The just concluded weekend was full of cricket. It makes sense to start the week by posting something on cricket.
This is a wonderful article by Amit Varma. He moved from being a cricket writer to a poker player (wow, though wonder how I managed). Now he is trying to link cricket decisions on the field using lenses from game of Poker:
Once upon a time, I used to be a cricket writer, and I’ve lost count of the series I covered for cricinfo.com (as it was then). Then I moved to other things, which included playing poker professionally for a few years. The most important lesson I learned from poker changed the way I looked at the world – and at cricket. I learnt to think probabilistically.
Let me give you an example of probabilistic thinking with the simplest illustration: a coin toss. An evenly weighted coin will fall heads 50% of the time and tails the other 50%. Let’s say I come to you with a fair coin, and tell you that we will flip the coin once. I will give you 51 paise if it’s heads and you will give me 49 paise if it’s tails.
Here’s how a poker player thinks in your position. First, he calculates the Expected Value (EV) of the spin. If you were to flip the coin 100 times, you’d expect to win 51 paise 50 times and lose 49 paise 50 times, for a total profit of 100 paise. Divide that by 100 and you get the EV of one throw: one paisa. So the proposition is what a poker player would call Plus-EV (or +EV, as I’ll write from now).
The value of your decision is one paisa. But the individual outcome is entirely different – and entirely misleading if you view it in a vacuum. If the coin lands tails – as it will half the time – that will not mean that your decision to call heads was a bad one.
We can extend this thought experiment. I could ask you to pay me 98 paise in return for tossing the coin under these terms 100 times. As the EV of 100 throws is 100 paise, the proposition itself is worth 2 paise to you. Similarly, I could ask you for 150 paise for 100 throws, and if you’re not thinking clearly in terms of EV, you might imagine the EV of each throw to be 2 paise instead of 1 (that’s our first instinct, since 51 minus 49 = 2), and accept, thinking you’re +EV by 50 paise when you’re actually -EV by that much. Note, though, that the outcome will seldom match the profitability of the decision. You might get 80 heads or 80 tails, as can happen. But in the long run, after millions of coin tosses, you will break the bank.
Poker is basically just this. Every decision carries an EV, and good players learn to calculate it to the best of their ability, and to make the most +EV decision at any given point. If they keep doing this over a period of time, they end up profitable. But the thing to remember is that you are making short-term decisions with only long-term outcomes in mind. What happens in any one hand says nothing about the quality of your decision.
This focus on the long run is best expressed in a cliché every poker player is familiar with: don’t be results-oriented (this refers to short-term results, of course). You may flip a coin ten times and see it land tails eight times. That doesn’t mean your decision to bet on heads was wrong. Now this might make it seem that poker is all about luck, and luck does indeed play a huge role, especially in the short term over a single hand or session. The skill in poker lies in understanding and manipulating the luck, and this skill manifests only in the long run. That is why poker players look to play as many hands as possible, to compress the long run as much as they can, “put in volume”. If you flip that coin millions of times, the results will converge towards the expected value, and your accumulated 51 paises will make you filthy rich.
This is the law of large numbers. Keep flipping and eventually the probabilities will converge towards towards expected value. What is really a basic insight somehow becomes so confused in a statistics class.
All cricket decisions are nothing but playing poker on your opponent. It works sometime and does not work the other:
All decision-making in cricket (as in anything else) has probabilities attached to it, with multiple possibilities, but is judged on binary outcomes. When a batsman in a tense situation skies a ball towards midwicket, it could, among other things, a) go for six, or b) be caught on the boundary, or c) kill a bird and fall on a fielder’s head, killing him as well. Only the last of these would be ascribed to luck. If the ball is a six, the batsman will be praised for his “bold aggression”, for “taking the attack to the bowler” and so on. If he is caught, he will be cursed for playing “an irresponsible shot” and “letting his team down”. But in both these cases, the exact same decision would have led to two very different outcomes.
To be honest, such thinking is mainly prevalent among fans and media, including some expert commentators who should know better. Cricketers themselves don’t fall into these traps, partly because one of the reasons they have got to the top in the first place is by focusing on processes. These days coaches and captains think probabilistically, and calculate the EV of different options, even if they may not use these specific terms.
ricketers have thought probabilistically, in a common-sense kind of way, long before this age of data came upon us. You don’t need data to tell you, for example, that smoking is -EV and exercising regularly and getting enough sleep are +EV – even if there appear to be examples to the contrary. Equally, you learn from experience and osmosis what to do in specific situations within matches. And yet, I expect data to affect the way players and coaches think about the game, with more clarity in their decision-making. Like every other sport, cricket will become a numbers game.
One example of a strategic shift hastened by probabilistic thinking is aggression within the game. As I wrote in an earlier essay, I believe that the EV of aggressive batting is being vastly underestimated in T20 cricket. Given that teams have the same number of batsmen and bowlers available to them as in an ODI, but 40% of the overs, it stands to reason that they should be far more aggressive while batting. Indeed, they can dispense with the ODI structure of building an innings and just attack from ball one, instead of waiting for artificially designated “slog overs”. Some teams – West Indies internationally and Gujarat Lions – have figured this out, and “front-load” their innings. Many others, though, continue to underestimate par scores. Expect strike rates to go up massively in the next few years. The movement upwards that took decades in ODIs will take years in T20s.
The Cricket Monthly published an excellent story by Kartikeya Date on the ongoing data revolution in cricket. But it is not data analytics per se that concerns me. Supply and demand will take care of that. It is, rather, the way we, ordinary fans, watch cricket.
We are too focused on outcomes, as is evident when people stone cricketers’ houses or burn effigies of them after a bad loss, or when TV channels look for a Match Ka Mujrim, (“culprit of the match”) as if causation is so easy, or necessary, to establish. My worry stems not from this being an injustice to the players but from it being such a waste. Cricket is a deep, complex, layered and beautiful game, and most of us watch it in a terribly shallow way, focused on the binaries of outcome. Watching a cricket match like this is like going to Wikipedia and reading a plot summary of a great novel. That misses the drama entirely: all 100% of it.
Match ka mujrim! Lol…
Keeping the joke aside, all such news coverage is just sensationalism and is just meant for attracting sound bytes (bites actually). Bit with our media turning increasingly mediocre, what else can one expect?
Nice bit. He says Lord Krishna would have made a great poker player as well (not just because he would know all the cards). There is little doubt on this. These mind games have been there for ages in outsmarting the opponent. Most wars were more mental games than pure physical ones..