rain – Pertinent Observations

Football in the rain

The weather in Barcelona had been excellent for the last couple of weeks. While it wasn’t warm (most days had required me to wear a rather heavy jacket), it was pleasant and sunny, with hardly any rain. For whatever reason, the rain gods had to choose today, when we had tickets to watch Barcelona play Arsenal in the Champions League, to pour down.

I had made a dash to a nearby supermarket to pick up light raincoats earlier this evening. In hindsight, I can attest that Quechua Rain Cut is a brilliant product and does its job. Among the best raincoats I’ve used. Very effective and light, and can be worn over other warm clothes!

Rain meant we had to take the bus to the stadium rather than walk (it’s 2km from home), and rain also meant that bus made painful and slow progress, dropping us near the Camp Nou some 15 minutes before kickoff. And then there was the lack of queueing at security check outside the stadium (made worse by the pouring rain).

Before the game I’d checked if backpacks would be allowed at the stadium and various forums had mentioned in the affirmative. As it turned out, they weren’t allowing them in today, which meant we had to drop my wife’s (fairly expensive) backpack at the gate before we got in. It was just before kickoff that we took our seats.

Rather, I took my assigned seat while my wife randomly occupied the empty seat next to mine, hoping to exchange it with her seat (which was one row in front) when the rightful occupant arrived. As it transpired, the rightful occupant never arrived (perhaps he was a season ticket holder deterred by the rain, else I can’t imagine someone letting go of a €150 ticket. I plan to do a post on season ticket pricing when back from vacation. Context is Hull City revamping their season ticket system. Interestingly the other seat adjacent to mine was also vacant! In fact, there were quite a few empty seats at the stadium).

There was this nice anecdote which can be used in economics classes on externalities – given that it was raining, it meant that people had an incentive to hold up an umbrella while sitting, but that would mean those in the rows behind would be inconvenienced – a negative externality. Usually, nudges and shouts did the trick to lower the umbrellas, but some umbrella men were steadfast.

Anyway, despite being in the third tier of stands, the view of the pitch was top class (apart from the occasional intrusive umbrella) and we soon got adjusted to the drizzle. The players weren’t that well adjusted, though, for they constantly kept slipping on the turf.

Photo taken at half time. The messy hair can be explained by the hood of the raincoat

Interestingly, the noise levels weren’t too high – when Barcelona scored, celebration was rather muted. There were no shouts of Vis?a Catalunya at 17 minutes 14 seconds (this had been rather vociferous the last time I was at the Camp Nou, but that was in the run up to the (later cancelled) secession referendum) – but that could be because that was exactly around the time Neymar scored.

Though there is another possible reason people didn’t celebrate too loudly – I belive people had gotten into certain positions that helped them beat the rain (like I’d pulled my raincoat forward and over my knees to protect my thighs from getting wet), and heavy celebration would disturb these positions. There was the usual drum band behind the south goal, but the crowd was otherwise rather quiet (the away stand directly behind us was an exception, though!).

Anticipating an exodus, we had decided to leave as soon as the clock opposite us struck 42 in the second half. As it happened, Barcelona scored their third goal just as we were about to disappear into the stands. The early exit helped – there was a bus right outside the stadium that would drop us next to home, and we managed to find seats on that.

Oh, and the backpack that we had abruptly discarded near the gate when we went in was still in the exact position where we’d left it, and we gleefully picked it up on our way out. Quite impressive for a city that is known for its high rate of petty crime (which I’ve been victim to. I lost my spare phone on the day I landed last month, between getting off the cab from the airport and getting into my apartment building!)!

Gloomy weather

For most of today, the weather in Bangalore has been what most people would traditionally classify as “gloomy”. The sun has mostly been invisible, popping out only now after a fairly strong shower. There has been a rather thick cloud cover, with the said clouds being mostly dark. There has been the threat of rain all day, culminating in a rather powerful shower an hour back.

I haven’t minded the weather one bit, though, though it helps that I haven’t had to step out of home all day. I’ve been happy sitting by the window, sipping coffee and tea and green tea, and eating Communist peanuts, and working. In fact, I’ve grown up considering this kind of weather (cool, cloudy, with a hint of drizzle) as being the ideal romantic weather, and when the weather turns this way nowadays, I miss the wife a whole lot more! Till recently, I never understood why such weather was traditionally classified as “gloomy”. Until I went to Europe to visit the wife last month.

March in Europe is traditionally classified as “Spring” (summer doesn’t come until June there, which is hard for someone from Bangalore, where summer ends in May, to understand), but in most places I went to (I visited five different cities during my trip), the weather was basically shit. I had carried along my “winter jacket” (bought at a discount in Woodland at the end of last winter), and didn’t step out even once without it. It was occasionally accompanied by my woollen scarf and earmuffs, with hands thrust into pockets.

For days together the sun refused to come out. In fact, our entire trip to Vienna was a washout because of the weather. Thick dark clouds and no sun might be romantic in tropical Bangalore, but in Vienna, where it is accompanied by chilling winds and occasionally maddening rain (and once snow), it can be devastating. It can cause insane NED – you might argue that if weather was so bad in Vienna we could have used it as an excuse to stay inside museums and see things, but the gloom the weather causes is real, as we frittered and wasted hours in an offhand way, hanging around in coffee shops doing nothing, and just touring the city in trams, again doing nothing (we had got a three-day pass).

The one time the sun peeped out (after a heavy shower like this afternoon’s in Bangalore), we went ecstatic, but our joy was shortlived as it was quickly followed by another downpour which killed our enthu for the rest of the day.

The bad weather followed us all though our 10-day trip across Prague, Vienna and Budapest. The first and last being former Soviet cities didn’t help, as the (really beautiful from inside) apartment we stayed in Prague was in a rather dreary area, with the weather making the locality even more depressing. As a consequence, we hardly hung around in the locality, taking away dinner on each of the three days we were there. Our Budapest apartment was in a more vibrant part of town (most of our meals were within 500m of our apartment) but the general dreariness and chill meant that we didn’t explore as much as we would have otherwise done, perhaps.

We were back in Barcelona (which too had been rather dreary in March) last Saturday night, and when there was bright sunshine on Easter Sunday morning as we went to the nearby bakery for breakfast, we were absolutely ecstatic. We spent time just sitting on the parkbench, soaking in the sunshine. I made a mental note that if I’m going those parts next spring, I should go there AFTER Easter and not before (like this year). I also made a mental note to never again question why weather that is traditionally called “gloomy” is called so.

Duckworth Lewis and Sprinting a Marathon

How would you like it if you were running a marathon and someone were to set you targets for every 100 meters? “Run the first 100m in 25 seconds. The second in 24 seconds” and so on? It is very likely that you would hate the idea. You would argue that the idea of the marathon would be to finish the 42-odd km within the target time you have set for yourself and you don’t care about any internal targets. You are also likely to argue that different runners have different running patterns and imposing targets for small distances is unfair to just about everyone.

Yet, this is exactly what cricketers are asked to do in games that likely to be affected by rain. The Duckworth Lewis method, which has been in use to adjust targets in rain affected matches since 1999 assumes an average “scoring curve”. The formula assumes a certain “curve” according to which a team scores runs during its innings. It’s basically an extension of the old thumb-rule that a team is likely to score as many runs in the last 20 overs as it does in the first 30 – but D/L also takes into accounts wickets lost (this is the major innovation of D/L. Earlier rain-rules such as run-rate or highest-scoring-overs didn’t take into consideration wickets lost).

The basic innovation of D/L is that it is based on “resources”. With 50 overs to go and 10 wickets in hand, a team has 100% of its resource. As a team utilizes overs and loses wickets, the resources are correspondingly depleted. D/L extrapolates based on the resources left at the end of the innings. Suppose, for example, that a team scores 100 in 20 overs for the loss of 1 wicket, and the match has to be curtailed right then. What would the team have scored at the end of 50 overs? According to the 2002 version of the D/L table (the first that came up when I googled), after 20 overs and the loss of 1 wicket, a team still has 71.8% of resources left. Essentially the team has scored 100 runs using 28.2% (100 – 71.8) % of its resources. So at the end of the innings the team would be expected to score 100 * 100 / 28.2 = 354.

How have D/L arrived at these values for resource depletion? By simple regression, based on historical games. To simplify, they look at all historical games where the team had lost 1 wicket at the end of 20 overs, and look at the ratio of the final score to the 20 over score in those games, and use that to arrive at the “resource score”.

To understand why this is inherently unfair, let us take into consideration the champions of the first two World Cups that I watched. In 1992, Pakistan followed the principle of laying a solid foundation and then exploding in the latter part of the innings. A score of 100 in 30 overs was considered acceptable, as long as the team hadn’t lost too many wickets. And with hard hitters such as Inzamam-ul-haq and Imran Khan in the lower order they would have more than doubled that score by the end of the innings. In fact, most teams followed a similar strategy in that World Cup (New Zealand was a notable exception, using Mark Greatbatch as a pinch-hitter. India also tried that approach in two games – sending Kapil Dev to open).

Four years later in the subcontinent the story was entirely different. Again, while there were teams that followed the approach of a slow build up and late acceleration, but the winners Sri Lanka turned around that formula on its head. Test opener Roshan Mahanama batted at seven, with the equally dour Hashan Tillekeratne preceding him. At the top were the explosive pair of Sanath Jayasuriya and Romesh Kaluwitharana. The idea was to exploit the field restrictions of the first 15 overs, and then bat on at a steady pace. It wasn’t unlikely in that setup that more runs would be scored in the first 25 overs than the last 25.

Duckworth-Lewis treats both strategies alike. The D/L regression contains matches from both the 1992 and 1996 world cups. They have matches where pinch hitters have dominated, and matches with a slow build up and a late slog. And the “average scoring curve” that they have arrived at probably doesn’t represent either – since it is an average based on all games played. 100/2 after 30 overs would have been an excellent score for Pakistan in 1992, but for Sri Lanka in 1996 the same score would have represented a spectacular failure. D/L, however, treats them equally.

So now you have the situation that if you know that a match is likely to be affected by rain, you (the team) have to abandon your natural game and instead play according to the curve. D/L expects you to score 5 runs in the first over? Okay, send in batsmen who are capable of doing that. You find it tough to score off Sunil Narine, and want to simply play him out? Can’t do, for you need to score at least 4 in each of his overs to keep up with the D/L target.

The much-touted strength of the D/L is that it allows you to account for multiple rain interruptions and mid-innings breaks. At a more philosophical level, though, this is also its downfall. Because now you have a formula that micromanages and tells you what you should be ideally doing on every ball (as Kieron Pollard and the West Indies found out recently, simply going by over-by-over targets will not do), you are now bound to play by the formula rather than how you want to play the game.

There are a few other shortcomings with D/L, which is a result of it being a product of regression. It doesn’t take into account who has bowled, or who has batted. Suppose you are the fielding captain and you know given the conditions and forecasts that there is likely to be a long rain delay after 25 overs of batting – after which the match is likely to be curtailed. You have three excellent seam bowlers who can take good advantage of the overcast conditions. Their backup is not so strong. So you now play for the rain break and choose to bowl out your best bowlers before that! Similarly, D/L doesn’t take into account the impact of power play overs. So if you are the batting captain, you want to take the batting powerplay ASAP, before the rain comes down!

The D/L is a good system no doubt, else it would have not survived for 14 years. However, it creates a game that is unfair to both teams, and forces them to play according to a formula. We can think of alternatives that overcome some of the shortcomings (for example, I’ve developed a Monte Carlo simulation based system which can take into account power plays and bowling out strongest bowlers). Nevertheless, as long as we have a system that can extrapolate after every ball, we will always have an unfair game, where teams have to play according to a curve. D/L encourages short-termism, at the cost of planning for the full quota of overs. This cannot be good for the game. It is like setting 100m targets for a marathon runner.

PS: The same arguments I’ve made here against the D/L apply to its competitor the VJD Method (pioneered by V Jayadevan of Thrissur) also.

Ranji Trophy and the Ultimatum Game

The Ultimatum Game is a commonly used research tool in behavioural economics. It is a “game” played between two players (say A and B) where A is given a sum of money which he has to split among himself and B. If B “accepts” the split, both of them get the money as per A’s proposal. If, however, B rejects it, both A and B get nothing.

This setup has been useful for behavioural economists to prove that people are not always necessarily rational. If everyone were to be rational, B would accept the split as long as he was given any amount greater than zero. However, real-life experiments have shown that B players frequently reject the deal when they think the split is “unfair”.

A version of this is being played out in this year’s Ranji Trophy thanks to some strange rules regarding points split in drawn games. A win fetches five points while a loss fetches none. In case of a drawn game, if the first innings of both sides has been completed, the team that has scored higher in the first innings gets three points, while the other team gets one. The rules, however, get interesting if not even one innings for each side has been completed. If the match has been rain affected and overs have been lost, both sides get two points each. Otherwise, both sides get zero points each!

I don’t know about the rationale of this strange points system, but I guess it is there to act as a deterrent against teams preparing featherbeds, batting for most of the four days and not even trying to win the match. In general, I haven’t been a fan at all of the Ranji Trophy’s points scoring system, and think it’s quite irrational and so refuse to comment on this rule. What I will comment about, however, is about the “ultimatum” opportunity this throws up.

In the first round of matches, Saurashtra batted first against Orissa and piled up a mammoth 545 in a little under two days. The magnitude of the score and the time left in the match meant that Orissa had been shut out of the game, and the best they could’ve done was to overtake Saurashtra on first innings score and get themselves three points. However, they batted slowly and steadily, with Natraj Behera scoring a patient double century, and with a few minutes to go in the game, they were still over 50 runs adrift of Saurashtra’s score, with three wickets in hand.

At that time, they had the chance to declare their innings, still some runs adrift of Saurashtra’s score, and collect one point, and handing over three points to Saurashtra. They, however, chose to bat on and block the game, and both teams finally ended up with zero points. It maybe because they also see Saurashtra as a competitor for “relegation”, but I thought this was irrational. Why would they deny themselves one point – if only to deny Saurashtra three points? It’s all puzzling.

Going forward, though, I hope the Ranji Trophy rules are changed to make each game a zero sum game (literally). Or else they could adopt the soccer scoring of 3 points for a win and 1 for a draw (something I’ve long advocated), first innings lead be damned!