Bondonomics! Sky-High Expectations for new 007 Flick


I finally published some thoughts on the ‘Bond, James Bond 007’ movie franchise business model via an opinion piece, which ran in the Australian Financial Review (today, Monday 9 November), titled: “Bond Formula Ensures Franchise will Die Another Day” on p.35.

With the new movie (number 24) opening in Australian cinemas on Thursday, it is a timely piece for those of you wanting your Bond fix before then.

More on Optimal Sequencing: Soccer Edition


[Cross-posted at: Wages of Wins Journal, 7 August 2014]

This earlier Wages of Wins piece by Shane Sanders (July 29, 2014) generated plenty of discussion. It highlighted the problem of Triathlon deaths in the swim leg. One crucial point to make with many economic policy analogies on which to draw is that sequencing of the legs (or phases) matters – all other considerations aside, the ‘best’ sequence of phases can be optimized according to some objective (in this case, minimizing fatalities).

One such possible economic policy analogy is with respect to unemployment benefits. Imagine a two-phase policy, where in the first six months the recipient is eligible to a relatively unrestricted entitlement of an amount according to some predefined percentage (say 40%) of some benchmark (average weekly earnings or minimum full-time wage). If the recipient is still unemployed after the 6 months have elapsed, a second phase kicks in at which the benefit is now highly restricted thereafter (having to satisfy minimum job search requirements, etc.) and/or reduced in value. Now, many people will disagree as to whether this two-phase policy is too generous or too miserly (or even on the basis of something else entirely). However, one aspect most of us would agree on is that swapping the sequence of these two phases would make absolutely no sense whatsoever.

It got me thinking about other such analogies about sequencing from sport that could be useful in policy circles. Recently, I published an article in the December 2013 issue of Journal of Sports Economics [gated], along with Jan Libich (my colleague at La Trobe) and Petr Stehlίk (University of Western Bohemia, Czech Republic). We took on soccer’s penalty shoot-out problem.  In knock-out matches that are tied after 90 minutes, the following 30 minutes of overtime is often beset with overly-defensive play due to insufficient incentive to attack.   This means that overtimes often finishes goalless, and that nearly 50% of the time, the match is decided via penalty kicks anyway (put differently: in nearly one of every two ties, overtime fails to achieve the one and only thing it is fundamentally there to do).

We show that an alternative sequence – regulation time followed by a penalty shoot-out followed by overtime – improves attacking outcomes. The qualification is that, while the shootout produces a winner – you still play overtime, with the winner of that winning the contest as currently. It is only when overtime fails to resolve the deadlock that the winner becomes the team that had won the shootout already (think of winning the shootout as worth half-a-goal lead at the start of overtime).

Specifically, we show that the probability of at least one goal being scored in overtime rises by approximately 50% (depending on the underlying characteristics of the match). Exactly how we estimate the effect of a policy that’s never existed is outlined in the paper for those of you who are interested to read further.

Coming back to sequencing, why the simple economic intuition (as well as the data) says this rule change will likely work is the following: there will always be one team chasing the next goal, because they will be eliminated unless they do – they have little else to lose. While the other team may correspondingly become more defensive, we show the net effect to be overwhelmingly positive. Furthermore, what you will no longer get are those overtimes where both teams sit back having jointly overestimated the probability that they will win if it goes to a shootout.

Had Mario Götze spurned that chance just minutes from time in the recent World Cup final, and it had have instead gone to spot kicks, the penalty shootout problem would now be far higher on the soccer agenda. Nonetheless, better public policy (optimal sequencing included) should never be far from the agenda, so I hope to see more studies like this make some impact in the broader public policy debate.

Superb World Cup ‘Selection Bias’ Example


[Cross-posted at: The Sports Economist, 4 July 2014]

For all those economics professors and tutors out there who struggle to explain the crucial concept of ‘selection bias’, a nice illustration can be found in FIFA World Cup finals records. With students (at least those who do not loathe sport) currently in soccer-crazy mode, they may be more motivated to understand this concept through the following trivia question:

Q: In World Cup (finals) history, which team has the highest goal-scoring ratio (goals scored divided by games played)?

Scroll below for the answer, which may be surprising to many, except the amateur World Cup historians among you.

Most people would instinctively say Brazil; however, they appear second on this list at 2.16 per game (218 from 101 games, inclusive of the second-round of the 2014 edition). Germany follows at a very-close third with 2.15 (221 from 103).

The record-holders are…wait for it…Hungary! Yes, those ‘Mighty Magyars’ top the list and (get this) by a comfortable margin, too – indeed a chasm – their 87 goals in 32 games comes in at an astonishing 2.72 goals per game.

If you don’t believe me (and you’re more than entitled not to), check the figures here. Hungary has never won the World Cup, but have twice reached the final: in 1938, when they lost to Italy; and again in 1954, with legends Puskás and Kocsis (et al.) in their ‘Golden Team’, which came into that World Cup undefeated in more than 4 years, only to squander a two-goal lead (which they had after only 8′) to (the then-West) Germany, who incidentally they had annihilated in the first round by the incredible scoreline of 8-3.

OK, so what is the selection bias here? Well, look at the chart below, which displays average goals per game by World Cup. The flags I added at the top of the bars denote the World Cup finals that Hungary both entered and qualified for.

goals by world cup

From this, it is easy to see that scoring outcomes were lower from 1962 compared to earlier, with a further decline (albeit slight) since then. Hungary is but one of a number of national football teams that were among the best handful in the World for considerable periods at any time since the inaugural World Cup in 1930 (according to retrospective Elo ratings, they were ranked number one as late as 1965). However, of all national teams in this category, Hungary is the one that played the highest proportion of its matches in higher-scoring World Cups.

For all you Magyars out there lamenting your boys’ extended absence from the big stage (28 years now and counting), rest assured that (since it’s unlikely that Brazil and Germany will ever get anywhere near 2.72) the only way to guarantee holding this highly-prestigious record in perpetuity is to continue to NOT qualify for the finals – proof that there is indeed success in failure!

UPDATE: OK, Germany (2.181) now overtake Brazil (2.146) for second-place after that unbelievable semi-final; but Hungary’s place at the summit still looking just as safe in the bank vault as before!

James Reade on Tennis Home-Advantage


My co-author, James Reade (University of Reading) published an excellent piece today in The Conversation (UK edition) on our joint work using pro-tennis data, focusing on home-court advantage in the sport. This is of topical interest in Britain right now owing to Andy Murray’s defense of his Wimbledon title currently being in full swing.

Read: Hard Evidence: Does Home Support Help or Hinder Murray’s Wimbledon Chances?

We are interested primarily in other aspects of the data; nonetheless, home advantage is a nice little scientific problem that the average fan can sink their teeth into – nice one, Jimmy!

NFL Scheduling and Competitive Balance


[Archived from: The Sports Economist, 2 January 2014]

In this paper (now forthcoming, JSE: doi: 10.1177/1527002512471538), it was shown that for every single year after the expansion to 32 teams in 2002 (until 2011), the NFL was even more competitively balanced when the strength of schedule was accounted for, without exception, using four common CB measures. Previous The Sports Economist posts on this are here and here.

Since the 2013 regular season has just been completed, we crunched the numbers on the two most recent seasons. The streak remains unbroken, once again demonstrating the importance of adjusting CB measures for unbalanced schedules.


Standard Deviation Ratio: 1.5245 (unadjusted); 1.4645 (adjusted)

Herfindahl Index of CB:  1.1453 (unadjusted); 1.1340 (adjusted)

Concentration (12) Ratio:  1.4010 (unadjusted); 1.3889 (adjusted)

Gini Coefficient:  0.2776 (unadjusted); 0.2647 (adjusted)

Home Advantage Omen for Ashes Whitewash


[Archived from: The Sports Economist, 2 January 2014]

With cricket’s latest ‘Ashes‘ series having been decided more than a fortnight ago, much of the remaining interest in the final Test, just underway, centres purely on whether Australia can complete a 5-0 Ashes whitewash for only the third time in history (following 1920/21 and 2006/07). Most ‘key performance indicators’ for Sydney are pointing in that direction – the newly-rediscovered ferocity of the Australian pace attack, not to mention the unexpected feebleness of England’s batting top-order (and middle-order, for that matter). England have also selected three debutants.

Moreover, there is an additional factor that, given recent history, points fairly and squarely in Australia’s favour – merely that they are the home side. The calendar year of 2013 was a stellar one for home teams in Tests. Specifically, of the 44 Tests played last year, a remarkable 30 were won by the home team, 10 were drawn and only 3 won by the away team (Pakistan looks likely to make that 31 against Sri Lanka in the Test that started on New Year’s Eve).

The surprising element of this occurrence, according to some pundits, was that it came after a period, from 2010-2012, in which away teams performed quite admirably against the tide of home-ground advantage. At least on the basis of raw numbers – in these years, a combined 124 Tests resulted in 48 home wins, with the number away wins almost at parity (43). This apparent ‘trend’ towards away teams did not go unnoticed by sports journalists and other non-academic writers. For example, Gideon Haigh remarked to this effect (“The quiet revolution: home ground advantage begins to fade away”, The Australian, 20/12/2012).

However, as economists know all too well, looking at just the raw figures is too parsimonious an analysis for making claims that the nature of home-ground advantage – a phenomenon so well researched, understood and entrenched in sporting culture – has diminished so fundamentally and suddenly. What needs to be understood about the sample of Tests in those years were that they were correlated with factors that skew the chances of victory in favour of the home team to begin with, most obviously on the basis of relative strength of both teams.

For example, easily the best team of 2012, South Africa, played 10 Tests that year. All but one of them were played away from home, with an unbeaten record (4 wins, 5 draws) befitting a World number one. This is a nice example of what in economics (and some other scientific disciplines) is called a ‘selection bias’ – such biases have to be accounted for, since it is not difficult to imagine how the figures would have more-highly favoured home teams at an aggregate level if the Proteas had instead been scheduled to play 9 Tests at home. Another example (this time for 2011) is that minnows Bangladesh and Zimbabwe played a combined total of 8 Tests, 7 of which were on home soil, again skewing the overall record in favour of away teams. With such a small sample of teams and Tests, these selection biases are important and should not be ignored.

Likewise, the stunning reversal back towards home teams in 2013 has to be taken with caution – (the again rampant) South Africa played 7 of its 9 Tests at home, winning 6 and drawing the other. Second-ranked India also played the majority (6 of 8) of its Tests at home, completing a perfect record, not to mention third-ranked England’s impressive Northern summer record (5 wins, 2 draws), prior to their almost inexplicable slide in the current series.

Most Australian cricket supporters will  hope that the aberration of 2013 does not continue past this week – their next series is away to South Africa. Otherwise, that tour could prove to be a sobering experience following the current euphoria. Nevertheless, the influence of home-ground advantage in Test cricket does not appear to be under any immediate threat. To this end, if one was the betting type, I would not be shy in punting on a home victory at the SCG.

Media Misses Point on Cricket’s Decision Review System


[Archived from: The Conversation, 15 July 2013]

The first Ashes Test was indeed a veritable thriller. England edged Australia by a mere 14 runs, after an absorbing four-and-a-half days of action to go one-up in the best-of-five series. For those not well versed on the sport, only a dozen or so of more than 2,000 Tests dating back to 1877 have been decided by fewer runs.

Partly because of the closeness of the match, much of the media focus has centred on decision outcomes arising from the Decision Review System (DRS). This system, which allows up to two incorrect challenges per innings, is in economic terms a resource like any other – a scarce one, and one to be used, lest it be lost.

Opening with a disclaimer, I have absolutely no sympathy for my team here. No Australian cricket fans were complaining back in the pre-DRS era in 2008 when the Andrew Symonds incident in Sydney arguably turned the entire series against India in Australia’s favour. I could even excuse Doug Bollinger for his infamous dummy spit in Adelaide a couple of summers later against the West Indies when the system was still in its infancy, but by now there is no longer any excuse for such irrationality.

What is not in dispute is that the DRS has significantly reduced the incidents of incorrect umpiring decisions being allowed to effectively stand, relative to the previous status quo. This is also true in tennis, yet the consensus is that it works perfectly well in that sport. This helps tell the economist in me that there is very little, if anything at all, wrong with the system itself in cricket. But try telling that to various print and broadcast journalists.

Many local scribes over the weekend into today have sadly succumbed to the temptation to pander to the masses of their readership. Since Australian fans want to have our spleen vented in one united voice right now (among other ways) by reading what we want to hear – that “we woz robbed” – sports writers have a strong incentive to serve up precisely that, even if it misses the entire point.

As an economist, of ultimate policy-related importance is that what the DRS did was to re-assign some (albeit small) proportion of decision-making power from the umpires to the players themselves. But what is being ignored in the DRS discourse is the commensurate responsibility that comes with that power.

Sure, Aleem Dar’s third-day call on Stuart Broad was indeed a howler, and that wasn’t the only injustice served up by the men in white during this Test either. But why is it that no-one seems to be willing to give Australian captain Michael Clarke and his men the unconditional lambasting they deserve for willfully squandering their unsuccessful challenges like a bunch of drunken sailors on tour?

An argument here might be to say that (former Australian wicket-keeper Adam Gilchrist’s views on walking aside) professional athletes cannot be trusted for complete honesty anyway. So why bother holding them to account like we have always done to the umpires?

However, this argument is weak at best. In fact, if I were Stuart Broad, I too would have defiantly stood my ground. What’s more, rather than looking sheepish about it, I would have backed it up by giving the Australian players a right old bollocking – or perhaps sledging – telling them (in laymen’s terms) that if they were not so systematically and profligately quick on the trigger with their challenges, I’d be back in the pavilion by now…so suck it up, laddies!

Even more worrying was that the harsh lessons from the third innings of the match were not heeded in the final innings, when Australia once again exhausted their challenges early on (though they had already benefited once from one correct challenge). Imagine if Brad Haddin had not actually nicked the ball, yet were incorrectly shown the index finger.

Economics, particularly on the micro side, is about decision-making. I am yet to meet a cricket-loving microeconomist who thinks the DRS is anything but a solid system with an appropriate treatment given to incentives and strategy.

It is just a pity that the Australian cricketers have not yet woken up to their responsibility of mastering the art of rationality around it, and that commentators and writers have not yet learned to correctly apportion the fair share of the blame on the players for the so-called injustices that can still arise under the system.