Author Archives: bajit

IPL Extraaaaaaaaaaaaaaaaaaaaa.

This is not a post about:

a)   IPL is not cricket

b)   IPL is cricket

c)   IPL has issues such as conflict of interest, spot fixing, sexism etc.

These are some random musings.

I am a sucker for cricket and I’d like to know if there is any other forum to watch Sachin Tendulkar and Rahul Dravid play other than the IPL. And I play the fantasy league. In fact, that is the second most significant reason I follow the IPL. Also as mentioned by @gradwolf on Twitter, these are the only folks who seem to be watching the IPL.

I watch the pregame show on mute (only until they display the playing XIs so I could adjust my fantasy league team) for the fear of Sidhu taking Rahul or Sachin’s name and the foul stench of his breath and sense of humor that would  emanate from the television set and cause nausea and increase in my blood pressure. I wish there were an option to visually mute Samir Kochhar whose skin tone displays a range that covers the entire Loreal skin tone chart, thanks to some heavy make-up. Also, the oil content on his skin could vary from bone dry like Bombay High to unexplored wells in Saudi Arabia. If it’s not make-up then I’d like to nominate him for the most curious biological specimen in terms of control over melanin and sebaceous gland activities.

Coming back to muting Kochhar, I think the mirror image of an L-shaped ad might do the trick since Samir invariably sits on the (TV screen) right hand side of the panel menagerie, feeding morsels of gossip and stoking emotions so the panelists species present in the studio could spit out some words at a frenetic pace and even clap their hands and sing and dance every now and then I don’t understand why one needs to resort to waterboarding as a means of torture when one could show the tape of this show to achieve far more effective results. They have even hired the services of Isa Guha since England is not represented well in the IPL, apart from Owais Shah (who?). Also, screw you, Eoin Morgan is Irish. Besides, Kevin Pietersen (even though not playing) is a South African. So. This move makes IPL a truly global phenomenon, representing all the “significant” cricket playing countries.

And if you thought IPL is appealing only to Homo sapiens, you’re dead wrong. They have specifically hired Danny Morrison to squeal at frequencies above 20,000 Hz in order to communicate with the animal and possibly the avian kingdom. Because I sure as hell can’t understand a damn thing he’s saying and I can guarantee that he sure as hell isn’t speaking below 20Hz where his consternations might escape my attention.

Also, one of these days, I need to ask the Lars Ulrich of the show how demeaning it is to wield his skilled hands upon the denouement of a cerebral gem from Sherry paaji. Every single time. Without fail. And how does he maintain that icy expression on his face? Does he have genuine fiduciary concerns as a result of which he had to sign up for this? What’s really going through his mind? Would rather flip those sticks in air and punch them straight into his ears to save himself the agony of listening to the audio and philosophical cacophony or hit his head hard enough against the drumhead membrane (are they made of cowskin? Alligator skin? Who cares.) to pierce it and seek refuge within its serene interiors. The odor and suffocation in that milieu would still be better than what he’s experiencing outside.

I’m not sure where I’m going with this post. I guess I could have called it “A rant against IPL Extraaa innings and the ill effects of Ekta Kapoor’s F-U to English spelling” but I figured IPL and Ekta Kapoor in the title would repel all but one person on this planet from reading this post. That person would be me since I have the misfortune of proof reading it before hitting the send button.

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For those who don’t dare…to MAKE them dare.

Who’s more ‘clutch’? Tendulkar, Lara or Ponting?

By Ajit Bhaskar (@ajit_bhaskar)

Who is the most clutch among these three legends from our generation?

The Stage

Given the somewhat sensitive title of the post, I tried to think of a lot of emotional, heartfelt introductory content but I failed miserably. But it suffices to say that these three players are the best from our generation, particularly in the ODI format of the game. A couple of folks (Ian Chappell and Nasser Hussain) have opined on who’s the greatest among the three ‘modern greats’. Honestly, it is a tough ask to rate the three for each is excellent in his own ways.

I’m not here to ‘rate’ which one of them is the best among the three. What I’m going to address, is each batsman’s ability to perform in the clutch, which is one of the measures of a player’s greatness. After all, such performances tend to ‘define a player’s legacy’!

I am going to compare (statistically), the performance of these three players under ‘clutch’ situations.

Also, it makes some sense to compare these three players in particular because:

  • They have played in the same era.
  • They are all top order batsmen and have spent a vast majority of their careers batting in 1-4 spots in the batting order.

Ground Rules/Assumptions

  • I’m going to restrict this conversation to ODIs alone.
  • Clutch’ is defined as chasing a target. I will try to make things more granular as I proceed further.
  • Only India, Australia, West Indies, Pakistan, New Zealand, England and South Africa have been considered for this analysis. Sorry Zimbabwe, Bangladesh et al.
  • Only run chases are considered.
  • The pronouns HE and HIS used in generic sentences encompass BOTH male and female human beings. Do not hassle me with ‘sexist’ and other epithets.

A brief note on ‘clutch’

Various images flash across our minds the instant we hear the word clutch. Like Michael Jordan’s buzzer beating “The Shot” against Cleveland (followed by Jordan jumping in the air and then throwing his elbows exactly three times after planting his feet on the ground), Javed Miandad’s last ball six off Chetan Sharma (I hate Nataraj pencils just for that) and so on. As far as ODIs are concerned, a clutch situation typically involves chasing a target. The pressure that is associated with chasing a target, particularly when two good, competitive teams are playing makes for good drama and excellent cricket. The players who shine repeatedly and consistently under such circumstances become legends of the game.

The reason for emphasis on run chase will become clearer during the course of this article.

The Statistics

These are obtained from Cricinfo directly after applying a filter for ‘fielding first’.

Key observations:

  • They’ve been involved in enough run chases to qualify for statistical analysis
  • Lara has scored nearly half his runs chasing targets!
  • The ‘chasing average’ of all three players is pretty close to their career averages. This suggests that the pressure associated with a run chase doesn’t influence their performance significantly. In fact, Lara (on an average), scores 3 more runs during chasing.
  • All players show the Jekyll and Hyde syndrome, i.e. elevated averages when their teams win during a run chase and reduced averages when their teams lose while chasing a target.
  • It’s the extent of this syndrome exhibited by the three players that is quite intriguing.
  • If we define Differential Chasing Average or D = Chasing Average during Wins – Chasing Average during Losses, it represents the degree of discrepancy in individual performance while a team goes on to win or lose. In principle, a ‘legendary’ player is expected to play the same way and produce at a high level regardless of the outcome of the game and the performance of other players on the team. So lower the D value, greater the degree of consistency of a player during run chases.
  • The D values for Tendulkar, Lara and Ponting are 19.53, 40.11 and 39 respectively.
  • Let’s pause and ponder over this for a moment. Taking Lara as example, when WI chases a total successfully, he tends to score FORTY MORE RUNS than when WI fails to chase a target. While an average of ~68 runs is fantastic during successful a run chase, that also indicates a lot of variation in performance. In other words, consistency is lacking. The same is true of Ponting (Differential = 39). However, the key difference between Lara and Ponting is that when their teams lose while chasing a target, Lara still manages to score a decent 27.5 runs, Ponting manages only 19 runs.
  • Tendulkar, on the other hand, shows the least variation (D = 19.53). In fact, the variation is half of Lara’s and Ponting’s. This indicates more consistent performance during run chases.
  • Lara has the best Chasing Average in Wins by a distance. He scores nearly 10 more runs than Ponting and 16 more runs than Tendulkar during successful run chases.
  • Tendulkar has the best Chasing Average in Losses. It’s is about 13 runs or 67% greater than Ponting’s. He also scores 4 more runs than Lara during unsuccessful rn chases.
 Figure 1. Graphical representation of performance of Sachin Tendulkar (SRT, blue), Brian Lara (BL, Red) and Ricky Ponting (RP, green) during run chases.

 

Cranking up the pressure to ‘ultimate clutch’

While the analysis so far has provided an indication of the extent of consistency of these players, it hasn’t truly separated them as to who is the best among the three. So I’ll up the ante a little bit and crank up the pressure.

I’d like to evaluate these players’ performances under extreme pressure.  In many cases, teams are chasing fairly small targets of 100 or 150. While the task is still challenging, it is not as daunting as chasing a larger target. Say 250.

How do these players fare when chasing targets of 250 or above? The reason for choosing 250 becomes clearer when we take a look at how teams fare when they chase such targets.

Data Acquisition

  • Get the ODI inning by inning list for Tendulkar on cricinfo.
  • Set a filter for ‘fielding first’.
  • Open every single match/scorecard and choose only those where targets of 250 or above were chased.
  • Note the runs scored in each inning under two columns based on whether his team won or lost.
  • Calculate various parameters (Average, average during wins and losses etc.)
  • Not outs are considered as outs for calculating averages
  • Repeat the process for Lara and Ponting. Note that in Ponting’s case, a tied match is included for calculating chasing average.

Here’s how the three batsmen fare:

Key observations:

  • There is a LOT of collective failure! Just take a look at the W-L records. With these legends representing India, West Indies and Australia respectively, they have won ~30, 25 and 40% of their matches while chasing 250+ targets. The collective success rate is just 31%!
  • So, if anybody tells you chasing 250+ is an easy task, just show him this table. Even the ‘invincible Aussies’, who have boasted some of the game’s premier batsmen, bowlers and perhaps some the most balanced sides ever, have failed to win even half the games while chasing 250 or above!
  • Tendulkar’s average while chasing 250+ targets (39.9) is virtually same as his regular chasing average of 40.03. This is remarkable consistency. Lara and Ponting on the other hand, tend to score nearly 5 and 3 runs lower than their regular chasing averages respective, when chasing 250+ targets.
  • Tendulkar also averages the most during 250+ chases. While Tendulkar and Lara are separated by one run, Tendulkar scores nearly 3 more runs than Ponting.
  • The differential (D) values for Tendulkar, Lara and Ponting are 10.3, 34.2 and 46.6 respectively.
  • Let me emphasize a bit more on the D values. Regardless of W or L, you can expect consistent performance from Tendulkar. Lara and Ponting, on the other hand, tend to play extremely well when their respective teams are winning, but tend to score poorly when their sides are on the losing side. This is particularly true of Ponting, whose average of 18.5 when the Aussies lose chasing targets 250 (probability is 26 out of 44 games or 59%) or above is quite frankly, poor!
  • WI has lost 39 out of 52 games while chasing 250+. But even under these circumstances, Lara pretty much assures you 30 runs (chasing avg. during losses).
  • Tendulkar, on the other hand, gets you 7 more runs than Lara and nearly 18 more runs than Ponting on days when your team is not doing a good job at chasing. This is a very significant difference in my opinion, given the fact that India and WI do not end up on the winning side often while chasing 250+ targets.
  • But when their teams win, Lara and Ponting fire and fare much better than Tendulkar. This is clear from their chasing averages during wins.

Figure 2. Graphical representation of performance during 250+ run chases for Tendulkar (blue), Lara (red) and Ponting (green).

Bottom Line

The bottom line is, no matter how high the pressure is, whether the game is being played on earth or elsewhere, no matter what kind of target the team is chasing, Tendulkar provides the most steady, consistent performance. Lara is a gambling man’s pick, while Ponting is (compared to Tendulkar and Lara) more of a hit or miss case. If snoring is a problem, you may need ZQuiet.

To me, this analysis puts Tendulkar and Lara a cut above Ponting. Particularly because Ponting has enjoyed the benefit of better overall teams than Lara and Tendulkar have enjoyed over their careers. But more importantly, the averages of 18.95 during unsuccessful run chases and 18.5 during unsuccessful run chases involving 250+ targets is something I wouldn’t call ‘stuff of legends’.

In a nutshell, if I were to pick one of these three legends to help chase my team a target of 250 or above, which in my book, is a clutch situation given the rate of failure involved, I’d flip a coin. Heads – Tendulkar, Tails – Lara.

Sorry Ponting, you just don’t make the cut on my list. Certainly not in ODIs.

Top heavy IPL: A statistical analysis.

The IPL season is in full swing.About 3/4th of the season is over and this might be a good time to assess why certain teams are doing well and why some others aren’t. This piece aims to look at things from a purely batting perspective. The particular focus is on trying to correlate the success that certain franchises have enjoyed to the performance from their top order batsmen.

These are the current rankings:

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Apart from rankings, few other things are also shown. None of these statistics have been taken directly from cricinfo.

IPL is a fairly batsman friendly game. Also, a team gets to face ~120 balls per inning. So, in my opinion, the performance of the top order becomes extremely critical, regardless of whether a team is trying to set a total or chase one. While one bad over might be overcome by a good one following it immediately, a couple of quick wickets, especially among the top order batsmen puts much higher pressure in a T20 game in my opinion. This is the rationale behind assessing batting performances.

I consider the statistics listed above as a reasonable metric for analyzing the performance of top order batsmen.

All the teams have played at least 12 games. PWI is the only team that has played 13. As per current rankings, KKR, DD, MI and RCB round off the top four spots. Let’s try to look into how does their success correlates with the performance of their top order.

For the purposes of this piece, top order will refer to the first three batsmen in the lineup. Middle order will refer to batsmen no. 4 & 5 in the order.

Here’s how the table appears when the teams are sorted based on the % of total runs of the entire team scored by the top order.

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The results show that three out of the top four teams continue to feature in top 4. The only new entry is RR, which wasn’t too far (5th in overall rankings) to begin with. Further, there is not much change in CSK, KXIP and PWI’s positions. This suggests that there is a reasonable correlation between the performance of top order and overall success of the teams. The major outliers to this trend would be MI and DC.

A couple of interesting revelations:

  • MI slips to the last spot. This suggests they do not truly depend on their top order for their success. This in spite of one Sachin Tendulkar, but I shall not dare to ramble along those lines.
  • DD top order accounts for nearly 2/3rd of the total runs scored by the team!.

A few other details are revealed when the teams are sorted out based on the total number of runs scored per inning by the entire team.`

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A few interesting observations right away:

  • Top teams like KKR and DD have now slipped to the bottom of the ladder. In fact, those two teams score nearly 20 runs fewer than RCB, which leads the pack. In a nutshell, while DD and KKR don’t score much (relatively speaking), they do rely on their top orders to set or chase a target quite heavily. This accentuates the value of Gautam Gambhir, Brendon McCullum, Virender Sehwag and Kevin Pietersen.
  • MI continues to sit at the bottom of the pile. So not only does MI score the fewest runs, their top order contributes the least towards their scores. So how a does team that performs so poorly with the bat manage to do well in the overall rankings? I’ll try to address that in more detail now.

The curious case of MI:

How is MI winning games in spite of horrendous scoring compared to the rest of the league? One of the possibilities is a strong middle order. The table below sorts the IPL teams based on the average runs scored by the middle order.

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No points for guessing which team has the BEST middle order in the business. It’s MI.  Here are a few other interesting observations:

  • Mumbai’s middle order contributes nearly TWICE as much to its team’s success when compared to Kolkata. This is further proven when one watches the performances of Rayudu, Pollard and the likes who have bailed Mumbai out many a times. The latest addition to this was the blitzkrieg from Dwayne Smith that flattened CSK.
  • Sorting teams based on average runs scored by the middle coincidentally sorts the teams based on the % runs contributed by no. 4 and no. 5 towards the total score. This further accentuates the contribution of the middle order of MI towards its success, particularly in close games.
  • The fact that KKR lies in the bottom of this list again accentuates how important the top order is for its success. Same rationale applies for RR that has been enjoying the success of Rahane and Dravid, and now Watson. The top order is critical for their success as well.

So I hope that I have been able to throw some light on the importance of the top order’s performance towards the success of a team. While this might be intuitive for some, analyzing statistically, nerding it up with figures and tables makes a lot more fun! Also, this could enable fantasy IPL players to choose certain players from particular teams. Too bad I won’t be getting a medal for this social service.

P.S: 3 matches have taken place since I’ve compiled this data. It would be great to put the above analysis to a litmus test.

Game 1: DD v/s DC

  • For DC, the top order scored 107/187 runs (~57.2%). While this sounds quite impressive for a team that is dead last in standings, this is still an AVERAGE if not slightly below average performance. The middle order scored 78/187 (~41.7%) runs. This is nearly twice their average production, which is probably why DC posted a significantly higher score than their season average.
  • For DD, it’s very simple. The top order won the game for them. They scored all the runs and flattened the opposition. This certainly holds true with the above analysis.

Game 2: RR v/s CSK

  • RR has relied quite a bit on it’s top order. In this game, they were fairly abysmal. They scored 26/126 (20.6%) of the team’s runs, which is barely 1/3rd of their season average! The middle order (Binny and Botha) bailed them out a little with 60 runs (47.6% of the total score). But this is a clear cut deviation from their season’s average trend.
  • CSK on the other hand, didn’t rely on their top order to win this game, which is in line with the above analysis. The top order scored only 42/127 runs (33.1%). This is below their season average of 49.8%. The middle order and the bottom order bailed them out big time and they were able to snatch a close game from RR’s hands.

Game 3: RCB v/s PWI

  • RCB batted first and their top order gave them an excellent start to set a platform for a competitive score. Chris Gayle, Tilakaratne Dilshan and Virat Kohli combined for 68.8% of the team’s runs. This is in line with their season’s trend.
  • PWI continued to showcase the fact that they have one of the worst top orders in the game This doesn’t have to do with poor quality batsmen as much as the number of times they’ve tinkered with their top order. They have changed their top order roughly 9 times in a span of 14 games. That is not the best approach towards a stable, established lineup. The game was practically over when they lost their entire top order for a mere 17 runs. The middle order did well by scoring 69/138 (50%) of the runs but it was clearly too much pressure to bail out such a poor show from the top order. The result was a crushing defeat.

So it appears that the above analysis was valid to a good extent on the games that transpired after compiling the data. As the title suggests, IPL does seem to be top heavy.

– Ajit Bhaskar.

(@ajit_bhaskar on Twitter)