can in part be explained by comfortably chasing totals. The West Indies fared poorly in terms of average runs scored but batted second on all four occasions, chasing two out of three low totals. India had the lowest average runs scored and lowest average boundary percentage, two statistics which are largely shaped by being bowled out for 79 against New Zealand. Australia were ranked in the top five across all four metrics. Afghanistan and Sri Lanka had the highest average wickets lost.


Innings Analysis: Bowling

TeamAverage Runs ConcededAverage Wickets TakenAverage Boundary Percentage Average Dot Ball Percentage
Afghanistan155.756.0016.87%36.87%
Australia157.756.2516.26%32.45%
Bangladesh162.256.7517.85%33.07%
England175.006.2518.54%34.79%
India143.667.3313.05%38.05%
New Zealand110.258.509.62%40.89%
Pakistan173.005.0018.05%33.61%
South Africa161.258.7516.46%35.09%
Sri Lanka143.254.0014.90%36.14%
West Indies137.257.5011.45%40.20%
Match Winners143.427.7313.70%38.13%
Match Losers159.785.5716.88%34.13%

England and Pakistan, who had the highest average runs scored also register the highest average runs conceded, low numbers for average wickets taken and the highest two average boundary percentages. Bangladesh had similarly high average runs conceded and average boundary percentage and also bowled relatively few dot balls. Interestingly Australia, who performed mid-table in terms of average runs scored, average wickets taken and average boundary percentage had the worst dot ball percentage. Semi-Finalists New Zealand and West Indies, who batted second in all four of their matches registered the best two average runs conceded figures, second and fourth highest average wickets taken respectively and the two lowest boundary percentages. India recorded mid-table average runs-conceded and took a relatively high number of wickets. South Africa were the most potent bowling team, collecting the highest average wickets taken and Sri Lanka were the least potent bowling team.


Super 10: Aggregate Trends

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Freddie Wilde is a freelance journalist, @fwildecricket. 

WORLD T20 2016, FIRST ROUND ANALYSIS

A summary of statistics from the First Round stage of the ICC World Twenty20 2016

The following data is comprised of the sixteen innings that were played over 20 scheduled overs in the First Round of the World T20 2016. Therefore the two No Results, Netherlands v Oman and Bangladesh v Ireland, are not included, neither is Scotland’s 8-over run-chase against Hong Kong, both innings of the rain reduced match between Ireland and Netherlands and Oman’s 12-over chase against Bangladesh. Hong Kong’s 20-over first innings v Scotland and Bangladesh’s 20-over first innings v Oman before rain reduced the remainder of the matches, are included.


Powerplay Analysis: Batting

Team/CategoryNumber of PowerplaysAverage Runs ScoredAverage Wickets LostAverage Boundary PercentageAverage Dot Ball Percentage
Afg346.33118.51%43.51%
Ban2310.59.72%54.16%
HK332.661.6613.88%57.40%
Ire146022.22%61.11%
Net139119.44%50%
Oma144022.22%58.33%
Sco244219.44%51.38%
Zim340.661.6616.66%48.14%

Afghanistan emerge as the team who utilised the Powerplay best as a batting team. On average they scored the most runs and had the lowest dot ball percentage. Interestingly the other qualifier from the First Round, Bangladesh, on average scored the fewest runs in the Powerplay and had the lowest boundary percentage, crucially however, they only lost 0.5 wickets in the phase on average, bettered only by Ireland and Oman who just played one innings each and did not lose a wicket.

Powerplay Analysis: Bowling

Team/CategoryNumber of PowerplaysAverage Runs ConcededAverage Wickets TakenAverage Boundary PercentgaeAverage Dot Ball Percentage
Afg347117.59%45.37%
Ban139119.44%50%
HK248120.83%43.05%
Ire144022.22%47.22%
Net13318.33%47.22%
Oma237.5016.66%61.11%
Sco334.331.6613.88%53.70%
Zim335.662.3316.6655.55%

Scotland and Zimbabwe stand out as the two teams who fared best in the Powerplay as a bowling team. On average they took the most wickets in the first six overs and only Netherlands conceded fewer runs. Hong Kong really struggled in the first six overs; they conceded the most runs on average, had the lowest dot ball percentage and highest boundary percentage of those to have played more than one phase. Qualifiers Afghanistan and Bangladesh both also toiled in the Powerplay, although the latter only bowled in one six-over Powerplay in which the batting team was scheduled to bat for 20 overs.


Middle Overs Analysis: Batting

Team/CategoryNumber of Middle Over PhasesAverage Runs ScoredAverage Wickets LostAverage Boundary PercentageAverage Dot Ball Percentage
Afg373.662.3311.11%31.11%
Ban2963.57.22%24.16%
HK2632.667.22%32.77%
Ire172413.33%31.66%
Net173311.66%35%
Oma168535%35%
Sco2693.57.5%33.33%
Zim3703.668.33%31.66%

The two qualifiers, Afghanistan and Bangladesh, performed best in the middle over phase with the bat. Bangladesh comfortably scored the most runs on average, thanks largely to their 110-3 against Oman – which was the only three figure phase score. Bangladesh had the joint lowest boundary percentage but made up for it with the lowest dot ball percentage. Afghanistan lost the fewest wickets in the middle over phase and had the second lowest dot ball percentage after Bangladesh. Zimbabwe had a notably low dot ball percentage, only fractionally worse than Afghanistan’s, but lost a high number of wickets on average in the phase.

Middle Overs Analysis: Bowling

Team/CategoryNumber of Middle Over PhasesAverage Runs ConcededAverage Wickets TakenAverage Boundary PercentageAverage Dot Ball Percentage
Afg357.664.334.44%37.22%
Ban173311.66%35%
HK264.52.57.5%35.83%
Ire168510%35%
Net182415%30%
Oma2913.520%25%
Sco375.662.6611.11%26.11%
Zim376.332.3311.11%30.55%

The middle over phase is where Afghanistan clearly put distance between themselves and the rest of the teams. Only Ireland took more wickets on average than Afghanistan and only have one innings worth of data. No team conceded fewer runs on average, no team conceded a lower boundary percentage and no team had a higher dot ball percentage.


Death Overs Analysis: Batting

Team/CategoryNumber of Death Over PhasesAverage Runs ScoredAverage Wickets LostAverage Boundary PercentageAverage Dot Ball Percentage
Afg338.331.6622.22%23.61%
Ban239.5120.83%35.41%
HK233.33210.41%31.25%
Ire136112.5%37.5%
Net133212.5%16.66%
Oma 146212.5%25%
Sco233211.17%24.05%
Zim333.33313%31.69%

Of the teams to have played at least two death over phases, the qualifiers Afghanistan and Bangladesh emerge as the teams with the highest average score in the phase and this is despite Afghanistan’s average score being skewed by completing their run-chase against Hong Kong with two overs remaining. The two qualifiers also boast the lowest average wickets lost in the phase and the highest boundary percentage too. Bangladesh did, however, struggle with dot balls in the final phase, with only Ireland, who played just one phase, demonstrating a higher percentage. Both of Bangladesh’s 20-over innings were recorded batting first.

Death Overs Analysis: Bowling

Team/CategoryNumber of Death Over PhasesAverage Runs ConcededAverage Wickets TakenAverage Boundary Percentage Average Dot Ball Percentage
Afg328.331.668.83%28.91%
Ban133212.5%16.66%
HK2262.518.75%33.33%
Ire146212.5%18.75%
Net138212.5%20.83%
Oma238.50.518.75%37.5%
Sco338212.5%20.83%
Zim343.332.6619.94%27.14%

Hong Kong’s low average runs conceded in this phase is misleading as Afghanistan only batted for two overs of it before beating them, they did still at least boast an impressively high dot ball percentage. Below Hong Kong in terms of average runs conceded again comes Afghanistan and Bangladesh, although the latter only defended one phase, against the Netherlands. Afghanistan, again performed well in terms of dot balls and boundaries but less so in terms of wickets. Zimbabwe, like they did in the Powerplay, averaged the most wickets taken, but were also the most profligate and conceded the most runs of teams to have played more than one phase.


Innings Analysis: Batting

Team/CategoryNumber of InningsAverage Runs ScoredAverage Wickets LostAverage Boundary PercentageAverage Dot Ball Percentage
Afg3158.33515.12%33.54%
Ban2166.5517.5%35.41%
HK31296.3310.83%40%
Ire1154515.83%41.66%
Net1145614.16%35.83%
Oma1158714.16%40%
Sco21467.511.75%36.96%
Zim31448.3311.70%36.61%

The result of their dominance through the batting phases is that Afghanistan and Bangladesh on average scored the most runs,  lost the fewest wickets and had the lowest dot ball percentage. Only Ireland prevents Afghanistan coming second to Bangladesh in terms of boundary percentages. Ireland, Hong Kong and Oman were conspicuously poor at rotating the strike while Hong Kong, Zimbabwe and Scotland struggled to hit boundaries.

Innings Analysis: Bowling

Team/CategoryNumber of InningsAverage Runs ConcededAverage Wickets TakenAverage Boundary PercentageAverage Dot Ball Percentage
Afg313379.20%37.99%
Ban1145614.16%35.83%
HK2138.5613.10%37.82%
Ire1158714.16%40%
Net1153713.33%35.83%
Oma2167418.75%38.33%
Sco31486.3314.16%31.25%
Zim3155.337.3314.50%37.41%

Zimbabwe’s wicket-taking threat posed in the Powerplay phase and the death over phase resulted in them averaging the most wickets taken, but they leaked boundaries regularly and could not bowl enough dot balls so ended up conceding a high number of runs. Afghanistan conceded the fewest runs thanks largely to a remarkably impressive boundary percentage of less than 10, which was considerably better than Hong Kong in second, who also conceded the second fewest runs. Of those to bowl in more than one 20-over innings Oman emerged with the highest dot ball percentage, followed closely by Afghanistan. Bangladesh struggled to prevent rotation the strike in their one 20-over bowling effort against the Netherlands. Scotland had the lowest dot ball percentage.


Freddie Wilde is a freelance journalist, @fwildecricket. 

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