The game and the million dollar question
As much as Cricket is a game of the minds, it’s a game of numbers (read: stats), also permutations and combinations. It’s not all that hard to imagine how, when one gets to know the myriad pitch, weather, playing and match conditions. It might not come as a surprise that it can rival the possible moves in a game of chess.
As the game of cricket has developed over the last five centuries, more and more detailed statistics have become available. These are important indicators and can be used to predict a game’s outcome, or at least give a possible indication of an expected result. In fact, the New Zealand coach, Mike Hesson, quite eloquently answered is T20 the format where data is most effective at yielding that advantage, while addressing in general, the use of data in the modern game. But even in T20I Cricket, there are an endless number of questions that are not amenable to experimentation or direct analysis but could be easily addressed via simulation. For example, on average, would India benefit more from increasing their Strike Rate of their middle order or consistency of the top-order. If they do, what percentage of time would India be expected to win over Australia while setting, in Sharjah?
While Hesson’s interview sets up the premise for the analysis, its predicated by the more recent article by Karthikeya Date, on Why hitting is more optimal than batting in T20. While the results of the Date’s analysis reveal the importance of power hitting, this analysis aims to investigate the impact of power hitting, contrasted with improving consistency, their effects on the outcomes of a n-match bilateral series between 2 teams of choice by the use of a Bayesian framework to predict the outcome of the series.
This analysis currently investigates the outcomes of games from a batsman point of view. This restricts the variables being considered for analysis to be strictly batsman centric. But the problem statement remains clear: Which among the two competing strategies (power-hitting Vs Consistency) leads to greater chance of win a T20I game?
We try to answer the winning strategy question by simulating a 7 match series featuring India and the West Indies. A Bayesian stochastic framework is used to simulate the performance of the players. The most important assumption is that the score, in itself, is the sole and just reflection of all the factors relevant to describing the contest and its outcome. For the rest of the assumptions, refer to the link at the bottom of the page.
Prior, Likelihood and Posterior
With no “extra” information, we assume (prior) that each team is as like to win (or lose) the series as the other, i.e. a 50-50 chance to both the teams, as shown below.
It may be observed that the average runs scored in each of the series is “in general” reflective of actual T20I series between the 2 sides.
Back to Bayesian, we then calculate the likelihood of victories in the 7 match series, the posterior, using the prior and likelihood.
It may be observed that the that the posterior of India winning the series has gone up to 56%, meaning that India is likely to win the series 56 out of 100 times. Usually in the T20I, the West Indies are amongst the most powerful teams, but we see that India are just ahead of them. This might well be due to the fact that 2 key players of the Windies team (Sinal Narain and Keiron Pollard) aren’t part of the playing XI. (Remember the playing XI from World T20I semi-finals Ind Vs WI?).
Strategy: Power Hitting Vs Consistency
We carry out similar analysis for 2 what-if scenarios.
- Improving the power hitting by 10 % (Strike Rate up by 10%)
- Improving the consistency by ~10% (Standard Deviation down by 10%)
We may visualize the effects as follows.
Run scoring and win distribution: We clearly see that when the strike rate increases, the runs scored by India goes up (moves to the right), leading to higher win %. The effect of consistence is observable, but less potent than strike rate increase.
Prior, Likelihood and Posterior: We see higher likelihood of win when the strike rate increases, as compared to the increase in consistency.
We carry out the simulation for various combinations of Strike Rate and Consistency improvements. The results are shown below. We see a distinct increase in win % with increasing strike rate.
This settles the discussion: Hitting trumps Consistency in T20I. Atleast for India against West Indies, with the same playing XI of their last world T20I matches respectively.
Click here in-depth description of this study.