CricViz analyst Patrick Noone outlines how England should target Bangladesh’s key players.
Here you will find detailed analysis highlighted from the CricViz app.
Clive Azavedo introduces three new metrics for evaluating teams.
Freddie Wilde analyses whether the ball that spins into the batsman is more likely to take a wicket than the ball that spins away.
Freddie Wilde analyses whether the ball that spins into the batsman is easier to score off than the ball that spins away.
Boundary-hitting is arguably the most important skill in Twenty20 cricket, and is therefore a critical factor in assessing performance. Metrics such as boundary runs and boundary-balls-percentage don’t give us the full picture. A batsman who scores 65% of their runs in boundaries might be below average at rotating the strike. A batsman who hits half his deliveries to the fence could be swinging every other ball.
Ideally, we need to know how often a batsman attempts to hit a boundary and how successful they are when doing so. A boundaries attempted metric will be quite subjective. When a batsman has a big swing, it’s obvious what his intentions are regardless of the outcome. On the other hand, a simple leg-glance for a single might turn into a boundary if timed well enough. It’s also important to consider how the field is set and the situation of the game to give us extra clues about the batsman’s plans. However, without someone sitting down and explicitly recording boundary attempts in every match (as is done with ESPNcricinfo’s control metric) we will have to infer it from ball-by-ball data.
Defining a boundary attempt
Our data records 22 types of shots a batsman could play including all manners of drives, sweeps, pulls and cuts. Using data from over 2,000 T20 matches, we can analyse which types of shots are most likely to result in a boundary.
|shot type||boundary %|
Slog-sweeps result in a boundary 40% of the time followed by upper cuts and scoops on 34%. The top performing shots on the list down to and including reverse sweeps we may reasonably assume are played with the intention to hit a boundary. So let’s draw the line here and use these top 8 shots as our proxy for boundary attempts. Drives and conventional sweeps do result in boundaries but we’re not confident enough that they are always boundary attempts.
We also have data on what connection the batsman makes with each shot.
|batting connection||boundary %|
|Missed (Leg Side)||0|
|Play and Miss||0|
|Play and Miss (Leg Side)||0|
Middling the ball or getting a strong or well-timed connection results in quite high boundary percentages. We will take these three shots to add to our definition of a boundary attempt. Finally we will assume all free hits are boundary attempts.
Boundary attempts in the IPL
In this season’s IPL, there have been 2,484 boundary attempts from the 32 matches so far. That’s nearly 2 per over. Our definition covers 92% of all boundaries scored i.e. about 8% of boundaries are unintentional. The average boundary-success rate across the tournament is 49%.
The graph above shows the boundary success rate broken down by team. This correlates quite well with the current standings; Mumbai Indians have the highest success rate and are one of the form teams at the moment. Contrast this with RCB who have a success rate of 10 percentage points fewer, near the bottom of the table.
Gujarat Lions attempt by far the most boundaries per 120 balls faced. Their batting lineup, which includes Raina, McCullum and Finch, are making a concerted effort to hit as many balls to the fence as possible. However, their below-average success-rate suggests they’re not executing their plans. Interestingly, Mumbai Indians attempt the fewest boundaries of all the teams despite having the highest success rate. The likes of Nitish Rana, Jos Buttler and Pollard are choosing their boundary options with more care and it’s been working effectively so far.
Boundary attempts by player
Let’s take a look at boundary attempts on an individual batsman level. The table below shows the 47 players to have attempted at least 20 boundary hits.
|batsman name||boundary attempts||intentional boundaries||boundary success %||balls faced||balls per boundary attempt|
|AB de Villiers||37||17||46||117||3.16|
Sunil Narine, in his role at the top of the KKR batting order, has the second highest boundary success rate of 68%. He also has the fifth-lowest balls-per-boundary attempt figure – every other ball. At the other end of the scale, Pune’s Ben Stokes has been struggling, producing a 37% success rate. Meanwhile, Stokes’ teammate Ajinkya Rahane attempts a boundary almost every 5 balls – the highest in the list. However he does have the 3rd highest boundary success rate suggesting he is quite picky over which balls to target. This approach is perhaps not serving him so well as he has the lowest strike rate out of the top 20 run-scorers of the season so far.
This boundary-attempts metric has been fairly crudely formulated in this article. But there is clearly potential to lend insight into how teams and batsmen approach a T20 innings, and contribute to a more comprehensive analysis of a side’s performance.
Imran Khan, @cricketsavant
Now that cricketers have dispensed with the tedium of a winter rest (“Sleep’s for wimps”; Derek Trotter, 1985), instead plying their trade on the global cricketing treadmill, we are better equipped to look at recent form. There are almost no significant gaps in the T20 calendar, so a bowler who rocks up for one tournament in April probably had a stint in another tournament a few months prior. Their form guides are more accurate now than, say, in Test matches twenty years ago when – sweet mercy – cricketers had months to themselves, or spent it playing cards on the boat back home from somewhere hot. Or in the case of Andrew Caddick, learning to fly helicopters while painting Taunton’s pavilion – disappointingly not at the same time – as a memorable issue of Cover Point once regaled.
For us, it’s great news. In years gone by we’d look at a small sample of a player’s stats, based on last season, and make little of it. Now, however, we have an almost continuous sample of live data coming in which gives us a much broader view of the game’s critical areas, while ensuring it’s recent and relevant.
All of which leads to the following list of bowlers, and how they perform at the death (any bowler who has bowled more than six overs since the start of 2016, in overs 16-20).
IPL economy rates at the death
|Shane Watson||Royal Challengers Bangalore||174||110||16||12||9.49||pace||2016|
|Mitchell McClenaghan||Mumbai Indians||130||101||14||9||7.72||pace||2016|
|Mustafizur Rahman||Sunrisers Hyderabad||182||152||16||8||7.18||pace||2016|
|Chris Morris||Delhi Daredevils||64||68||12||7||5.65||pace||2016|
|Graham Wagg||Glamorgan (Wales)||100||66||12||7||9.09||NULL||2016|
|Rumman Raees||Islamabad United||46||52||7||7||5.31||pace||2017|
|Dwayne Bravo||Gujarat Lions||195||121||15||7||9.67||pace||2016|
|Sunil Narine||Melbourne Renegades||88||60||6||7||8.80||spin||2017|
|Lasith Malinga||Sri Lanka||65||43||4||6||9.07||pace||2017|
|Wahab Riaz||Peshawar Zalmi||63||72||9||6||5.25||pace||2017|
|Mohit Sharma||Kings XI Punjab||143||93||14||6||9.23||pace||2016|
|Umesh Yadav||Kolkata Knight Riders||82||52||9||6||9.46||pace||2016|
|Ben Laughlin||Adelaide Strikers||37||36||5||6||6.17||pace||2017|
|Jade Dernbach||Surrey (England)||69||67||6||5||6.18||pace||2016|
|Ashok Dinda||Rising Pune Supergiants||77||52||9||5||8.88||pace||2016|
|Mohammed Shami||Delhi Daredevils||62||46||8||5||8.09||pace||2016|
|Yuzvendra Chahal||Royal Challengers Bangalore||69||43||13||4||9.63||spin||2016|
|Anwar Ali||Quetta Gladiators||82||56||9||4||8.79||pace||2017|
|Sandeep Sharma||Kings XI Punjab||100||66||14||4||9.09||pace||2016|
|Jasprit Bumrah||Mumbai Indians||136||99||14||4||8.24||pace||2016|
|Michael Hogan||Glamorgan (Wales)||45||48||13||4||5.63||pace||2016|
|Kesrick Williams||West Indies||43||36||4||4||7.17||pace||2017|
|Ben Dwarshuis||Sydney Sixers||60||43||4||4||8.37||pace||2016|
|Tymal Mills||Quetta Gladiators||32||40||5||4||4.80||pace||2017|
|Bhuvneshwar Kumar||Sunrisers Hyderabad||166||111||17||4||8.97||pace||2016|
|Mark Steketee||Brisbane Heat||42||42||6||4||6.00||pace||2017|
|Ravi Ashwin||Rising Pune Supergiants||64||60||14||4||6.40||spin||2016|
|Ben Hilfenhaus||Melbourne Stars||60||52||8||3||6.92||pace||2017|
|Murugan Ashwin||Rising Pune Supergiants||74||52||10||3||8.54||spin||2016|
|Shane Watson||Sydney Thunder||39||37||5||3||6.32||pace||2017|
|Zaheer Khan||Delhi Daredevils||110||67||12||3||9.85||pace||2016|
|Sunil Narine||Lahore Qalandars||55||37||8||3||8.92||spin||2017|
|Tom Curran||Surrey (England)||83||66||13||3||7.55||pace||2016|
|Chris Jordan||Royal Challengers Bangalore||72||46||9||3||9.39||pace||2016|
|Dhawal Kulkarni||Gujarat Lions||88||61||14||3||8.66||pace||2016|
|Hasan Ali||Peshawar Zalmi||86||64||10||3||8.06||pace||2017|
|Mohammad Sami||Islamabad United||70||57||9||3||7.37||pace||2017|
|Barinder Sran||Sunrisers Hyderabad||60||47||14||3||7.66||pace||2016|
|Sohail Khan||Karachi Kings||75||46||9||2||9.78||pace||2017|
|Mohammad Nawaz||Quetta Gladiators||76||49||10||2||9.31||spin||2017|
|Nuwan Kulasekara||Sri Lanka||42||37||7||2||6.81||pace||2017|
|Piyush Chawla||Kolkata Knight Riders||47||38||11||2||7.42||spin||2016|
|Dwayne Bravo||Surrey (England)||56||41||6||2||8.20||pace||2016|
|Andrew Tye||Perth Scorchers||59||39||7||2||9.08||pace||2017|
|Sunil Narine||Kolkata Knight Riders||63||47||11||2||8.04||spin||2016|
|Tim Southee||Mumbai Indians||57||36||11||2||9.50||pace||2016|
|Johan Botha||Sydney Sixers||46||36||6||2||7.67||spin||2017|
|Mohammad Aamer||Karachi Kings||75||51||10||1||8.82||pace||2017|
Shane Watson, the interim captain for RCB in IPL 2017, was their go-to death bowler last season; his strike-rate was good, but economy was higher than the average. Jamie Overton, who has been on the cusp of an England career for a while, took death wickets for Somerset last year and kept his economy under 7/over, which isn’t approaching deadly-assassin status, but something close to it.
Chris Jordan, however, struggled in his the 2016 IPL (economy approaching 10/over) before following it up with a tighter performance for his home team Sussex a few months later. The green, green grass of home.
Try sorting the table and looking at who might pop up when we review the IPL mid-way through the tournament.
The IPL, about to enter its 10th season, pits teams that are somewhat evenly matched and compete in more or less homogenous conditions. This coupled with player drafts every three years should result in a competitive and exciting tournament every season. Six different winners in nine seasons suggests this has largely been the case. Imran Khan looks deeper into how certain teams have performed throughout their history by considering their Elo rating – a system that evaluates teams purely on their results.
Elo ratings introduction
A team’s Elo rating indicates its relative strength compared to other teams. When a team wins a game it gets transferred a certain number of points from the other team i.e. the total points for both teams stays the same. This ensures the average across all the teams stays roughly constant. Additionally, a stronger team will gain fewer points when beating a weaker team than the other way around. At the very beginning, every team is assumed to be of equal strength so start off with the same Elo rating (in our case it will be 1500).
Let’s say we have a match between Team A and Team B. Team A is stronger and has an Elo rating of 1600 compared to 1400 for Team B. The probabilities of the teams winning can be calculated to be 76% and 24% respectively (assuming there are no ties). If Team A does indeed win, their Elo rating will go up to 1604 and Team B down to 1396. However, if Team B causes a small upset and wins its Elo rating will go up 11 points to 1411 while Team A goes down to 1589. The intuition is that we would like to reward underdogs more for winning than we reward favourites for winning. Note that the total number of points is the same before and after the game.
A brief history of the IPL
Of the 584 scheduled IPL matches to date, there have been 568 outright winners, 6 ties and 10 no results. I have counted the winners of the super over after a tie as the overall winner and given half a win each to the teams involved in no results. The plot below shows the Elo ratings for each of the 13 IPL teams to have existed over the course of every season.
Although this looks quite cluttered at first, we can distinguish some general trends. The league was fairly closely contested in the first four seasons with 2010 the most tightly packed. No team reached an Elo rating of beyond 50 points from the average of 1500 in that season. In fact, 4 points separated 6 teams in the final standings with even bottom-placed Kings XI Punjab taking points off both eventual finalists. From 2012, things started to spread out a bit more as Chennai Super Kings dominated and some teams, in particular Delhi Daredevils, started to fall away.
Chennai Super Kings
The Super Kings, the most successful IPL team so far, won titles in 2010 and 2011, have a win rate of 61% and have made the playoffs in every season in which they participated.
During CSK’s first title win in 2010, the Elo ratings suggest they were far from the best team for much of the season. They scraped into a playoff spot on net run rate. They also won as many games as they lost in the group stages beating teams that eventually finished in the top 4 on only two occasions. In seasons 2013-2015, the Elo ratings suggest that there was a significant gulf between them and most of the other teams. The finished top of the group in 2013 and 2015 but ultimately stumbled at the playoff stage. What the graph above illustrates quite well is their performance peaking in the middle of each of the 2013-2015 seasons as opposed to at the end in 2010/2011.
CSK enjoyed the highest Elo rating of all time when they beat Kolkata Knight Riders by 2 runs in the middle of the 2015 season to take their rating up to 1609. We can conceivably say that this CSK team was the best of all time during that period. However, it was not to continue having staggered through the latter half of the 2015 season and losing in the final to the Mumbai Indians.
Daredevils and Warriors
In contrast, the Daredevils have been in a steady decline since 2010 after finishing 4th, 3rd and 5th in the first three seasons. Apart from in 2012 where they exhibited a brief resurgence, Delhi have finished at or near the bottom in every season since.
Their lowest point occurred at the beginning of the 2015 season. However, this was not the lowest of all time; the dubious honour being claimed by the now defunct Pune Warriors India.
The Warriors finished in the bottom two in each season of their fleeting existence winning only 27% of their games. A run of 9 consecutive defeats culminated in an Elo rating trough of 1378 points when they lost to the Mumbai Indians near the end of the 2013 season.
We can use the Elo ratings to compare the relative strengths of teams before each match. Of the 570 matches in which there was a result, 55.4% of favourites, according to Elo, won the game. If a team with a lower rating beat a team with a higher rating, we can quantify how much of an upset this was.
The table above shows the ten biggest upsets defined by the difference between the ratings of the two teams. The top match on the list was a surprise in more ways than one. Chennai were coming off the back of their peak Elo rating and Delhi were near the bottom of theirs. In that match, Delhi restricted CSK to just a run a ball and knocked them off with ease. The Daredevils also feature in a further six of the matches in that list highlighting how, in the last few seasons, any victory was a seen as a shock.
We can also consider which games were of the highest quality defined by the sum of the Elo ratings for both teams.
According to the system, the final of the 2015 season between Mumbai and Chennai was the highest rated match of all. Both teams had quite similar ratings. But as the graph shows below, Mumbai were the form team going into the final while Chennai were riding on their early-season performances. It’s probably no surprise that Mumbai won by a pretty hefty margin.
The Mumbai/Chennai rivalry takes up eight of the ten slots in the list. Mumbai follow a similar pattern to Chennai in terms of the Elo ratings although they are slightly out of phase. They tend to get off the mark slowly at the start of the season then surge to peak near the end. This is most noticeable in seasons 2008 and 2013-2015.
Improvements to Elo
The Elo ratings are based on a simple concept – a team is credited for winning and penalised for losing, while underdogs are credited more for winning etc. The ratings can be refined by considering home advantage, major team changes after auctions for example and the margin of victory. We can also dynamically change the importance of certain matches. For example, playoff matches may offer greater payoffs in Elo points while a team’s matches from several seasons ago can be discounted in value.
Imran Khan, @cricketsavant
You may be familiar with the CLR James epigram which features in the preface of Beyond A Boundary: “What do they know of cricket who only cricket know?”
I often find a total break from the game – in my case a week covering horse racing’s Cheltenham Festival – gives me renewed energy to enjoy cricket, and a hunger to delve into the unique CricViz stats that underpin a particular match.
In this case, I am drawn inexorably to Bangladesh’s maiden Test victory over Sri Lanka. Put in the shade as it invariably will be by the titanic continuing struggle between India and Australia (1-1 heading to a Dharamsala decider, by the way) I certainly feel it deserves some extra attention.
First of all, there is the sheer landmark nature of this result. In their 100th Test, this was only Bangladesh’s ninth win and their first away from home against a team other than Zimbabwe or West Indies. It also comes five months after their Dhaka win against England which followed a winless year in 2015.
Then there was the less than ideal background to the win: a heavy defeat in the first Test, serious pressure and rumours of an impending axing for the captain Mushfiqur Rahim, an injury to the wicketkeeper Liton Das and three other players dropped after the Galle setback.
WinViz suggests it was the Shakib innings that turned Bangladesh from underdogs to favourites
And finally there was the troubling scorecard late on day two in Colombo: Bangladesh up against it at 198-5 on day two, some 140 runs behind. WinViz had a Sri Lanka win at 62% with Bangladesh at 27%: not a hopeless position for the tourists but an unencouraging one.
It was at this stage that Shakib Al Hasan crafted one of the most important centuries of his career. A naturally exuberant player (his strike rate exceeds that of all top current batsmen other than David Warner) he elected to curb his instincts to some degree but still scored at a healthy rate.
He watched the ball onto the bat well: only playing and missing five times from 159 balls faced while producing only two outside edges. When attacking, he timed the ball well – indeed our analysis shows he mistimed just two shots, the second of which finally brought his dismissal on 116, an innings which turned a probable Bangladesh deficit on first innings into a very valuable lead of 129.
WinViz suggests it was the Shakib innings, alongside valuable contributions from Mushfiqur and Mossadek Hossain, which turned Bangladesh from underdogs to favourites. But sometimes the hardest thing in a Test match is to reinforce a dominant position, or to get the job done when you hold all the aces – particularly if you’re a team without much experience of winning.
The next part of the job was carried out by Bangladesh’s bowlers, led by the hugely exciting fast bowler Mustafizur Rahman, backed up admirably by Shakib’s resourceful slow left-arm stuff.
The key period came just after lunch on day four when these two bowlers operated in tandem and the draw had moved in excess of 50% probability on WinViz. Sri Lanka were 137-1, nudging into an overall lead – but suddenly Bangladesh found their bite.
The first breach came when Mustafizur had Kusal Mendis caught behind with a delightful delivery. It was the last ball of the over, and at 79.8mph it was the fastest too. Pitching on a fairly full, almost half-volley length – 5.9m from the stumps – it induced the drive.
All six balls in the over offered to swing away from the right-hander. But unlike two previous balls, which had carried on with the angle after hitting the wicket, this one straightened just enough (moving 0.9° degrees away from Mendis) to take the outside edge. Mushfiqur, the stand-in keeper as well as captain, gleefully accepted the chance.
Five overs went without a wicket before Mustafizur struck again. Continuing with a full length, he had Dinesh Chandimal fishing well wide of off-stump and nicking off. This was not per se a brilliant delivery, but an intelligent one, the sort with which Ian Botham used to take countless wickets. A tempting outswinger sometimes looks like it’s there to be hit. But Chandimal had not been at the crease long enough to play a relatively risky cover-drive and paid the price.
It was Shakib’s turn to get involved next: Asela Gunaratne lbw padding up for just seven. A misjudgement for sure, but again the bowler’s skills played their part: this ball drifted a fair bit, 2.5° into the right-hander who felt that on his initial observation he could afford to let this one bounce and turn away from him. The thing is the extra drift meant the ball was arrowing into the stumps and relatively modest turn away (2.6°, around half of the previous ball’s turn) meant it was straight enough to be hitting.
PlayViz recorded a -38 fielding score for the hosts
Shakib’s next wicket soon followed, a dismissal that reduced Sri Lanka to 190-5 (effectively 61-5). Bowling with a lovely rhythm, Shakib was getting some deliveries to turn really quite sharply, others to skid on without any turn at all. At times like these, batsmen often believe their best bet is to premeditate, and invariably out comes the sweep shot.
Niroshan Dickwella played one such sweep to a ball that turned a lot (6.6° in fact, putting it in the top dozen of Shakib turners for the innings). Also, the length was short of ideal length for sweeping, so the ball had time to turn and bounce before Dickwella’s bat made contact with the ball. Mushfiqur, who had a fine game behind the stumps, anticipated everything smartly to move across to complete the catch.
Sri Lanka fought on. The ninth wicket put on 80 to leave Bangladesh some kind of challenge, namely a target of 191. However the Tigers would not be denied and man-of-the-match Tamim Iqbal hit 82 (Shakib arguably had stronger claims to that individual gong). A memorable victory was achieved with four wickets in hand.
A final footnote: Sri Lanka have been poor in the field for much of the past six months and PlayViz recorded a -38 score for the hosts against a +52 aggregate for Bangladesh. The differential in batting was even more stark at +141 for the winning side (who had the clear disadvantage of batting second) against Sri Lanka’s -21. These indicators are very welcome for Bangladesh going forward while Sri Lanka’s side, still in transition following the retirements of so many key players of late, could find more roadblocks in their path.
This article is contributed by Imran Khan, who you can follow on Twitter @cricketsavant.
Seam bowlers dominated the top wicket-takers list, with only Usama Mir, Sunil Narine and Mohammad Nawaz representing the spinners. However, spinners did have a lower economy rate and strike rate than seamers over the whole tournament. Wahab Riaz and Hasan Ali, who picked up 27 wickets between them, spearheaded the bowling attach for the champions Peshawar. We’ll investigate what made them successful later on.
Tournament top run getter Kamran Akmal was most destructive against right-arm spinners and medium pace seam bowlers, against whom he scored 150 runs at a strike rate of 195.
The beehive plot below shows all of Akmal’s boundaries against these types of bowlers. He rocked onto his back-foot and seized on anything marginally short from the slow bowlers or went down the track to hit over the top.
In fact, Akmal scored 55 runs from the 36 occasions he played a shot off his back foot against right-arm spinners and medium-pace seamers. He also accrued 31 runs from the 10 balls he went down the track during the tournament.
Against fast seam bowling however, Akmal was restricted to a run a ball and dismissed three times.
The heat map above is generated from his dot balls against fast seam bowlers with his dismissals in red. He was generally kept quiet by good to back-of-a-length deliveries just outside off stump. In fact, from these types of deliveries Akmal scored 46 runs at a strike rate of 90 – well below his overall strike rate of 129.
Akmal was also relatively constrained by left-arm orthodox bowling scoring at a little over a run a ball and being dismissed four times.
The pitch map above shows a distinct cluster of dots and singles (red and blue) where the bowlers like Imad Wasim and Hasan Khan pitched it on a very good length. However, on the few occasions where they bowled full or a touch shorter, Akmal would take advantage.
The talk before the PSL was of Chris Gayle’s overwhelming superiority in T20 cricket having scored nearly 10,000 runs in the format. However, he is still 63 runs short after the end of the tournament having scored just 160 runs at an average of less than 18 and a meagre strike rate of 115.
Gayle struggled against fast seam and off spin bowlers striking at less than a run a ball and being dismissed four times each.
The heat map above shows the distribution of dot balls faced by Gayle against fast bowlers with his wickets in red. Back of a length and outside off stump is where most of the dots are concentrated. This is a bowling plan that has historically kept him quiet. In fact, he scored 25 runs from 24 balls including just 4 boundaries when facing deliveries in this region.
Gayle did not fare particularly well against right-arm off spin and left-arm orthodox bowling. The heat map above shows that his dot balls generally came when they bowled very straight to him on a good length, again something that spinners have exploited previously. Of the 21 balls he faced from off spin and orthodox bowling and which were on the stumps, he scored only 12 runs and timed exactly one ball (which was hit for six).
The best bowlers
Top wicket-taker, Karachi Kings’ Sohail Khan utilised his slower ball to great effect. He sent down 44 throughout the tournament earning him six of his 16 wickets whilst only conceding a run a ball (compared to his overall economy rate of 7.61). Second highest wicket-taker Wahab Riaz fared just as well conceding just 28 runs from his 35 slower deliveries and picking up two wickets.
Sohail Khan’s slower ball was very consistent in terms of speed as the histogram shows above. Wahab’s distribution is less pronounced indicating that his slower balls were a variety of speeds, with a slight bump at 130 kph.
21-year-old leg-spinner Usama Mir who took 12 wickets for Karachi Kings, the highest for any spinner, predominantly stuck to his stock delivery during the tournament. However, he did send down variation in the form of googlies and quicker balls a total of eight times, from which he picked up three wickets and conceded only eight runs.
Mir bowled his quicker delivery more than the googly as the very slight bump in the positive spin region illustrates. Compare this to Sunil Narine who more or less bowled his variations as often as his off-break delivery – something no doubt Mir will gain the confidence to do in his career.
Every match of the tournament was played on two grounds – Dubai and Sharjah, with the exception of the final which was held in Lahore. This allows us to reliably compare the two grounds to see how different conditions may have affected team strategies.
The table below summaries some statistics for seam bowlers for all matches in both grounds. Seam bowlers enjoyed a lower economy rate in Dubai, although at the cost of a slightly higher average and strike rate.
Similarly for spinners, Dubai offered a lower economy rate by 0.5 runs an over, while their average and strike rate were higher.
We can ask whether these differences came about due to the different pitch conditions in the two grounds. The table below summarises the average off the pitch and in the air movement for seamers and spinners in degrees.
Although Sharjah offered a little more swing for the seamers, they extracted a lot more seam movement in Dubai. Dubai also saw more drift and a lot more spin.
The histogram above shows the distribution of spin at both the grounds. Both grounds are slightly skewed towards negative values of spin (indicating spin away from the right-hander and in to the left-hander). Sharjah has a much higher and narrower peak demonstrating the relative lack of assistance from the pitch for spinners.
Importance of the toss
In every game bar one the winner of the toss chose to bowl first. The table below shows the same attributes from before but separated by first and second innings.
It’s evident that the second innings offered a bit more for every factor but not significantly more – certainly not enough to convince captains to bat first.
As has become a wider trend in T20 cricket, knowing your target is advantageous enough to always bat second regardless of conditions.
The graph above shows the average worm for matches where the team batting second won the game in this year’s PSL. The green line shows that teams generally start off quicker in the Powerplay before slowing down somewhat to keep wickets in hand until the tenth over. After this they overtake the first innings worm to chase down their target in the latter overs.
Imran Khan, @cricketsavant.
A statistical summary of the 2017 Pakistan Super League.
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