Enough of Centuries and Fifers, Time to Dig Into Fielding Numbers
How can we find out the real fielding prowess of a particular player? The Quint breaks down a few metrics.
Take a look at these tables. What do the career stats of these two players suggest about their standards in fielding?
Honestly, the number of catches doesn’t really help us distinguish between the fielding skills of the two.
The two players above, however, are of two different leagues. In the 1992 World Cup, in one of the most famous moments of fielding in the history of sport, the former (Player 1) fell prey to the latter (Player 2).
Quite dishearteningly, even though the first table highlights much about the batting heroics of Inzamam-ul-Haq, there’s nothing much to be said about the fielding great, Jonty Rhodes from the second table.
That, in a nutshell, outlines the state of fielding statistics and analytics available in cricket.
In runs scored or conceded, balls faced or delivered, wins and losses and in many more, cricket is a game of numbers. All these, however, revolve around batting and bowling. Digging deeper would not unearth much about their fielding prowess.
Let’s look at cricket’s most important fielding-related metrics, and why and how they should be measured barring certain challenges.
Unfortunately, even with the advent of sophisticated technology, modern-day cricket still does not have much to offer when it comes to calculating the amount of runs saved by a particular player.
There’s no statistics to compare if a Saha is more efficient at saving byes than a Dhoni per Test match. With many such statistics missing, cricket is often ill-equipped to represent the right picture.
Challenges: Capturing the number of runs saved by each player data accurately may require high precision online time and motion study by high-class technology. Not impossible though.
Intel’s Augmented Reality and Virtual Reality brought some quality insights in the Champions Trophy this year, mostly for batting and bowling. For fielding, SportVU camera and spatio-temporal pattern-recognition software can generate great insights.
Catches Taken/Dropped Ratio
While the data on ‘Catches taken’ is available, ‘catches dropped’ is not. So it is ridiculous to say things like Inzamam grabbed more catches than Jonty, or for that matter, that Ricky Ponting stands at a hapless 26th position by catches/innings index in the ODIs.
A long-time slip catcher in Test matches would inevitably have more numbers, than say a deep midwicket fielder (where chances are handful). If tracked, the metric would throw up the most efficient catcher, players with the best conversions, and fielding position wise specialists.
However, the truth is camouflaged under a lack of data and a measurement system. Facts such as, in Tests, Virat Kohli has a 3 to 2 catch taken to dropped ratio and India’s overall poor catching efficiency against pace over spin are absent from records.
Challenges: The only challenge here is to consider the ‘drop’ by the difficulty level of the catches. There is, however, a solution. Cricket Australia’s Team Performance department has developed a comprehensive database dubbed as 'Fielding Average', where it differentiates easy to difficult chances with a gradation system. Grade 1 refers to an average difficulty, with the grades going higher the more difficult chances.
Run Outs Effected
A run out effected by a piece of fielding brilliance is basically supposed to be the fielder’s wicket. Unfortunately, cricket does not approve of that.
Because of this, people cannot ask what Jonty’s scalp in run-outs is, or if Aussies are more effective at runouts than others. A run-out is, at the end, of the day a dismissal. Not officially accounting the number of run-outs per player or capturing stats creates a blind spot in the game.
Challenges: Run-outs effected should be a rather straightforward piece of record-keeping. There might be some ambiguity to credit the most deserving fielder in cases where multiple fielders are involved.
But, a process and a set of rules can solve that ambiguity. Whichever fielder was more influential to effect a run-out, should be awarded the wicket.
Fielding position-wise, performance and data are the most neglected but crucial aspects of the game. Different positions require different skillsets and attributes. While fielding at the slip cordon requires soft hands and focus, fielding inside the 30-yard circle requires agility and second-guessing abilities.
Today, because of the lack of data, watchers of the game cannot read much from India’s unsettled slip cordon or Kohli’s inconsistency across positions.
Challenges: A relatively easy metric to capture, the challenge lies only in the fact that cricket has close to 40 fielding positions vis-à-vis 11 batting positions. Record keeping might get a little cumbersome.
Besides these Level-1 metrics, cricket can have many Level-2, 3 metrics – such as the direct hit percentage, fielder’s speed and ground coverage, throw speed and so on.
With the advent of modern technologies, analytics and skilled experts, the game can fare much better if proper fielding stats and insights are put in right perspectives. A good running catch resulting in a wicket from an ordinary delivery is as much the fielder’s wicket as it’s the bowler’s.
A juggling effort to save a boundary is as effective as hitting a cracking boundary. Therefore, in order to celebrate fielding efforts in equal dealings with that of batting and bowling heroics, or to pave way for selection on the basis of fitness and fielding, cricket, we need a better monitoring and tracking system.
(Debnath Roychowdhury is an alumnus of SP Jain Institute of Management and Research (SPJIMR), Mumbai. He works as a management consultant. He can be reached on @ImDebnath.)
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