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

1ST PAKISTAN V ENGLAND TEST ANALYSIS

The first Test of the series was largely a story of batting dominance. 16 wickets in four days and two first innings totals of 500+ suggested the final day would be a procession towards a draw. This proved not to be the case, thanks to a last gasp contribution by a leg spinner that ranked alongside the most dramatic of its kind.

That Adil Rashid’s 5-64 could not quite get England over the line did not prevent his spell from being the major contribution of the match. The Yorkshireman made a statement for the rest of the series, showing why he is so dangerous in the second half of matches.

Rashid’s final day burst followed the pattern he has set in county cricket in recent years. Like most leg-spinners, he is more dangerous in the second innings and against the tail – in the last three County Championship seasons he has taken more than twice as many tail-end wickets (7th to 10th to fall) than middle order (3rd to 6th).

Adil Rashid - last 3 County Championship seasons
Wicket to fallInns 1Inns 2Inns 3Inns 4Total
1st213
2nd3227
3rd2316
4th46111
5th14128
6th12227
7th17210
8th47415
9th557320
10th885122
3rd - 6th41012632
7th - 10th182714867

Rashid performed his Yorkshire role at Abu Dhabi and England fans should not expect anything else. His job is not to contain well-set batsmen on days one and two – few leg-spinners can – but to becoming an attacking option when tail-enders are at the crease or when the pitch offers more help.

The balance of England’s attack helps in this regard. The presence of Ben Stokes and Moeen Ali in the top six of the batting order means there are plenty of resources for Alastair Cook to juggle. A flat wicket like Abu Dhabi makes it hard for any bowler to contain batsmen in full flow, but the tourists at least have options to take the pressure off Rashid.

Not bowling the legspinner on day one does not necessarily denote a lack of confidence and the below BatViz numbers for spinners – statistics based on the quality of each ball rather than its actual outcome – show that in Moeen Ali England have a decent foil for Rashid.

BatViz Bowling Figures 1st Test - Spin
BowlerBallsWktsRunsAvgEcon
Moeen Ali2204.510924.12.98
Shoaib Malik235411529.12.95
Zulfiqar Babar463722932.72.97
Adil Rashid3164.415234.62.89
Joe Root300.41535.92.98
Asad Shafiq420.42053.12.84

Rashid’s own confidence on day five was evident and the below table shows how much more dangerous he became. He turned 77% of his deliveries on day five more than four degrees; this proportion was 63% in Pakistan’s first innings. His average amount of turn increased from 4.8 degrees to 6.1 degrees.

Adil Rashid in 1st Test
InningsAvg speed - mphAvg turn - degrees% turn > 4 degrees
1st48.94.863
2nd48.96.177

Pace bowlers also performed their expected roles. Mark Wood and Wahab Riaz are the strike bowlers in their respective bowling units and both produced the wicket-taking threat their captains desired.

The pace bowling BatViz numbers reveal that they had the best projected averages, based on the quality of the balls they delivered. BatViz evaluates every ball’s quality by comparing it with a database of similar deliveries and averaging the runs and wickets associated with these 1,000 similar deliveries.

BatViz Bowling Figures 1st Test - Pace
BowlerBallsWktsRunsAvgEcon
Mark Wood1763.69927.13.36
Wahab Riaz2474.5139313.37
James Anderson1912.89534.22.97
Ben Stokes1452.38335.63.43
Imran Khan1622.27935.92.91
Stuart Broad1752.38938.73.04
Rahat Ali1681.99449.93.34

Their BatViz economy rates also hint at their priority of taking wickets and England should be wary that Wahab’s strike bowling threat will probably increase should Yasir Shah return for the second Test. The left-arm paceman can be used in even shorter, pacier bursts with the team’s premier spin bowler operating for large parts of the innings.

WHAT’S WRONG WITH MS DHONI IN T20 CRICKET?

Since the Champions League T20 Final in 2014 Mahendra Singh Dhoni, one of the most successful T20 players of all time, has entered his worst period of form in his ten year career.

In 19 matches in 2015, 17 for Chennai Super Kings in the Indian Premier League and two for India, Dhoni has scored just one fifty, averaging 30.53—the lowest calendar-year average in his career—at a strike rate of 122.15—the second lowest calendar-year strike rate of his career.

PhaseInningsRunsBalls FacedAverageStrike RateFifties
Pre-20151724035295437.71136.5916
20151939732530.53122.151
Career1914432327936.93135.1617

After the second, and what turned out to be the final match of India’s three match T20 series against South Africa earlier this month, Dhoni sought to explain his poor form, by essentially saying that playing according to the situation in T20 cricket was hampering his returns.

“It is a very short format,” Dhoni said. “Personally I feel I use a bit too much of my brain in this format. It is very important that I keep myself a bit free, and go and play my shots.”

“A lot of times when I go in to bat, usually it is in the 16th or 17th over, or fourth or fifth over with four or five wickets down. I have that tendency to use my brain, ‘Okay let’s go to 130, that will be a good score.’ Depending on that I play a bit slow initially, and then look for big shots. It has happened quite a few times in the past, but in this format I believe what I should do is I should go in and play the big shots irrespective of what the scenario is. Because that’s what this format is all about.”

Only 15 players ever have played more T20 matches than Dhoni and few have been as successful as he has – so when he talks about T20 cricket, you should listen, but this explanation, one that chastises the use of thought, seems alarmingly shallow and very simplistic, and is a damning indictment on the T20 format.

Indeed, given the weight of the accusation levelled at T20 cricket, and more specifically, with the World T20 less than six months away, the importance of Dhoni in India’s T20 team and the importance of the role he is supposed to be playing, his explanation and solution is deserving of closer inspection.

What is so interesting about Dhoni’s statement is that he is conspicuously simplifying a game that he originally became excellent at by complicating.

A close look at the numbers show that Dhoni owes an enormous amount of his success in T20 cricket to the fact that he does use his brain, that he does play particularly carefully according to the situation and the opposition and, most notably, that he does not play big shots irrespective of what the scenario is. Dhoni’s approach to batting in T20 has in fact been the polar opposite of what he is suggesting.

Dhoni has scored 17 fifties in T20 cricket—all of them in the IPL. For the sake of this investigation those 17 fifties are going to be used as the gold standard against which to compare his more recent struggles.

Screen Shot 2015-10-14 at 13.53.58

A close look at the data from those 17 fifties shows that Dhoni takes some time to play himself in, with his average strike rate in those 17 innings not exceeding 100 until the sixth ball he faces and not reaching the average strike rate of 135.24 until the twelfth ball of his innings.

Immediately this data is at odds with his suggestion that he should “go in and play the big shots irrespective of what the scenario is.” For Dhoni it seems, like many players before him, the old adage of “getting your eye in” still applies. Even in the shortest of formats there remains value in taking a few balls to get used to the nature of the pitch, conditions and bowlers.

More interesting however, is the breakdown of Dhoni’s run-scoring in those 17 fifties against each bowler he faced. Dhoni has faced at least four bowlers in each of his 17 T20 fifties and never more than six.

Screen Shot 2015-10-14 at 13.54.01

Ordering Dhoni’s strike rate against each bowler in each innings from highest to lowest allows us to calculate the average strike rate against the most expensive bowler through to the least expensive bowler.

The range between the highest average strike rate, 305.55, and the lowest average strike rate, 45.79, of 259.76 is vast and suggests quite explicitly that Dhoni does use his brain when he is batting in T20 cricket – at the very least to decide which bowler to attack and when.

If T20 cricket and success in it is about “playing the big shots irrespective of what the scenario is” then surely the range between Dhoni’s highest and lowest average strike rate per bowler would be far lower. The numbers suggest that Dhoni, as is widely believed, picks a bowler and a moment to attack, rather than indiscriminately doing so, and that T20, like other formats of cricket, remains hugely influenced by shot selection and not purely shot execution.

So what has changed this year? Well, it can’t be the mind. If anything the mind is a tool that becomes sharper with age. Dhoni should in fact be getting better at reading a match situation and at choosing who and when to attack. Indeed, a closer look at all 19 innings played by Dhoni in 2015 reveals that he has been approaching innings in much the same way as he did in his 17 fifties with the two lines almost fitting neatly in to one another.

Screen Shot 2015-10-14 at 13.54.04

What has, quite obviously changed, is the strike rate. Although Dhoni still appears to be approaching an innings with the same strategy, he is not executing that strategy as well. His average strike rate in his first 15 balls of his innings in 2015 is just 113.33 and the highest it reaches at any point is 122.83, suggesting that not only is he taking longer to play himself in, but that even then he is struggling to accelerate as he once did. Dhoni in 2015 has been a shadow of his former self.

Of course, Dhoni has been an outstanding performer for almost a decade and it would be wrong to write him off completely after one bad year, but given the extent of this slump and given his age—he is now 34—it is possible that he is in terminal decline. While his mind will not wither the data shows that Dhoni is struggling to score at the pace he was once capable of suggesting that his power, eyes, and hands are beginning to fail him.

Although flashes of power may return Dhoni would be best served by remoulding his game to utilise his enormous experience and using that brain he is so keen to discard. Although the consistent power may have gone Dhoni still possesses one of the finest T20 brains in history, if he can marry that intelligence with an adapted strategy he could continue to succeed at the highest level.

Given that the ratio between Dhoni’s failures and successes is worsening, India, CSK and Dhoni would perhaps be best served by relieving the reliance on his successes by taking him away from the final stages of innings, and rather than giving him a high intensity role in the team’s innings; giving him a more disposable one.

On average the number six batsman faces 12 balls per innings and the number seven faces 6 balls an innings, given his even greater recent proclivity to eat up balls at the beginning of his innings there is no way that Dhoni should be batting as low as six, seven or even five; he would be better placed at number four, or perhaps, depending on the situation, number three, anchoring the innings and marshalling those younger, more powerful players around him.

India have, to an extent been hamstrung in this strategy by the dearth of alternative finishers to Dhoni, but if they aren’t going to drop him (given his experience and captaincy they shouldn’t) they need to utilise him better and try a new, younger alternative at the death, Hardik Panyda, for example.

If Dhoni can maintain his high levels of fitness his innings at number four can come to be defined not by brutal explosions of power, but instead by intelligent cricket, persistent running between the wickets and consistent proactivity.

This approach is a far lower risk strategy than his suggestion of arriving in the middle and hoping he can slog his way back to form when all evidence suggests he will fail. He will of course still have to hit boundaries, and he still can, but rather than relying entirely on doing so, a redefined approach and a new role can ensure there remains enormous value in Dhoni’s continued presence in any side he plays for.

Freddie Wilde is a freelance cricket journalist. 

PAKISTAN V ENGLAND SERIES PREVIEW

Predicting what will happen in England’s Test tour of UAE is a difficult task. Will we see a run feast, or perhaps death by spin? A Joe Root masterclass, or maybe a seamer-inspired show of English bowling strength?

The memories of 2012 are fresh. England arrived as the number one-ranked Test team. Unbeaten in nine series, they had risen from seventh to first in that list in little more than two years. Ashes winners down under and World T20 champions, a win in alien conditions against a talented, if fragile, Pakistan team seemed very much achievable.

However, England were humbled in all three Tests, coming out second best in a series that was defined by the bowlers. The expected attritional slog never materialised – batsmen struggled from the outset, with England’s 58-5 at lunch on day one of the opener setting the tone.

Azhar Ali scored 251 runs in his five innings, but no other batsman from either side averaged more than 40 in the series. On supposedly batsman-friendly wickets, the England batting unit misfired spectacularly.

The tourists’ opening day collapse was followed by a slump to 87-7 in the second innings and a failure to chase 145 in the second Test. They followed that by earning the unwelcome accolade of becoming the second team to lose a Test after dismissing the opposition for below 100 on day one.

The bowling attack functioned well. Stuart Broad took 13 wickets at an average of 20.4, Monty Panesar 14 at 21.6, Graeme Swann 13 at 25.1 and James Anderson nine at 27. However, the batting gave little respite – England were in the field on every day of the series.

Saeed Ajmal (24 wickets at 14.7 average) and Abdur Rehman (19 wickets at 16.7) were rampant. On low, skiddy pitches they bowled quickly for spinners, often touching 60 mph, testing both edges of the bat.

The pitches brought the stumps into play throughout, and a combination of excellent bowling and the new DRS system contributed to a record number of LBWs – the 43 in this three-match series is the joint-most ever recorded in a Test series.

However, the tour as a whole was not a disaster for England. They bounced back in the ODI series to deliver a whitewash of their own, and learned enough to seal a historic Test series triumph in India the following winter, the first by an England team in nearly 30 years.

So what can we learn from the last tour?

Attack the Stumps

Bowling straight in UAE gains much more reward than other host nations. Far more batsmen are dismissed bowled and LBW than the worldwide average, and in particular in comparison to Tests held in England.

Dismissals in Tests by venue
BowledLBWTotal
UAE19.7%24.8%44.5%
England16.7%14.6%31.3%
World17.1%16.9%34.0%

This table shows that nearly half of all dismissals in UAE are bowled or LBW, compared to less than a third in England. In the 2012 series 22.6% of the balls bowled would have gone on to hit the stumps. By way of comparison, in the fourth Ashes Test at Trent Bridge this summer, 9.1% would have struck the timbers.

The prominence of spin is obviously a major factor here – over half the overs bowled in the UAE are bowled by spinners, whereas in England it is about a quarter. Spinners bowl more balls that would hit the stumps, whilst the lower bounce of the pitches means that both seamers and spinners can hit the stumps from shorter lengths.

A Spinner’s Length

In general, balls that are hitting the stumps in Test cricket have a considerably lower average than those that don’t. For spinners, about 25% of balls bowled would go on to hit the stumps, and these take their wickets at an average of 17.4; the balls that are going to miss the stumps average nearly three times as much.

Stumps - Spinners% BallsAverage
Hitting25.7%17.4
Missing74.3%48.1

What the Pakistani spinners did particularly well in 2012 was to bowl quicker, dragging their lengths back a little whilst still attacking the stumps. Monty Panesar was able to perform a similar role for England when he was selected for the second Test.

 Average SpeedStumpsAverage LengthBatViz Predicted AverageSeries Average
Aimal56.136%4.724.814.7
Hafeez54.940%4.525.916.0
Rehman57.039%5.026.916.7
Panesar55.435%4.829.021.6
Swann52.932%4.539.325.1
Pietersen53.322%4.742.8-

The spin bowling in this series was of a very high standard. Spinners normally average around 36 in Tests, so for BatViz to be predicting averages in the 20s the size of the challenge facing batsmen is evident. The actual Series averages show how much batsmen struggled to cope, with all the spinners having greater success than was expected.

For comparison, here are the statistics of spinners in the Ashes Test at Cardiff. They bowled slower and fuller, and were less able to attack the stumps.

 SpeedStumpsAverage Length
Root53.231%4.2
Ali50.822%4.5
Lyon52.423%4.3

Pakistan start as favourites

With their strong batting and bowling line-ups and traditional strength in familiar conditions, it is no surprise that WinViz favours Pakistan at the series outset.

WinViz   
EngDrawPak
1st Test28%21%51%
Series23%19%59%

PROBABILITY SPACES IN TEST CRICKET

The first Test at Abu Dhabi is moving on quickly. You have just checked WinViz and it has Pakistan at 42%, England at 35%, and the draw at 23%. You then look at PredictViz and it is showing an England win by a handful of runs. Surely something has gone wrong? One tool is saying Pakistan are going to win, the other that England are.

There has not been a technical meltdown; the CricViz tools are working correctly. Remember, we are not predicting a Pakistan victory. In fact, we think Pakistan are more likely to not win (58%), than win (42%). Therefore, it should not be a huge surprise that the average result is not a Pakistani win.

But wouldn’t you expect the average result to come from the most likely outcome?

Well, sometimes it does, sometimes it doesn’t. There are a couple of concepts to understand before looking at the details of why this happens.

First of all, percentiles: If you are in the 40th percentile for height, you would expect 40 out of 100 people to be your height or shorter. If you were in the 95th percentile for height then you would expect only five in every 100 people to be taller than you.

Similarly, if we look at the possible range of scores for a Test team we can use percentiles to measure how likely a team is to make a certain score. For example, let’s look at an average team batting second in a Test match. A score of 420 is in their 70th percentile. 30% of the time they will score more than 420.

Secondly, let’s take a look at probability spaces. Imagine we each roll a six-sided die and add the two numbers together. There are 36, equally likely outcomes, which we can illustrate in a diagram:

roll 1

As you can see, the total eight occurs five times, so we can say that the probability of getting a total of eight is five in every 36, or 5/36.

We are now going to play a game. The rules are as follows:

1.) If your score is greater than or equal to mine, then you win
2.) If my score is greater than yours, I win.
3.) However, if we both throw a 4 or higher, then it is a draw.

How likely is each of the three results? We can look at the probability space to tell us:

roll 2

So, in 15 of the 36 possibilities you win, so you will win 5/12 of the time. I will win 12 out of 36 or a third of the games, and a quarter will be draws.

We can take the same approach with Test matches, by creating a probability space based on how well each team scores during the match. Let’s take a look at the probability space of a Test match between two well-matched teams with no weather interruptions.

Here the batting performances of each team form our axes. So the left-hand side are low Team A scores, the right-hand side are high scores. The top half of the chart shows good Team B batting performances, the bottom half are poor performances. As you can see, when both sides score highly (top, right-hand corner) we get a draw. When one side or the other scores poorly, they tend to lose.

Probability space for two well-matched teams:

Probability-Space-blog-tables-Tables-1

So, if Team A’s scores are in the 70th percentile then we are looking at the column above the number 70.  And we can see by looking up this column that they won’t lose if they bat this well.  The result now depends on Team B’s batting.  If they perform better than their 40th percentile then they will save the match, otherwise Team A will win.

One thing you will notice is that the chart is not exactly symmetrical.  The team batting first has a slight advantage in terms of scoring; the pitch tends to be more batsman friendly in innings 1 and 3 than in 2 and 4.  So in low-scoring matches, where there will be a result, Team A has a slight edge.  If you look at the 100 squares (from 5th to 50th percentile for each team) in the bottom left-hand section of the chart, you will see that 53 of them are blue Team A wins, and 47 are red Team B wins.  The blue squares include the 50th percentile match, our median match, which is what PredictViz shows.  If both teams produce their average performance, then the result will be a Team A win by a very small margin.  This is true even though the balance of power lies with Team B who will win 7% more matches than Team A.

So, if Team A scores more runs, why does Team B win more matches?  Well, the key is what happens in relatively high-scoring games.  It is far easier for Team B to force a result in matches where they bat well.  Look at the top, right-hand corner of the chart where both sides have batted better than average.  You can see that the red squares extend into this space where as the blue squares don’t.  There are no wins to the team batting first in matches where both sides score relatively highly.

We can see what this means in reality by thinking about the effect of a first innings lead.  If Team A gets a first innings lead, then to win the match they will generally bat on until they can make the game safe, declare and then bowl out the opposition, who know just what they have to do to save the game.  On the other hand, if Team B get a first innings lead, they just have to bowl Team A out and chase down the resulting total.  They are able to use the time left in the match far more efficiently to force a result.

PredictViz shows what will happen if both teams perform exactly as expected, how their innings will fall across the days of the match and what the average shape of the match from here will look like.  It is obviously showing just one of the infinite ways that the match can evolve from here.  How many of those fall to each team is represented by WinViz.

LAYING FOUNDATIONS

The United Arab Emirates is an appropriate place to seek the fresh laying of solid foundations. England have not settled on a Test opening partnership in recent years and Alastair Cook will have another new partner as his team seeks to construct some high-rise totals in keeping with the Emirati skyline.

Six players have tried to fill the role Andrew Strauss vacated in 2012. The lack of progress is shown by the fact that the man first given the chance was the most successful. Nick Compton averaged 57.9 in his 17 opening stands with Cook; none of the subsequent five candidates have averaged above 32.3 in unison with the skipper.

Compton was partly dropped for his slow scoring, a trait that has characterised all of these partnerships – the desire to pair Cook with a more fluent scorer led the selectors to Adam Lyth, whose average first wicket run rate of 2.83 with Cook was the highest of the six combinations.

England opening partnerships since August 2012
Cook and..PartnershipsRunsHighestRuns per over100 standsAverage
Compton179272312.69357.9
Robson11355662.76032.3
Lyth134021772.83130.9
Root10266682.25026.6
Trott61541252.44125.7
Carberry10250852.81025.0

Current candidates Alex Hales and Moeen Ali offer various attributes, but both have the range of shot and intent that is seemingly required in the continuing search for top order stability.

After hitting 907 Test runs at an average of 50.4 this year, Cook’s patient approach of accumulation is in good order – will it be Moeen’s elegant left-handed aggression or the powerful belligerence of Hales that provides the impetus?

The Cook – Compton axis was a crucial part of England’s success in India in 2012/13. They piled up 493 runs in their eight opening stands, at an average of 70.4. Their steady scoring rate of 2.69 runs per over was not a problem in the context of such productivity – Cook in particular went on to score heavily against toiling spinners when well-set.

However, a solid base does not guarantee success in spin-friendly environments. David Warner and Chris Rogers largely did a good job at the top of Australia’s order in their humbling 2-0 defeat against Pakistan in the UAE in 2014/15. Australia were comprehensively out-batted overall.

They averaged 53 in their four partnerships, recording their team’s highest stand of a disastrous tour, 128 in the very first Australian stand of the series at Dubai. Pakistan’s average opening partnership was 35.8, but this was the only area that the tourists out-batted the series winners.

Average partnerships 2014/15
WicketPakistanAustralia
135.853.0
255.012.0
3174.016.3
4202.532.0
558.538.5
674.036.3
736.011.5

The first wicket was the only one in the top seven for which Australia had a higher average partnership than Pakistan. Solid starts were wasted by an under-performing engine room: Pakistan averaged 174 for the third wicket, Australia 16.3. The disparity was 170.5 runs for the fourth wicket.

Australia’s batsmen were blown away in the UAE in 2014/15. England will need to have more than a steady opening partnership if they are to prosper against Pakistan’s talented bowling unit.

4TH ASHES TEST ANALYSIS

On the first morning of the Trent Bridge Test match, Australia batted first and at the first drinks break were 38 for 7, their top seven all back in the pavilion. England started batting 50 minutes later and an hour into their innings were 30 for 0. The Ashes were, barring a freak turnaround, already on their way back to England.

What happened? Why did Australia collapse so dramatically? Great bowling? Poor batting? A green-topped, bowlers’ dream that simply handed the match to the captain lucky enough to win the toss?

Why was the first hour of England’s innings so different to that of Australia’s an hour and a half earlier?

Did the conditions get easier?

A little. The ball kept swinging; the average deviation in the air when the Australians bowled was 2.1 degrees, slightly more than the 1.9 degrees when England bowled. Both teams swung roughly 60% of the balls they bowled by more than 1.5 degrees, the amount of swing that starts to have a significant impact on a batsman’s performance.

There was more seam movement when Australia batted. 31% of the balls in the first hour deviated by more than one degree off the pitch, whereas the figure when England batted was 18%. The average seam movement faced was 0.7 degrees for Australia and 0.5 degrees for England.

However, this was part of a pattern in the series. England’s seamers got more lateral movement off the wicket and were more accurate throughout; the Australian pacemen consistently bowled a little quicker on average and got more movement in the air.

Conditions had got a little easier by the time England batted, but not drastically so.

Did England out-bowl Australia?

England, and Stuart Broad in particular, bowled very well. A traditional good length in Test cricket is usually defined as balls pitching six to eight metres from the stumps. These are the balls that have the lowest average (runs per wicket), regardless of pitch, conditions and opposition. When the ball is moving around in the air and off the wicket, the metre or so fuller than that (5-6m from the stumps) becomes equally, if not even more, dangerous. England landed just over 60% of their deliveries in these areas, and these balls accounted for all but one of the wickets in that innings. Australia though, bowled even more balls on these lengths, 67% in their first 11 overs.

The England bowlers also bowled unusually straight. Their average line was middle and off, very straight for Test cricket; 49% of the balls they bowled were within the line of leg stump and six inches outside off stump. It was the balls on these lines that did the bulk of the damage to the Australian top order.

Australia bowled significantly wider. Their average line was six inches outside off stump – they put 52% of their deliveries wide of this mark, compared to 35% of England’s. This allowed England’s batsmen more easy leaves than the Australians got, nearly half as many again.

So, as was the case all summer, better areas and more movement off the pitch from England, albeit at a slightly slower pace. When the pitch offered assistance, England were the more dangerous attack. When it didn’t, Australia’s pace and swing posed the greater threat. Trent Bridge was no minefield, but nor was it the pitch where you wanted your great strength to be taking the pitch out of the equation.

Did Australia go too hard at the ball? Play too many shots? Not leave well enough?

Using the BatViz system we can compare how Australia played the deliveries they faced with how an average Test side would have played them.

Given the balls they faced, we would have expected 25 attacking shots in the first hour. Australia played 22. BatViz projected 14.5 balls to be left; they played no shot on 19 occasions.

For comparison, we would have expected England to play 24.5 attacking shots and they played 21. They got more balls to leave, as Australia bowled wider than England. 17.5 leaves were forecast – they actually left the ball 25 times.

First hour BatViz shot analysis   
AustraliaEngland
Attacking shotsExpected2524.5
Actual2221
LeavesExpected14.517.5
Actual1925

There therefore seems to have been little difference in the overall intent of the two sides and it is worth noting that only three of the seven Australian wickets fell to attacking shots. That might be three too many given the situation and conditions, but it is easy to criticise attacking shots when they don’t come off and applaud them when they do: England showed a very similar level of attacking intent and left the ball marginally better.

Was it therefore poor shot selection and execution?

Given the balls received, BatViz projected 11.9 false shots – edges and misses – from the Australians. There were 19. For comparison, we would have expected eight false shots from England and there were just six (five misses and one edge). On average in 11 overs of Test cricket there would be 4.5 false shots.

England had to play fewer balls and the balls they played at moved a little less. They also played them better than par, whereas the Australians underperformed against the balls they faced.

First hour BatViz false shot analysis  
AustraliaEngland
False shots - predicted11.98
False shots - actual196
Missed105
Edged91
Wickets from edge60

Even so, 19 false shots to six can’t be the difference between seven down and no wickets very often.

So were Australia just unlucky?

They certainly were to an extent. Of their 19 false shots, nine were edges (47%). Generally only about 37% of false shots are edges, so they were unlucky to nick almost as many as they missed. England played and missed five times for their solitary edge.

About 15% of edges result in a wicket. Australia’s nine edges produced six wickets, so the picture of a perfect storm is forming. The pitch had good carry, so there was little chance of edges with the new ball falling short of the slip cordon. The England bowlers’ areas were good, so the edges produced were more likely to find catchers than fly to safety. Two wickets in the first over meant that for the remainder of the innings Alastair Cook employed five or six catchers, so any edge was likely to find a catcher rather than a gap.

And what about the catching?

The first hour brought five slip catches, the innings as a whole comprised eight. Every single one of the chances offered were held, including Ben Stokes’ stunning one-handed grab.

On average in Test cricket roughly 70% of slip catches are caught. PlayViz goes deeper by rating chances according to where they come and the reaction time the fielder has. In doing so we can estimate that the five chances presented in the first hour would normally have resulted in two or three wickets (2.65 to be exact): the English cordon hugely over-performed.

A bit of everything?

The Australians were hit by a perfect storm of several factors, each multiplying the effect of the others that together created a manic 11 overs that devastated their Ashes dreams.

The ball swung and seamed enough to trouble the batsmen. The bowlers – Broad in particular – used the conditions very skilfully, and allowed the batsmen little respite. The Aussies didn’t cope with the moving ball particularly well and didn’t have a lot of luck when it came to playing and missing. A pitch with good pace and bounce ensured the edges carried and early wickets meant a packed slip cordon. The chances went to hand and the fielders caught exceptionally well. 38 for 7. Ashes gone.

3RD ASHES TEST ANALYSIS

After ending the Lord’s Test with a batting collapse, England inflicted one of their own on the opening day of the third Test. Conditions were rather different at a damp Edgbaston to those which Australia prospered in at Lord’s and James Anderson duly delivered a seam bowling masterclass.

The Lancastrian’s 6/47 helped bowl out Australia for 136 inside 37 overs, a collapse which saw the tourists’ starting win probability of 31.9% reduce to 11.7% at the change of innings. Anderson’s lateral movement proved too difficult for Australia to deal with, but their shot selection played a major part in their slump.

The analysis of Hawkeye data for each delivery reveals how the Australian top order got caught in two minds when dealing with Anderson’s movement. As well as producing the average wicket probability and run total for each ball based on similar deliveries in the CricViz database, BatViz can analyse the type of shots played (see below table).

Anderson delivered 88 balls in Australia’s first innings. Of these, 10 had an attacking shot percentage between 40% and 49% – based on the similar delivery evaluation, these type of balls are typically attacked somewhere between 40% to 49% of the time.

All four of Anderson’s top order wickets – David Warner, Adam Voges, Mitchell Marsh and Peter Nevill – fell in this range. Warner (playing defensively too late), Voges (withdrawing his bat to leave too late) and Nevill (no shot) paid the price for tentativeness; Marsh (flat-footed drive away from body) ill-advisedly took the attacking option.

BatsmanShot typeDismissalLeave %Attacking %
WarnerDefensiveLBW3.745.3
VogesNo shotCaught31.344.9
MarshDriveCaught38.748.9
NevillNo shotBowled3.441.1

The type of deliveries Warner and Nevill received were clearly ones to play at. BatViz takes into account the speed, line, length and deviation when picking out similar deliveries and these two balls that were on the stumps were left alone just 3.7% and 3.4% of the time respectively.

This highlights the seeds of doubts that Anderson can plant in a batsman’s mind, despite the lack of extreme pace. Warner’s wicket was 82mph, Nevill’s 83.6mph. His day one wicket burst against a confused batting line-up was the crucial factor in England’s victory, a template that was followed emphatically at Trent Bridge by Stuart Broad’s opening salvo.

2ND ASHES TEST ANALYSIS

England maintained their pattern of following a win with a defeat due to a below par performance in all three disciplines at Lord’s. After winning the first Test with positive PlayViz scores in batting, bowling and fielding, they slumped well below what was expected at headquarters.

In being dismissed for 312 and 103 on a flat wicket, the hosts recorded a batting score of -267 in PlayViz – they scored 267 runs below what an average Test team was projected to score in those conditions and against that bowling attack.

Australia’s seam unit was as expected quicker than their counterparts, averaging more than 3mph faster, but crucially their accuracy and movement in their air was also superior. England seamed the ball more, but the tourists attacked the stumps with greater frequency (13% in line with stumps, England 11%) and found a way to swing the ball more as the Test developed.

10% of England’s pace deliveries swung more than 1.5 degrees in Australia’s second innings, compared with 29% of Australia’s as they stormed to victory. This was a higher proportion than they recorded in England’s first innings (26%).

England’s lack of incisiveness – the tourists declared twice – contributed to a bowling score of -135, vastly inferior to Australia’s 452. Mitchell Johnson led an attack that showed its suitability to the Lord’s conditions, assisted by a fielding effort that out-performed England; Australia dropped five chances, England eight.

ENGLAND V NEW ZEALAND 2ND TEST ANALYSIS

England started the second Test against New Zealand ideally placed. A thrilling win at Lord’s and first use of an inviting Headingley pitch in overcast conditions suggested the hosts’ seamers would make a decisive contribution on day one.

James Anderson reduced the Black Caps to 2-2, but a buccaneering counter attack from the Kiwi middle order took the initiative away from England that they never regained. The key factor in New Zealand’s 199-run win was the bowling of Tim Southee and Trent Boult.

They out-performed Anderson and Stuart Broad to ensure England could only match New Zealand’s first innings 350, despite reaching 177 for no wicket. The Black Caps opening attack ‘only’ took nine wickets between them, a return that does not represent the difficulty they caused England’s batsmen.

BatViz measures the likelihood of a wicket for every delivery, using a database of similar deliveries according to speed, line, length and deviation. This allows bowler performance to be interpreted beyond what is shown in the scorecard. The below table shows this BatViz data by bowler for the second Test.

BowlerBallsWeighted runsWeighted wicketsWeighted averageWeighted economy
Trent Boult3201517.520.22.8
James Anderson217954.023.92.6
Tim Southee2911525.328.43.1
Stuart Broad2001003.429.23.0
ALL BOWLERS2190110237.329.53.0
Mark Wood1981123.730.53.4
Ben Stokes174983.032.73.4
Moeen Ali162752.135.02.8
Mark Craig3471674.537.12.9
Matt Henry1971072.739.63.3

So as neatly as Mark Craig bowled at Leeds in taking five wickets, the role played by Boult in claiming four scalps was more instrumental in the tourists’ series-levelling win. The 320 balls delivered by the left-armer had a weighted wicket value of 7.5 and an average of 20.2. England were facing a bowler testing them far more than his match figures of 4-159 suggest.

From 231-2 England scored 31 runs for the loss of six wickets in the next 14 overs, all of which were bowled by Boult and Southee. They took two and four wickets respectively in this spell, but it was a prime example of a bowling partnership – Boult’s wicket-taking threat certainly contributed to Southee’s haul.

ENGLAND V NEW ZEALAND 1ST TEST ANALYSIS

The first Test of the 2015 English summer was a rollercoaster affair that showed the format in its best possible light. Both teams held dominant positions in a high quality contest that gave the CricViz tools full opportunity to show their uses.

England started the Test with a win probability of 53% in WinViz, which they lifted to 60% at stumps on day one. At drinks on day three this had fallen to 6% as New Zealand made early inroads after piling up a first innings total of 523; England needed something special, and they got it from Ben Stokes.

The Durham left-hander smashed the fastest Lord’s century, a game-changing innings that showed how individual brilliance can turn WinViz on its head. When Stokes arrived at the crease England had a win probability of 17% – when he was dismissed 109 minutes later for 101, it was New Zealand’s win probability that stood at 17%.

Stokes’ knock was the ultimate counter-attacking innings. He thrived under the pressure of England’s perilous position, playing with his trademark aggression despite the quality of the Black Caps bowling attack and the fact he did not score from his first nine deliveries.

An interesting feature of his innings was that New Zealand bowled better to him as the belligerent knock developed. Rather than wilting in the face of the barrage, the wicket-taking threat actually increased: Stokes first 46 deliveries had an average of 1.18% chance of taking his wicket, his second 46 a 1.88% chance.

The BatViz calculation that measures projected average runs and wickets from each delivery produces a more expected pattern in Alastair Cook’s anchoring innings of 162. The first half of his stay at the crease had an average 1.82% chance of taking his wicket, the second half a 1.60% chance.

Stokes solidified his position as England’s talisman in this Test, producing two innings of huge importance that were notable not just for their impact but for their quality. He showed his team-mates that an aggressive mode of batting could thrive against good attacks in tricky conditions.