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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

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