Seamus Hogan

Is 400 the new 300 in ODIs? - The Dismal Science

Jun 22, 2015

The current ODI series between England and NZ has been quite extraordinary. England has scored more than 300 in every game, but has lost twice. Yesterday morning, New Zealand’s total of 349 was not only chased down by England, it was chased down with ease, with England losing only three wickets and having 6 overs to spare. 

My sense from my Twitter feed is that the conventional wisdom is as follows:
  1. The rule changes dating from October 2012 (that saw two new balls in each innings and a reduction in the number of fielders allowed outside the circle in non-powerplays) allowed for larger scores, as the outfield gaps and still-hard balls allow batsmen to score at will in the final overs.
  2. These rule changes coincided with new batting skills honed in 20-20 competitions like the IPL.
  3.  New Zealand has been leading the way in showcasing an aggressive approach to cricket; England  prior to now has continued to play with an outdated conservative style, but has now belatedly accepted the new approach, in which “400 is the new 300”.
There is probably much right with this version of events, but I’m not fully convinced. Here are some raw numbers. Since the October 2012 rule changes prior to the current series between England and New Zealand, there were 177 ODI games played involving two teams from the top 8 (defined as the test-playing nations excluding Zimbabwe and Bangladesh), excluding games with a Duckworth-Lewis-Stern reduction in overs. Of those, 56 (or 31%) saw the team batting first score 300 or more. This is certainly a higher rate than we would have seen in past eras, but not as high as conventional wisdom seems to be suggesting. Moreover, getting to 300 still made the team batting first the overwhelming favourite. Of those 56 games with a first-innings score in excess of 300, the team batting first won 48 (86%). More pertinently, of the 18 games where the first innings score only just got to 300 (defined as a score between 300 and 310), the team batting first won 14, which is still a %77 success rate. If 400 is the new 300, it really should be easier to chase down 300 than these data suggest.

I wrote last year about how, once you adjust for mismatches between teams and where the game has been played, there wasn’t much evidence in the data for a general trend towards increasing first-innings scores. Taking all games from the start of the English 2002 season through to the end of the World Cup, controlling for team ability, home-field advantage, and the ground being used, first innings scores since Oct 2012 are only 12 runs higher on average than in the 10 years before Oct 2012. (For data geeks, I describe the exact model at the bottom.)


The following graph illustrates the lack of a trend. The small red dots are the difference between the first-innings score and a prediction based on the team batting, the team bowling, which team (if any) was playing at home, the ground at which the game was played, and allowing for a 12-run premium for the current rules. The solid red dots are a 25-game smoothed moving average, to take out some of the random variation and make any trends clearer. Although there appears to be a bit of an upward trend over the period since October 2012, scores by the end of this period were still only 28 runs higher than in the 2002-2012 period, suggesting that 328 is the new 300!



But now look at the four blue dots. These are the out-of-sample prediction errors for the first four ODIs between England and NZ in the current series. These predictions take into account England’s and New Zealand’s recent (since Oct 2012) batting and bowling form, England’s home-field advantage, and how high scores typically are at those four grounds. The prediction, actual score, and prediction error are as follows:



Ground

Predicted Score

Actual Score

Prediction Error

Edgbaston

235

408

173

The Oval

256

398

142

The Rose Bowl

269

302

33

Trent Bridge

232

349

117

Chester-le-Street

225 (Eng) 228 (NZ)

?

?


The point here is that rather than there having been a world-wide trend in the past few years that England have only now come to grips with; the current series has been extraordinary in every respect even in comparison to recent history. So what is going on? I can think of four hypotheses:
  1. I have made a massive coding error in my database.
  2. There has been a structural break in conditions: The four English groundsmen have produced very different pitches than in the past, ones much more favourable to high scores.
  3. There has been a structural break in team quality: Both NZ and England have better batting and/or worse bowling in this series than they had in the recent past.
  4. These four games have been black-swan events; and things will return to normal soon.
  5. There has been a strategic mindset shift in both New Zealand and England.

When things look extraordinary, coding errors are always a good bet, and I wouldn’t rule this out, but the raw predictions don’t look too far out from my own intuition, so I  don’t think this is the problem here.


I can’t comment on whether conditions were very different from usual in the four games so far, but I haven’t seen any commentary from England suggesting that the groundsmen have been producing untypical pitches, so I suspect hypothesis 2 is not the right one.


There is probably some truth to hypothesis 3. I don’t think the batting is too much different, but the bowling is quite possibly weaker. New Zealand have lost Vettori, Anderson and Milne from their World Cup bowling line-up, and have had Southee and Boult together for only one of the four matches. England have rested Anderson and Broad. Even so, I would put my money on the final two hypotheses explaining most of the data. 


The idea that teams are not aggressive enough when batting is something Scott Brooker and I have been saying for a long time. Back when he was writing his thesis, Scott experimented with what an average team would be able to achieve if they applied the optimal level of aggression. Based on the strike rates and dismissal rates that we can observe batsmen having in different game situations (e.g. conservative batting in the middle overs versus aggression in the death overs), he constructed a set of frontiers describing the trade-off between risk and return for typical batsmen in positions #1-#11, and then simulated optimal behaviour. He found that scores could be roughly 30 runs higher if batting teams were more aggressive, but that there would be more variance in scores and a higher probability of not batting out the overs. This was based on data from before 2007. It is likely that under the new rules, the value of extra aggression is even higher. 

What I think we are seeing in the current series is two teams who keep pushing the boundaries of this approach, forcing the other team to react in kind, and so all kinds of previously unrealised potential that has existed for a while is now being revealed. Contrary to the conventional wisdom, I don’t think this has been New Zealand’s approach before now. Rather, I think they have emphasised retaining wickets during the middle overs in preparation for an all-out assault in the final 10. New Zealand’s famous aggression in the World Cup was mostly seen in its approach to bowling, putting an emphasis on wicket taking rather than containment.


If I am right, that there has been a mind-set change for both teams in the current series, I am mindful that Scott’s conclusion was that the additional 30 runs on average would come alongside a big increase in variance. This brings me back to the black-swan hypothesis. We have seen scores more than 100 runs in excess of what recent form would have predicted on average. It is likely that in each game, there was a degree of luck. Batsmen got away with taking risks on these occasions, but we could just as easily have seen scores that were quite low. Even allowing for the fact that dropped catches are more likely when batsmen are hitting the ball hard, the catching in the current series does seem to have been below par. Realistically, 370 might be the new 300, but equally 180 the new 200.


Method:


My prediction model was based on a database of all non-rain-affected ODIs involving the top-8 countries since May 2002, using only games played on grounds where there were at least 10 matches played (but also including Chester le Street, as that is the venue for the final ODI between England and NZ).


The model was an OLS regression of first innings score on a dummy variables for the batting-team country, dummy variables for the bowling-team country, a dummy variable for each of the 53 grounds, a dummy variable for when the batting team was playing at home, and for when the bowling team was playing at home. Finally, I added a dummy variable for matches played since Oct 2012, and more dummy variables for this recent-era interacted with the batting and bowling team dummies. 

These interaction teams mean that only post-Oct-2012 data is used to determine the effect of team ability on scores; the only reason for pooling the data with the pre-Oct-2012 era is to provide enough data to estimate ground effects. Essentially, the model is assuming that the relative impact on scores of being at a particular ground and the relative impact of home-field advantage has not changed from before the Oct 2012 to after.



In the 25-game  moving average shown in the chart above, the data is broken around the structural break of Oct 2012, so that the smoothed line before the break is not influenced by games played after the break and vice versa. 

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So what *is* the most misleading term in Economics? - The Dismal Science

Jun 18, 2015

On Monday, I wrotedisagreeing with John Quiggan’s piece on “Pareto optimality” being the most misleading term in economics. My disagreement was more with his argument than his conclusion, but nevertheless, it got me thinking about what is the most misleading term in Economics. I have four favourites, which I will list in reverses order. These are all misleading in some way, but to different audiences.


4. Efficiency.


As I said, I don’t entirely disagree with John’s conclusion. I believe that when economists use the term efficiency without an adjective, it (nearly) always refers to Pareto efficiency, which properly understood is a fairly innocuous concept. It simply refers to a situation where no-one can be made better off in terms of the things he or she values (more stuff, cleaner environment, better civic amenities, living in a civil society, whatever) without making anyone else worse off in terms of the the things they value.  But I always advise my students to never use the word efficiency when talking with non-economists. Exhibit A to explain why is the following quote from the 1962 verison of mutiny on the bounty. Captain Bligh (Trevor Howard) is explaining to Fletcher Christian (Marlon Brando) why he just had a sailor flogged for something he didn’t do, saying that it won’t be possible to run the ship in bad weather if sailors don’t fear their captain more than they fear the weather. He goes on to say: 

Now don’t mistake me. I’m not advising cruelty or brutality with no purpose. My point is that cruelty with purpose is not cruelty—it’s efficiency
This scene, which happens early in the movie, is important for setting up Bligh as a horrible person in the minds of the movie watchers (much like Joffrey’s encounter with the diawolf and the butcher’s boy in the second episode of Game of Thrones). The screenwriters knew that having Bligh use the word efficiency to describe the treatment of people would be chilling to viewers. It invokes notions of Dickensian eight-year-olds up chimney, of sacrificing human values to the end of maximising material production, the total opposite of the totally human-values-centric approach to welfare that Pareto efficiency invokes.


3. Aggregate Demand


Efficiency is a problematic term as it can mislead those outside the subject. Aggregate Demand is worse as it misleads our own students. I complained about this one here. A standard demand curve is a statement of intentions. It shows how much buyers would buy if they could buy as much as they wanted at a given price. At the equilibrium price, the desired demand will equal actual purchases. It is also possible, however, to be on the demand curve at points where desired demand and actual purchases are different (say as the result of a legislated maximum price). The so-called aggregate demand curve is not analogous. It shows different equilibrium combinations of price and quantity such that demand for output equals actual output. It is possible to be out of this equilibrium, through undesired changed in inventories or other quantity buffers, but that implies being completely off the curve. The aggregate demand curve is a useful graphical device for teaching some basic macro concepts, but its name pretty much guarantees that the majority of first-year students will misunderstand its properties.


2. Investment


Here we have a term that, I think, misleads even seasoned economists. Investment in economics, refers to the accumulation of capital goods. The term in general usage is often used to mean particular mechanisms that consumers use to save. So, for instance, buying a rental property is investment in this everyday use, but, if it is an existing house, it is not “investment” in the economics sense. I am convinced that slippage in the meaning of the word investment mid-sentence is the reason for some half-baked justifications for a capital gains tax, as in statements like “we need a capital gains tax so that people will switch from investing in houses to more productive investments”. As I noted here, buying an existing house is not “unproductive investment”; it isn’t investment at all. Once that is noted, the link between a capital gains tax and productive use of savings becomes extremely tenuous.


But these three misleading terms are trivial compared to the granddaddy of them all:


1. NAIRU


That is, the "non-accelerating-inflation rate of unemployment". This is just embarrassing. As a profession, we like to get smug and despondent about innumeracy in the press with respect to the number of derivatives, sighing every time we read statements “inflation rose by 3% in the year to March”, when what is meant is either that “prices rose by 3%” or “inflation was 3%”. But then we do the same thing ourselves with one of our technical terms. 

For goodness sake, it should be the non-accelerating-prices rate of unemployment (NAPRU) or the non-increasing-inflation rate of unemployment (NIIPRU). There is an alternative term—the natural rate of unemployment. If it weren’t for the existence of NAIRU, I would have the natural rate in my list of misleading terms. It conveys a notion of unemployment being something that is just given to us, not something that can be affected by policy, and certainly not something that has very real human consequences. Again, it is a term that misleadingly conveys economics as a cold, heartless subject. But I would rather our profession was incorrectly perceived as cold and heartless than correctly perceived as innumerate. So as long as NAIRU is the only alternative, I will champion the natural rate!

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A low cost way to help the retailers - The Dismal Science

Apr 05, 2015

Eric asks
If Hartford, or anybody else, is able to come up some better way of processing GST at the border, without imposing undue hassle on either those who might be deterred from exporting to New Zealand or on Kiwi shoppers, and without collection costs that exceed the value of the GST collected, that would be great.

I’ll quibble a bit at the wording, the collection costs should not exceed the value of the improved allocative efficiency from removing a tax distortion, not the revenue collected, which is likely a much tougher hurdle, but either way I’m prepared to give it a go. 

My proposal will not just deal with the distortion that purchases by consumers that are made directly from overseas through on-line retailing receive a favourable tax treatment relative to those that are processed through an importer. It will also deal with a larger distortion in the GST. As it currently stands, the GST applied to imports does not apply to purchases made by New Zealanders while travelling overseas, and similarly the zero-rating of exports does not apply to the sale of services to foreign tourists while in New Zealand. That is, the current GST regime favours overseas tourism by New Zealanders over other imports, and penalises the New Zealand tourism industry relative to other exports.

So here is my proposal: Completely exempt all imports from the GST, and at the same time stop zero-rating exports and require firms to charge GST on all sales, including those to foreigners. Retail New Zealand should be happy, they would no longer be treated in differently from overseas on-line sellers in their tax treatment in New Zealand. And firms selling both overseas and in New Zealand would be happy to no longer have to have separate out sales overseas and domestic sales when filing their tax returns.


This idea runs completely counter to our inner mercantilist instincts, but our instincts don’t cope well with general-equilibrium reasoning. In my experience the greatest eye-opening moment you can give students in economics—the sort of epiphany that has them changing instantly from “this is obviously wrong” to “this is obviously right” is the Lerner symmetry theorem,  which shows that an import tax is exactly equivalent to an export tax. The idea here is that a tax on exports or imports is really a tax on trade. In the long-run, the present value of exports has to equal the present value of imports, as they are just opposite sides of the equals sign in a budget constraint. A tax on exports is a tax on imports, as it shifts resources away from producing for overseas (with the consequent importing from overseas that that allows) to producing for local consumption. (I was told that, during the Muldoon era, Treasury, knowing that it could not pursuade Muldoon to reduce tarrifs encouraged him in his policy of export subsidies, knowing that the latter would counteract the former.) 


In a country with a floating exchange rate, the way that the Lerner equivalence theorem would play out if it were to adopt the change from levying the GST on imports to levying it on exports, would be through a depreciation of the currency by the amount of the GST. So sure exporters would have to put up their prices to foreigners in NZ dollars by 15%, but the goods would not seem to be more expensive to foreigners because of the 15% depreciation. Similarly, the 15% GST coming off imports would be offset by the depreciation. In general, therefore, there would be no change, but with a few exceptions. On-line purchases would become 15% more expensive in NZ dollars due to the depreciation with no offsetting change in taxes. Trips overseas would similarly become 15% more expensive, but at the same time, New Zealand would become a far cheaper place for foreigners to visit, again.

I don’t imagine for a moment that any government would implement this policy. Instinctive mercantilism is too strong in all voters, and only a few have experienced the epiphany of general equilibrium reasoning. But this is not a “modest proposal” in the Swiftian sense. I am deadly serious. 

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Bleg: Quantifying the value of bowling variety - The Dismal Science

Mar 30, 2015

A common critique of the current English ODI side is that they suffered from having a sameness to their bowling attack--a series of right-handed fast-medium swing bowlers. It's an interesting question. Obviously, diversity in bowling styles can only take you so far: there is a limit to how much aggregate quality a team would be prepared to sacrifice in order to increase diversity, but it is not clear that there is any value to diversity at all. The question was raised recently in the following tweets:

@CricketFanBob Variety is often said to be advantageous, but has this ever been tested with data? May not be true.
— ballsintherightareas (@ballsrightareas) March 3, 2015
There are some obvious ways in which diversity might improve a team's bowling as a unit. First, having the style of bowling change from over to over might make it harder for batsmen to settle into a rhythm. Second, if some bowling types are more effective wicket takers against right-handed batsmen and others against left-handed, then style diversity might help stop one batsman running away with a game. But these are big mights. The twitter thread above led to this request:

@ballsrightareas @CricketFanBob I wonder if we can interest @seamus_hogan to take on this challenge?
— Declaration Game (@chrisps01) March 3, 201
I'm up for the challenge, but I can't see obvious solutions to three conceptual problems:

1. As @CricketFanBob asks, how do you define variety?

If you look at the cricinfo player profiles, you will find that Bill O'Reilly and Clarrie Grimmett, who played in the same Australian test team, are both classified as "legbreak googly". This is true, but this simple classification does not tell you that O'Reilly was an unusually fast spinner who liked to bowl with the wind, while Grimmett was a more-classical flight-into-the-wind legbreak bowler. Similarly, player profiles will tell you that Joel Garner and Malcom Marshall were both "right fast", but the difference between quite fast delivered by a 6'8" bowler and extremely fast delivered by a 5'11" bowler is probably quite substantial. Maybe, however these examples are sufficiently rare that simple cricinfo categorisations are sufficient. But...

2. ...What is the best way of aggregating these bowling-type classifications into a measure of variety.

Is RFM, RFM, LF, RM, SLO more diverse than RFM, LF, RM, SLO, SLO? I think so, but how do you quantify that. And above all,

3.... How do you assess what performance a given set of individual bowler abilities would be expected to produce in order to assess whether variety (or its absence) can explain some of the difference?

In particular, how do you control for the endogeneity that, for example, a spin bowler in spin-friendly conditions will probably a) be in a team with other spin bowlers to take advantage of those conditions, and b) likely to do better than average because of those conditions, making it difficult to infer any value to diversity that might exist.

I have some ideas, but I suspect that the number of variables needed would exhaust the useful degrees of freedom. Any thoughts?
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Competitive ODI matches - The Dismal Science

Mar 26, 2015

Before the current cricket world cup started, the International Cricket Council (ICC) announced that the next event (in 2019), would feature only 10 teams, the eight highest-ranked to qualify automatically, and two to be selected by a qualifying tourna...

Batting out your overs - The Dismal Science

Mar 08, 2015

The mantra that "the biggest sin a team batting first in an ODI can commit is to not bat our its overs" has long been a bugbear of mine. As Dan Liebke noted in a rant about net-run-rate the other day, We've had Duckworth Lewis for decades now and,...

More on Courtsiding - The Dismal Science

Feb 23, 2015

Eric is wondering first, what business the NZ police have enforcing ICC ticket terms and conditions regarding "courtsiding" by evicting from NZ cricket grounds spectators who are in violation of the T&C but not breaking any law, and second, why the...