# Was the India-Bangladesh World T20 match really interesting?

*8 min read*

*.*Updated: 22 Apr 2016, 04:05 AM IST

The short answer to the question is yes, and we built a math model to prove it

The short answer to the question is yes, and we built a math model to prove it

Was the India-Bangladesh match in the recent ICC World T20 as exciting as everyone says it was?

Is there any way to objectively measure this excitement or interest? The scorecard won’t help because that only gives a snapshot of the game.

And is this measure even important?

Third answer first: there are many reasons why objective determination of whether a game was interesting helps. Firstly, it helps tournament and series organizers choose teams and schedules better. Secondly, it helps broadcasters and advertisers make more optimal decisions. Thirdly, it helps fans looking to watch highlights packages make better choices. And finally, with cricket being an evolving game, it helps administrators of the game make better decisions on how to change the rules in order to make the game more interesting.

Second answer next—and it is a long one.

How to measure excitement/interest?

The margin of victory says nothing because well-fought and interesting cricket matches need not result in close finishes. The game between India and Australia in the recently concluded World T20 was widely regarded by spectators and commentators as being exciting. India won the game with six wickets and five balls to spare, a large margin by 20-over cricket standards.

It is thus clear that we need to go beyond the scorecard. To figure out an objective formula to determine the “interestingness", let us start by looking at a few games from the recently concluded ICC World T20. Instead of the scorecard, we will look at how the advantage in each game changed hands between the participating teams.

The simplest way to measure the likelihood of each team winning the game at a particular point in time is by looking at the “betting odds". With sports betting being illegal in India, this information is not available to us. Hence we need an alternative method to determine the likelihood of each team winning a game based on the current game situation.

Using WASP

In 2012, Sky Sports in New Zealand debuted a feature known as the “Winning and Scoring Predictor" (WASP) built by two economists from the University of Canterbury in New Zealand, Scott Brooker and Seamus Hogan. During the first innings of each limited overs game, WASP would predict what the team batting first would score. During the chase, WASP would indicate the probability that the chase would be successful (these numbers were displayed along with the scores at the bottom of the broadcast screen).

The algorithm, a basic version of which has been put in the public domain by Hogan in a blogpost relies on a technique called “dynamic programming" and calculates the odds based on the score by assuming that an “average batting team" is playing an “average bowling team". Using this algorithm, and making a couple of modifications, we can compute the likelihood of each team winning at any point of time in the game based on the score alone.

The changing probabilities of winning

Nevertheless, it is a perfectly serviceable formula.

Let’s use it to answer the first question.