Friday 26 April 2013

What If Lecture on Cricket

Last year, Eric presented a talk on alcohol in the University's What If Wednesday series. This coming Wednesday it will be my turn, talking about economics and cricket. The title is "What if...Economics could help cricket teams win matches?" I have blogged a bit about my work with students on various aspects of cricket in the past (click on the tag "cricket" to see all those posts).

On Wednesday, I am going to focus on how an economics-derived approach to the analysis of cricket can yield interesting analyses of on-field strategy. Specifically, I will be talking about an aspect of the work from Scott Brooker's doctoral thesis that I haven't blogged on previously--how we can estimate batter "production possibility frontiers" showing the tradeoff between risk and return for specific batsmen, and from that to suggest one explanation for why New Zealand has traditionally punched above its weight in ODI cricket.

The announcement and link to register for the lecture are here. I understand that the registration process can be a bit cumbersome as it seems like you are registering for a course, but it is free to attend and registering enables the University to ascertain likely numbers. (And to be honest, I haven't registered for the ones that I have attended.)

I hope to see as many loyal readers of Offsetting there as possible, conditional, of course, on your caring about cricket.


  1. Registration is too much of a pain to be bothered doing. Now having Crampton talk aboot cricket that I would pay good money to see!!!

  2. With Cricket has any research been done on the Follow-On? Even a super-simple one like % of games won where Follow On enforced vs % of games where Follow On wasn't enforced, removing all games where weather had a significant impact. You could add a lot more variables or refinements but I'd find this interesting.
    Statistically was McCallum right not to enfoce the follow-on against England in the last test?

  3. You do not want me talking on cricket. Have you read Mark Twain's brilliant little piece, "How I edited an agricultural paper once"? It's on point.

  4. This is something I would love to look at, but I suspect that it would be too hard to control for variables that are observable at the time but not observable in the data. In world where conditions don't change, it is a no-brainer that you should always enforce the follow-on, as by batting again you don't know how large a score you need before declaring, but by batting last you know you only need to bat till you have won. But there are two reasons that you might prefer to be bowling last that might outweigh that effect. The first is that the pitch could be deteriorating; the second is that your bowlers might be tired after the 2nd innings and so by batting 3rd you can give them time to freshen up.

    How much the pitch actually deteriorated might be observable in the data by the rate of wickets, but it will be confounded by the choice of follow on. A team choosing not to enforce the follow on will then choose to bat aggressively, and, by definition one of the teams has played much better than the other to that point and so the ordering of the innings will affect the appearance of deterioration.

    Bowler tiredness might be easier to measure, but by the time one adjusts for pacemen versus spinners, and then for which are likely to be the most important bowlers in the 3rd and 4th innings, I suspect that there will not be enough games to draw useful inferences.

    But my gut is that McCullum was right to not enforce the follow on against England (to freshen up Southee and Boult) but that he batted for too long.

  5. Exactly my thoughts both on being too hard to draw valid statistical conclusions from data available.
    And agree re last test that follow on shouldn't have been enforced but definitely batted too long.
    Maybe optimal third innings declaration could be worked out. Set required run rates to within ranges and see which range had highest win rate adjusting for losses.

  6. Unfortunately, I will not be able to attend but this is a fascinating area and one that Scott and I have discussed on several occasions. The conscious and sub-conscious analysis of "risk"is a major component of the decision-making process and as such, is essential in analysing both opposition and your own players. We have talked about including a risk assessment around players who, for example, face three dot balls ... a risk-index might allow me to analyse what type of shot a batsman might attempt. Alternatively, having been dispatched to the boundary, how much risk will a specific bowler apply to their next ball. Great stuff!

  7. This is an interesting area, Rupert. I have a question for you. It should be relatively easy to identify when players adjust their behaviour because of what has happened on the last few balls. But how do you assess whether they should have changed their behaviour? On the one hand, you might say that changing your aggression strategy as a bowler, just because a batsman took a risk and got away is a kind of sunk-cost fallacy, but it might be optimal revising of beliefs about the batsman's form on that particular day. Any ideas on how we could tell the difference using historical data?