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Measuring boundary attempts in the IPL

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 typeboundary %
Slog-sweep40
Upper Cut34
Scoop34
Switch Hit31
Pull29
Slog27
Hook27
Reverse Sweep26
Drive23
Sweep22
Late Cut18
Flick18
Cut17
Glance14
Steer8
Fended5
Worked2
Pushed1
Dropped1
Backward Defensive1
No Shot1
Forward Defensive1

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 connectionboundary %
Middled83
Strong60
Well Timed40
Outside Edge27
Top Edge25
Thick Edge24
Gloved13
Inside Edge10
False Shot10
Bottom Edge8
Leading Edge3
Mis-timed3
Neutral2
None2
Padded1
Bat-Pad1
Hit Helmet1
No Shot0
Missed (Leg Side)0
Hit Body0
Hit Pad0
Missed0
Left0
Play and Miss0
Shoulders Arms0
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 nameboundary attemptsintentional boundariesboundary success %balls facedballs per boundary attempt
Manan Vohra3625691243.44
Sunil Narine382668822.16
Ajinkya Rahane3624671704.72
David Warner6945652543.68
Shaun Marsh412663952.32
Sanju Samson5333621963.70
Jos Buttler5031621563.12
Moises Henriques3622611444.00
Hashim Amla6640612103.18
Sam Billings2716591053.89
Chris Gayle3420591303.82
Hardik Pandya291759792.72
Robin Uthappa7745582002.60
Kedar Jadhav5029581342.68
Kane Williamson331958932.82
Gautam Gambhir8247572873.50
Yuvraj Singh301757732.43
Kieron Pollard4123561583.85
Nitish Rana5128552084.08
Manoj Tiwary351954862.46
Brendon McCullum7238531882.61
Glenn Maxwell5730531111.95
Steven Smith5931532093.54
Suresh Raina7438512212.99
Jason Roy201050412.05
Krunal Pandya261350803.08
Rahul Tripathi5728491442.53
Chris Morris381847852.24
Parthiv Patel5124471402.75
Shreyas Iyer3215471083.38
Chris Lynn321547742.31
AB de Villiers3717461173.16
Aaron Finch6228451121.81
Rohit Sharma291345973.34
Manish Pandey5826451943.34
Ishan Kishan251144532.12
Virat Kohli4118441333.24
Dwayne Smith321444732.28
Rishabh Pant371643952.57
Yusuf Pathan281243812.89
MS Dhoni3816421303.42
Shikhar Dhawan9037412502.78
Mandeep Singh22941823.73
Axar Patel2711411063.93
Dinesh Karthik4819401443.00
Ben Stokes301137963.20
Karun Nair25936903.60

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

The top 10 T20 death bowlers: IPL 2017

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

PlayerTeamRunsBallsMatchesWicketsEconTypeYear
Shane WatsonRoyal Challengers Bangalore17411016129.49pace2016
Joe LeachWorcestershire15410512108.80pace2016
Mitchell McClenaghanMumbai Indians1301011497.72pace2016
Harry GurneyNottinghamshire124921198.09pace2016
Graham NapierEssex129851299.11pace2016
Jamie OvertonSomerset78721096.50pace2016
Mustafizur RahmanSunrisers Hyderabad1821521687.18pace2016
Matthew TaylorGloucestershire1291041287.44pace2016
Chris MorrisDelhi Daredevils64681275.65pace2016
Graham WaggGlamorgan (Wales)100661279.09NULL2016
Rumman RaeesIslamabad United4652775.31pace2017
Dwayne BravoGujarat Lions1951211579.67pace2016
Benny HowellGloucestershire85611478.36pace2016
Sunil NarineMelbourne Renegades8860678.80spin2017
Tymal MillsSussex89701167.63pace2016
Lasith MalingaSri Lanka6543469.07pace2017
James FullerMiddlesex86731167.07pace2016
Mitchell ClaydonKent145981168.88pace2016
Matt QuinnEssex126871468.69pace2016
George EdwardsLancashire87551069.49pace2016
Wahab RiazPeshawar Zalmi6372965.25pace2017
Chris JordanSussex6167965.46pace2016
Mohit SharmaKings XI Punjab143931469.23pace2016
Andrew TyeGloucestershire128801369.60pace2016
Umesh YadavKolkata Knight Riders8252969.46pace2016
Chris RushworthDurham100661269.09pace2016
Ben LaughlinAdelaide Strikers3736566.17pace2017
Paul CoughlinDurham61531166.91pace2016
David GriffithsKent139941368.87pace2016
Jade DernbachSurrey (England)6967656.18pace2016
Ashok DindaRising Pune Supergiants7752958.88pace2016
Rory KleinveldtNorthamptonshire96711058.11pace2016
Mohammed ShamiDelhi Daredevils6246858.09pace2016
Yuzvendra ChahalRoyal Challengers Bangalore69431349.63spin2016
Anwar AliQuetta Gladiators8256948.79pace2017
Sandeep SharmaKings XI Punjab100661449.09pace2016
Jasprit BumrahMumbai Indians136991448.24pace2016
Andrew CarterDerbyshire8455849.16pace2016
Michael HoganGlamorgan (Wales)45481345.63pace2016
Kesrick WilliamsWest Indies4336447.17pace2017
Ben DwarshuisSydney Sixers6043448.37pace2016
Tymal MillsQuetta Gladiators3240544.80pace2017
Usman ArshadDurham137921448.93pace2016
David WilleyYorkshire5244847.09pace2016
Bhuvneshwar KumarSunrisers Hyderabad1661111748.97pace2016
Mark SteketeeBrisbane Heat4242646.00pace2017
Ravi AshwinRising Pune Supergiants64601446.40spin2016
Ben HilfenhausMelbourne Stars6052836.92pace2017
Keaton JenningsDurham64431538.93pace2016
Jasprit BumrahIndia4143535.72pace2016
Murugan AshwinRising Pune Supergiants74521038.54spin2016
Shane WatsonSydney Thunder3937536.32pace2017
Zaheer KhanDelhi Daredevils110671239.85pace2016
Lewis GregorySomerset67641136.28pace2016
Sunil NarineLahore Qalandars5537838.92spin2017
Tom CurranSurrey (England)83661337.55pace2016
Imran TahirNottinghamshire6644639.00spin2016
Wahab RiazPakistan60364310.00pace2017
Oliver Hannon-DalbyWarwickshire120801339.00pace2016
Chris JordanRoyal Challengers Bangalore7246939.39pace2016
Dhawal KulkarniGujarat Lions88611438.66pace2016
Tymal MillsEngland4538337.11pace2017
Hasan AliPeshawar Zalmi86641038.06pace2017
Jake BallNottinghamshire83571038.74pace2016
Mohammad SamiIslamabad United7057937.37pace2017
Barinder SranSunrisers Hyderabad60471437.66pace2016
Tim BresnanYorkshire93641438.72pace2016
Sohail KhanKarachi Kings7546929.78pace2017
Mohammad NawazQuetta Gladiators76491029.31spin2017
Shiv ThakorDerbyshire69531127.81pace2016
Nuwan KulasekaraSri Lanka4237726.81pace2017
Clinton McKayLeicestershire50561225.36pace2016
Piyush ChawlaKolkata Knight Riders47381127.42spin2016
Jordan ClarkLancashire74491029.06pace2016
Tino BestHampshire5537928.92pace2016
Dwayne BravoSurrey (England)5641628.20pace2016
Andrew TyePerth Scorchers5939729.08pace2017
Richard GleesonNorthamptonshire61531026.91pace2016
Sunil NarineKolkata Knight Riders63471128.04spin2016
Tim SoutheeMumbai Indians57361129.50pace2016
Johan BothaSydney Sixers4636627.67spin2017
Matt HenryWorcestershire65461018.48pace2016
Ravi BoparaEssex99741518.03pace2016
Mohammad AamerKarachi Kings75511018.82pace2017
Jeetan PatelWarwickshire49361218.17spin2016
AzharullahNorthamptonshire72571207.58pace2016
Wahab RiazEssex5036508.33pace2016

 

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.

Say Elo to the IPL

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.

Biggest upsets

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.

Biggest contests

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

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.