The Secret of Chess?

Posted by David Smerdon on Dec 3, 2017 in Chess

A couple of months ago, I received a curious email:


Hello, Mr. Smerdon,

I recently published an innovative book on chess knowledge/evaluation,

‘The Secret of Chess’. 

It is written very much in the vein of Nimzovich’s and Kmoch’s works,

but is of much larger scope and accuracy of assessment

Please, try to take a look at it, I guess you will not be disappointed.

Best regards,

Lyudmil Tsvetkov, author of the book


As you might imagine, I was pretty sceptical that this book would indeed revolutionise chess – especially after discovering Tsvetkov’s a 2100 player who has been inactive from tournaments for more than a decade. Still, the author claims to have spent the past five years almost entirely devoted to the study of chess, and especially the use of engines. Given the ‘big data’ revolution in many sciences today, a part of me has always believed that there must be more sophisticated ways to train in chess. And so, despite the somewhat outrageous claims and poor written English of the introduction, I pushed on, hoping to find at least one or two useful training nuggets. And so, I read the whole book.


Before I get into the details, I want to make two paradoxical statements. First, I completely understand why other chess reviewers have been at best dismissal and at worst harshly critical of The Secret of Chess. Second, however, this book is a one of a kind work that legitimately has the potential to revolutionise how we think about chess.


In fact, it’s not even written as a regular book, but more of a mathematics textbook and an encyclopaedia (ironically, Amazon classifies it under ‘Humour and Entertainment’). It’s essentially just a list of hundreds of essential chess themes or patterns that together comprise the key heuristics to success, each with a definition, frequency and value (written as a bonus or penalty in terms of centipawns, or hundredths of a pawn). Here’s an example:


Blocked pawns on squares the colour of the bishop

Definition: pawns, blocked by enemy pawns on squares the colour of the bishop

Value: additional penalty, -10cps [centipawns], both for the mg [middlegame] and eg [endgame]

Additional information: the over-penalty is due because:

– the condition of being blocked makes the pawns fixed targets, unable to move; fixed targets are easier to attack and destroy

– blocked in general represents a more durable condition, further highlighting the weakness

Frequency: very frequent


The themes are typically accompanied by one or more illustrative diagrams, and occasionally also so-called ‘piece-square tables’, listing the centipawn values for pieces on each of the 64 squares of the board.


Such tables, like the values, are presumably designed for chess engine programmers, as their goal is primarily in arriving at the most accurate evaluation of a position as possible. And indeed several members of the computer chess community have apparently spoken highly of Tsvetkov’s identifying and quantifying these features. And you can actually find quite a few interesting threads on the Talk Chess forum in the past in which the author has contributed to improving the world’s strongest engines with his suggestions. I do get the impression from reading the book that chess programmers comprise Tsvetkov’s primary audience.


From a regular reader’s perspective, the tables and precise values aren’t very helpful. We’ll never be able to remember all of these numbers, let alone implement them in a live game. What would have been useful is to have these values distilled down into the more human “small advantage”, “clear advantage” and so forth, along with other simplifying heuristics. But after a chapter or two, one does get used to the book’s structure, and the going gets easier. What I did was make a list of the key themes that I wasn’t aware of, together with a more human assessment of their relative value and some clues for how I can remember them. It took some time and effort that I wish had been done for me in the book, but at the end of the day, I consider this written summary to be immensely rewarding and a reflection of the true value of this book.


Many of the themes are well-known to seasoned players, such as outposts, open files, the bishop pair, etc. But there are plenty of others that aren’t so obvious, at least to me, and which I found really interesting. Some of these concepts are so (post)modern that the author has had to come up with his own original terms for them, such as “spearhead pawn”, “unbackwarded pawn” and “double-root pawn”. Indeed, a huge bulk of the themes have to do with various pawn features, which leads to some of Tsvetkov’s most controversial arguments: That 1.c4 is White’s strongest first move, that the French is close to a losing opening for Black, and that the Stonewall Dutch, for either colour, is to be recommended. (Given my own experience, I’m not sure how I feel about this…)


It follows from his concept of “twice-backwarded pawns” that after 1.c4 e5 2.Nc3 Nf6, White should play 3.e4!, with an advantage. To be honest, I feel that Tsvetkov could be a little biased here by his large experience playing against engines; we know that engines struggle to play blocked positions, so a human would have a better chance of success by trying to close things up as soon as possible. Is 3.e4 objectively as strong against another human? (And, conversely, is 3.e3 as bad a move as Tsvetkov makes out? For example, he gives the position



where he says:


“In spite of the big development advantage white enjoys, black has already a winning

position. And the main reason for this is the familiar central pawn pattern in the

form of the e4,e3,f2,g2 pawns. The central e4 black backwardmaker is having a

cramping effect upon the entire white king side and renders the white shelter



He goes on to explain this rather outrageous claim, which I’ll reprint in full:


“Top engines, of course, completely misunderstand and misplay the variation. Most of them will still assess above position as very favourable for white, but of course, black is winning. As the associated lines are very deep, engines basically see nothing and rely on their

positional evaluation, which is far from perfect and, in many cases, like this one, rudimentary.

Winning is pretty much straightforward: black continues with slow attack on the king side, pushing pawns there, and gradually transferring pieces to this focal point, including the ones on the queen side. As the position largely carries a closed character, emphasised by the e4

central backwardmaker, black has all the time in the world for regrouping and coordination. White, on the other hand, can do almost nothing, as the white shelter is inflexible, and attempting to break free with f2-f3 or f2-f4 will easily backfire, creating multiple weaknesses.


Of course, in a practical chess game, matters are far from clear. But objectively…? Honestly, I don’t know. I’d need to hear the opinions of correspondence and freestyle chess experts before I’m convinced. But still, I like hearing the way Tsvetkov thinks about these positions, mainly because it’s a new way of evaluation that I haven’t encountered before. And I’m all for diversity.


Here are some other specific examples that I’m sure will have many grandmasters scratching their heads:



One of the key insights from The Secret of Chess is the need for flexibility in one’s pawn structure. The diagram is an example of this, for which the author writes:

“In spite of the enormous lead in development and massive centre, white is actually a bit worse… Fact is, white’s pawns are quite broken down in different very small groups, while black has a great number of interconnecting pawns. Look at the h6-g6-f7-e7-d6-c6-b5-a5 weaving snake!


It seems hard to believe that Black could be anything but worse here – White has the centre, more space, better development… But on the other hand, it’s true that Black’s position is tough to crack, and after further thinking, I couldn’t find a convincing plan for White to gain a clear advantage. I still have my doubts that Black is better, but at least Tsvetkov’s principle of pawn flexibility seems plausible to me.


Tsvetkov’s definitely not afraid of making bold statements about how a game will finish from a very early stage. He often writes that “Of course Black is lost here…” at a point where material is equal and there are no clear tactics or attacks at play. Here are two nice examples:



I don’t know how I would have evaluated this position if I got it in a game – probably I would have thought White was doing quite okay. I certainly wouldn’t have guessed that White is lost! But Tsvetkov writes:


“Black has already won the game, because of the white twice backward shelter f2

pawn…Black should get its dark square bishop to f6, sacrifice it on h4 for 2 enemy pawns, later transfer a knight via h7 to g5 and f3, with smashing attack. If necessary, both rooks could be enrolled in the approaching army to support the assault, by taking long-range aim along the h and g files.


Compare the previous position to this one (I have flipped the colours for ease of comparison):



“White will win this at some point, although this is not currently easily recognisable.

The reason is precisely the complete lack of a pawn shelter for the black king (with

the f5,g4 and h5 pawns all advanced), while its white counterpart still enjoys the immediate contact of 2 own shelter pawns, g3 and f2. It might take 30, 40 and even 50 moves, but at some point, the position will be opened, the white pieces will penetrate and mate the black king. The black king does not have any pawn shelter on its current place, the king side, as well as in the center, while walking to the queen side is simply impossible because of impending attacks.


It’s so hard for me with my classical chess training to believe that this position is already decisively won for White, while the previous one is lost. I’m still not sure that I believe it. And yet, as with most of the contentious claims in the book, these evaluations are backed up by Tsvetkov’s surprisingly robust theory of chess evaluation. Coupled with a second book of 100 annotated victories by the author over chess engines, we can get a sense for where the book’s strengths lie: Closed positions. Indeed, I get the impression that Tsvetkov’s approach works quite well in extremely blocked structures, and I suppose one could tailor an opening repertoire to maximise the likelihood of achieving said positions (Tsvetkov’s opening choices against Stockfish and Komodo would be a good place to start). Given his success both in improving and beating chess engines, I feel like it would be unwise to ignore his lessons on how to evaluate closed structures, and it would not surprise me if computers tell us exactly the same thing in ten or fifteen years’ time.


And this goes to the heart of the issue. Whether or not you believe in Tsvetkov’s chess philosophy or even just his evaluations, there’s no question that his approach to chess is fresh and different, something that’s been missing in the chess literature for a long time. I probably won’t end up a convert, but I have definitely spotted several interesting new heuristics that I will be trying out in the future. Concepts such as “vertically isolated pawns”, “twice backward pawns” and “spearhead pawns” are not things that I consciously think about when I analyse, though in a sense they sit somewhere in my chess intuition for assessment. But knowing which of these heuristics are relatively more important than others – a feature that Tsvetkov’s quantifications can address – as well as automatically bringing them into one’s decision processes, might be quite valuable. In any case, I’m going to try it out.


Unfortunately, the combination of the textbook style without much in the way of descriptions, combined with difficult English, makes The Secret of Chess a really hard read. And given the knee-jerk rejection that many ‘classical’ chess players will feel, there’s a fair chance this book will be largely ignored by the wider chess community. But I sincerely hope this doesn’t happen. I’m almost surely in the minority, but I believe Tsvetkov’s insights could really change the way we think about chess, from how beginners learn the game to how experts improve. It’s bold, completely different and sometimes conflicts with a lot of established chess wisdom, but, just like big data analysis, meditation and veganism, that doesn’t mean there aren’t some lessons to be learned, even if you don’t subscribe to the whole package. If you’re willing to open your mind to a new way of thinking about chess, and you’re determined enough to power through the text, this book is definitely worth a read.


Tsvetkov’s The Secret of Chess is available from Amazon in both Kindle ($5.96) and paperback ($25.99) editions.

Buy from Amazon


A swindle that never was

Posted by David Smerdon on Sep 19, 2017 in Chess

I’ve started collecting chess swindles for a new book [so if you have any good ones, please send them to me!]. Over the weekend, I visited a great little weekender on the Gold Coast and saw first-hand a fantastic swindle take place – or, rather, nearly take place.

Liu-Wohl was played on board 2 in the penultimate round, an enthralling clash between coach and former pupil. Wohl, an IM and a bit of a chess legend in Australia, was Black and steadily outplayed the young Liu from a worse endgame to take complete control. But as I watched the tables turn from next to the board, I spotted a really cute swindling motif for White. Liu, a pretty good tactician, had his head in his hands, looking dejected in playing every move as his final seconds ticked down, and I briefly thought he was pulling some sort of theatrical bluff on his older opponent. Alas, the gestures were all legitimate. As I was trying to evaluate the (I assumed) inevitable queen endgame to come, Liu let his clock run down to zero on his 38th move and resigned in the same motion.

Immediately after they shook hands, I asked him why he didn’t continue playing with 38.h7!. I think it was only here that both players realised the game was far from over, and that White has some serious self-stalemate chances: 38…b3?? 39.Rxc3! bxc3 40.g6! is immediately a draw, for example.

Another pretty line is 38…Rb5? 39.Rxc3 (anyway!) 39…bxc3 40.g6! c2 41.gxf7 and there is still no way to avoid the draw.

Wohl suggested (correctly) 38…Rc8!, which is the only try for Black to keep winning chances. I pointed out that White can still continue with 39.g6!

39…Ke7+ (or 39…fxg6 40.Rxc3 Ra8 41.Rc8+ with stalemate to follow) 40.Kg7 fxg6 (else Black even loses) 41.Re2+!

41…Kd6 42.Rf2 Ke6 43.Rf6+ Kd5 44.Rf8!,

forcing a queen endgame. Black has no better than 44…Rxf8 45.Kxf8 c2 46.h8=Q c1=Q,

but White can pick up one of the pawns with 47.Qg8+, leading to a difficult queen endgame that I’m sure Liu would have been very happy to escape to. Even more painfully, tablebases confirm that it’s a theoretical draw.

It was a shame that Liu didn’t find this sequence over the board, although it would have been difficult anyway to hold the queen endgame given the time situation. And (like all swindles?) Wohl probably deserved to win. Still, it will make a nice addition to the book…

(You can replay the variations using the board above.)


How to survive the economics job market

Posted by David Smerdon on Sep 5, 2017 in Economics, Non-chess

As I’ve previously mentioned, last year I went to the economics job market. The job market is an incredible annual event that sees thousands of newly-minted PhDs and young researchers from around the world pitted against each other in a global battle for careers at hundreds of universities, government agencies, international NGOs, banks, start-ups and other multinationals such as Facebook and Microsoft. It’s huge. It’s stressful. And, for a young economist about to leave the safety of the student nest, it’s incredibly confusing.

One of the things that really struck me on the market is that not every candidate is on an equal footing when it comes to understanding the process. I found myself playing catch-up once the market opened, whereas for some of my (largely US-based) peers, their universities start training them for years before they were even applying.

So I’ve put together some tips for surviving the market for this and future year’s candidates, based on my experiences. There are plenty of very good advice articles online, especially:

These articles are invaluable, not least to help ease the stress of what can be an especially trying experience for a young researcher. To these, I’m adding some advice from my recent experience as a Europe-based applicant. I’ll be giving a seminar to prospective job-market candidates from my alma mater on Wednesday, and I’ve expanded the presentation so that the slides can stand alone. Hopefully some readers find them useful. Comments/suggestions are very welcome.

(Note: If your browser doesn’t let you see the embedded pdf, there’s a download link below.)

Download (PDF, Unknown)

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Charlie Changes Everything

Posted by David Smerdon on Sep 1, 2017 in Non-chess

I don’t know how I ended up becoming a chess book reviewer in my spare time, but it’s certainly a fun hobby. It’s gotten to the point that every now and then, I randomly receive a new chess book in the mail to take a look at – which, as any chess addict can appreciate, is awesome. And then, just recently, I got this letter:

“Dear Dr Smerdon,

I’m a big fan of your blog and noticed that you like reviewing things every now and then. So just on spec I’m sending you a free copy of my novel. It’s meant to be a funny book to make you think so I reckon you’ll enjoy it.

Yours sincerely,

Robert Cregan”

Enclosed was a thin novel with an intriguing title: Charlie Changes Everything.

Usually I don’t have time to read novels, but several aspects of this random gift were appealing. First, I like getting free stuff. Second, this is the first time anyone’s ever addressed me as “Dr” in a letter, and my ego is easily stoked. Third, the lingo in the letter strongly hinted at an Australian background (a fact soon confirmed). Fourth, it’s a kids’ book, and I hadn’t read one of those in ages. And fifth, the cover has a pretty picture with a rainbow on it. And who doesn’t like rainbows?

It was a really nice letter to receive. And reading the author’s motivations for this labour of love was also quite interesting:

My daughter wanted a story and it got me thinking about all the things I should’ve learned when I was growing up. I thought about the values and ideas I wanted to teach my children and this is the story I told her: a funny book for kids to help make their world a better place…

So, I read it. And then I gave it to my wife, and she read it. And guess what? It’s pretty cool.

I’ve got no experience at reviewing novels at all, but here goes. There’s Billy, who’s having a tough time in primary school because his teacher’s a super mean lady, and the girl he’s got a crush on doesn’t notice him. We can all associate with that. Then along comes Charlie, a renegade orphan with the sophistication and savviness of a British secret serviceman. Then there’s a war with the rival school, forbidden romances between the teaching staff, and a twisted web of intrigue in the ensuing battle between children and adults, culminating in a predictable yet delicious twist. Ta-dum.

Ok, summarising the plot wasn’t so hard. But more importantly, Robert did a great job at setting out to do what he intended. Not only is it a very nice, smooth read, but the values imbedded throughout the book are subtle enough not to overpower the story but strong enough to leave a clear message. And these aren’t just sugary meanings of the Aesop’s Tales garden variety, mind you. Climate change, religion, gender roles, child-rearing and the politics of war and conflict all see some light as both children and adult characters learn their respective lessons. All for just a couple of bucks for the Kindle edition. I don’t know what else to say about the book other than to say that I’d be very happy for my (future) children to read it. That’s a pretty good recommendation, right?


Perverse incentives

Posted by David Smerdon on Aug 12, 2017 in Economics, Non-chess

One of the cool things about studying economics is that it teaches a new and exciting way of thinking about things. This means we can look at all sorts of topics in a whole new light, spot problems that we never knew were even there, and come up with efficient solutions. And THAT means every now and then we come across an everyday, routine situation and say, “Err, what?”

This has happened to me a few times recently, all related to the problem of incentivesOne of the neat areas in the economist’s toolkit is contract theory, which came to public prominence last year when two of its champions were awarded the Nobel prize. Contracts and incentives govern most of the relationships in our everyday lives, both formal (such as with our employer, our bank, the government…) and informal (neighbours, strangers, and of course, partners). And it’s absolutely critical to get the incentives right. Normally, they’ve sorted themselves out over the years, either through social norms or legal obligations. But every now and then, we come across situations where the incentives don’t align with the situation.

One example from earlier this week was when I was investigating customs clearance when moving back to Australia. Shipped goods are inspected by customs officials, and – if they decide the goods don’t meet the test – they can charge you for treatment or destruction of your property. That is, the officials, and only the officials, get to decide whether or not you have to pay them more money. Now in this case, we could assume (probably correctly) that the officials are acting as unbiased members of a government organisation in which there’s no corruption going on, and so the inspection decisions are made on the merits alone. But part of designing good contracts is reducing the potential risks of corruption developing in the future, and here the incentives don’t really line up.

Not that this will affect my shipping decisions. But fast-forward to yesterday when I started investigating buyer’s agents, a whole industry I previously didn’t even know existed. Basically, real estate agents are employed by would-be home buyers to search for property on their behalf, negotiate the price and execute the sale. Sounds good in principle, especially for the busy worker who doesn’t have the time or know-how to search themselves. But the fee structure is truly baffling. Buyer’s agents charge a (quite sizeable) percentage of the sale price – say, 3% of the final amount you pay for the house. That means when they’re searching for property and negotiating with the seller, they make more money if they get a worse deal for you. The incentives are almost exactly aligned in the wrong direction. How does this possibly make sense?!

Granted, I’m new to this field, but the more I’ve searched online the surer I am that the incentive system in this industry is really perverse (to use the economic term). So then I started to think about what sort of contract would actually align the incentives of agent and buyer. There are a couple of better alternatives to the status quo, though it turns out this problem is not as simple as it appears.

A fixed-fee model is the easiest, and a minority of agents do use this. But this means there aren’t any monetary incentives for the agent to really work hard to get you the best deal. (There are some reputational benefits of course, but that’s another story.) For the buyer who’s risk-averse and just wants to avoid getting screwed over, however, let’s see if we can do better. First, the agent searches for properties within the buyer’s strict criteria (price range, location, size etc). Then, when the buyer has agreed on one she likes, she agrees that she will pay in total the listed property price. The agent then gets paid whatever amount lower than the asking price the agent can negotiate. E.g. imagine the listed price is $500,000 and the agent negotiates it down to $490,000. The buyer pays $490,000 to the seller and $10,000 to the agent. The point is that the buyer knows exactly what her total cost will be before the negotiation takes place, reducing the uncertainly, as well as reducing the risks for the agent to act against the buyer’s interests.

It’s not a perfect solution, though. This contract might influence the agent’s selection of properties to present to the buyer; maybe we’ll only get to see properties that the agent thinks are overpriced (and therefore easily negotiated downwards). Can we do better?

The solution I came up with is complicated, but we can outsource most of it to a computer (in theory, anyway). First, the buyer comes up with a list of strict criteria for the perfect property. E.g. up to $700,000, within 4km of the office, near to parks and schools, at least 3 bedrooms, living space of at least 150 square metres, blah blah. Then there’s a second list of “optional extras” that the buyer likes: a garden would be nice, a pool would be amazing, more than one bathroom or more than one car park sounds good, open-plan kitchen, close to cafes, possible to ride a bike to work, and more blah blah. We feed our strict and desired preferences into our fancy computer software, which spits out a score function. Then, every potential home, for a given price, is given a score. If a house just meets the bare minimum criteria with no optional extras, the score is 0, and the agent gets a minimal flat fee. For every point higher in the score, the agent gets paid more. E.g. if the price is negotiated down to $5,000 less than our maximum price, the score goes up, the agent gets paid an extra $2,000, and everybody’s happy. If the location is closer to the office, the score goes up, proportional to the distance or travel time. Extra bedroom? Score goes up. Outdoor pool? You beauty!

The nicer the property and the better the deal is to the buyer, the more the agent earns. The key point is: it’s in the agent’s interests to try harder for the buyer. Incentives are aligned. Everybody wins.

So… Anyone know a good programmer?


All boxed up

Posted by David Smerdon on Aug 1, 2017 in Chess

When you play often enough on an online chess server, you start to see the same usernames popping up as your opponents. It makes for a weird social network. I recall a story where some Australian chess players met the famous Hikaru Nakamura at a tournament. Among them was a shy, timid junior called Moulthun Ly. At the introductions, Hikaru said something along the lines of “Moulthun… like “Molton”, from ICC?” The two had played literally hundreds of blitz and bullet games against each other online, and that sense of respect was transported from the virtual world to the ‘flesh’ (mainly because Moulthun had won quite a few of the games, I suspect).

In the last month I have played 60 games against user “ukchessbomber” on chess.com’s server. We’ve never chatted and I don’t know anything about this person, other than that they play from Wales and their opening repertoire needs a bit of work. Still, after so many games, one can get a strange sense of camaraderie. And now after one more game, I know one more thing: They’re a good sport, allowing me to play through to checkmate in one of the weirdest games I’ve ever been a part of. Black’s queenside pieces are literally boxed into submission, falling over each other in complete uselessness. On Facebook, I called it my “Trump administration” game, but without the political commentary, something like a ‘pieces in a box’ game would be more appropriate.

After 17…a6?? 18.a5!, believe it or not, Black can resign. I guess soon afterwards he or she realised the self-immobilisation. 25.Re8+ was admittedly cheeky, but I couldn’t resist. Ironically, chess.com’s computer analysis tool calls this move “Blunder! Black is winning”, with an evaluation of -4.9.


PS – My opponent’s sportsmanship was rewarded; he beat me soon afterwards.


The strangest dream

Posted by David Smerdon on Jul 29, 2017 in Non-chess

I’m a dreamer. Literally; I dream almost every night, and I recall them vividly. They are often bizarrely creative, including the odd chess dream, though occasionally, during stressful work periods, more boring topics sneak in.

But last night’s has left me with goosebumps all day. It was a hot, moonless night in Milan. I remember waking up during the night to some sounds in our courtyard. My clock said 3.00 am, and there was a cool breeze blowing through my bedroom window. I fell back asleep.

We’re in the jungle. I’m driving a roofless military jeep, frantically, along a dirt path – we’re being chased. My uncle’s in the passenger seat, and my two best friends are in the back. They’re yelling at me to go faster to escape the unknown assailants. Branches crash into the windscreen as I weave and dodge, desperately trying to keep the vehicle straight. I briefly glance up at the dirty rear-view mirror; there are black sedans chasing, but the windows are heavily tinted. I yank the steering wheel hard to the right and we skid on the dirt and fishtail into some sort of rocky opening, a cave. The cave extends deep into a network of tunnels. I can barely see ten metres ahead through the darkness, but we keep careening on, wheels screeching. The sedans follow. The tunnel keeps branching and I randomly take lefts and rights, trying to lose our pursuers. The tunnel floor seems to be sloping upwards. My friends yell at me to keep going; I floor the accelerator, and now there is a definite incline; we’re going up and up, but I still can’t see anything.

Now it’s very steep, and I can’t see anything in front or behind, and as we fly forwards, I’m sitting almost horizontal in my seat, like at the start of a roller-coaster, but faster. Suddenly, we burst out of the tunnel into daylight, and we’re way up in the open air, on some sort of massive, elevated road suspended miles above ground. We’re at the height of a plane when it levels off. The road’s narrow, just about the width of our jeep, just a strip that goes up and down with no supports, and we’re speeding along it. I can see houses like dots below us. My friends in the back yell that we’ve lost the cars behind us, and my uncle shouts at me to slow down, but I can’t – the accelerator is stuck, and the break’s not working. The car’s speeding up and we’re rocketing at top speed, and I’m desperately trying to keep the wheels within the narrow edges of the track, but it’s an impossible task, and now everyone’s screaming at me, and suddenly I realise that it’s inevitable, there’s no other way for this to end.

The front-left tyre slips over the edge and the jeep jolts violently to the left, and my friends in the back are thrown clear into the abyss. Then the whole jeep tilts over and falls, front-first, and I’m looking through the windscreen straight down as we start hurtling towards the ground. I can see my friends below us; they’re falling back-first and I’m staring into their faces. They have their mouths open, screaming, but I can’t hear them, only the whistling of the wind. And the ground’s coming so fast, and all I can wonder is whether I’ll die instantly, or if not, whether I’ll be in pain, even for a second, and I find myself wishing just that there’s no pain, please, let there be no pain. And my uncle’s still next to me, and we’re floating next to each other now, like two sky-divers, and he looks over and says, so calmly and so clearly:

“With the world’s collapse – the brief slowness of time.”

As his last word hangs in the air, I stretch my arms out above my head and I smash into the roof of a house, spread-eagled like a pancake, and everything goes black. For half a second I’m aware that I’m still alive, but dying, and then my vision goes blindingly white, and I feel an incredible numbness in my outstretched arms. As I start to lose consciousness, I feel my shoulders start to tingle, then my biceps, and then my forearms as the spears of pain move their way down to my hands and fingertips, until my whole arms are tingling, burning, and I can’t think anymore. And as I finally slip away from life, I hear a computerised, female voice echoing a single word in the distance: “Reboot”.

I woke up in my bed, lying flat on my stomach, arms outstretched above my head, with pins and needles all the way to my fingertips. I looked up at the clock; it was 3.00 am. There was a cool breeze blowing through my window.


Chess, age and Roger Federer

Posted by David Smerdon on Jul 22, 2017 in Chess, Economics

In the provocatively titled “Can Anand Be The Federer Of Chess?“, Chess.com’s Mike Klein brings up the question of whether chess players can really keep performing at the top level as they age. Proponents of this view typically note that chess is not subject to intense physical stresses, that it depends a lot more on past experience than other competitive sports do, and typically end curtly with “Korchnoi.”

All plausible arguments. On the other hand, opponents like to point out that scientists typically ‘peak’ before they turn 30, judging by the age when the key work for Nobel prizes was conducted (though this age may be increasing). This is supported by a famous Einstein quip:

“A person who has not made his great contribution to science before the age of thirty will never do so.”

All well and good, but it’s perhaps not fair to compare chess to either physical sports or science, as our passion only partly overlaps with either comparison. It’s probably better to look at how chess rankings and ages have changed over time. And here, there’s undeniably been a trend towards the world’s elite becoming younger. Hardly surprising, really, given the exponential increase in availability of chess materials and resources. The more easily dispensable chess knowledge is younger players, the less older players can rely on their experience to their advantage. And that’s the key point: If younger players can more easily (and quickly) pick up the knowledge that took older players years to acquire, then the days of chess veterans dominating the charts are numbered.

A quick aside: Of the world’s top 15 as of the time of writing,  only two are over 40: Former World Champions Vladmir Kramnik and Vishy Anand. Is it a surprise that Kramnik is known as a meticulous opening preparer and innovator, while Anand was one of the very first professional chess players to use computers for chess training? Of the remaining 13 players, three are in their 30s, nine are in their 20s, and the future World Champion Wei Yi is still old enough to play in junior events…

There’s a reason I highlighted some special characteristics about Kramnik and Anand. Statistics that look at the average rating of different age cohorts often make a fundamental error that econometricians like to call ‘selection bias’. The players who drop out of professional chess as they get older are not random, but instead are exactly the types who are ‘feeling their age’ with regard to their chess performance. So when we look at the average of older players who are still competing, we’ll actually be calculating the average of the better players, so we’ll always think age is having less of an effect than it actually is.

This seems like a pretty basic thing to keep in mind, but it’s shocking how often this mistake is made in research. Anyway, some economists have recently shown that once we take care of this bias, the results show that chess players’ performance indeed decreases steadily as we get older. Moreover, this decline happens much earlier than we used to think. They found that the average peak age for chess performance is a remarkably young 21.6 years, with a median around 24 years. One of the most remarkable findings from their study is that the average chess player’s level at 40 will be similar to when he or she was 15 (obviously, this assumes the player was already playing tournaments at 15). I find this very hard to believe from an intuitive standpoint, and I haven’t yet had time to go through their paper in close detail. But from a quick read, it seems like the results are solid.

“Seriously, show some respect.”

As an ageing player myself, I should find this depressing (especially to think that in eight years time, I’ll get beaten by my 15 year old self). But taking a step back, the age we live in is the most exciting of all time to be a chess lover, as I explained in a recent interview. The exponential increase in chess knowledge, playing opportunities and tournament coverage (all thanks to computers) has brought the joy of the game to hundreds of millions. And if that means I have to get beaten up by a couple of kids every now and then, do I really have a right to complain?

Then again, back in my day…


Just winging it

Posted by David Smerdon on Jul 12, 2017 in Chess

These days, the extent of my chess career seems to be the odd blitz game on the net during my lunch break. It’s more virtual escapism than serious training of course, but I get to try out some fun openings. One I’ve been enjoying a lot lately is the Wing Gambit, considered dubious at best (and at worst, complete junk) by almost all strong players. It goes 1.e4 c5 2.b4!?, although White can also use it against the French Defence by playing 1.e4 e6 2.Nf3 d5 3.e5 c5 4.b4!?. I’m kind of addicted to it – it’s like the white version of my audacious Scandinavian –  and every now and then, I play a cool game.

In a game from today, I decided on sacrificial symmetry, giving up first the b-pawn and then the g-pawn to open lines. Black probably had to be brave and try 13…Bxc1!, when it’s really on. Later, there were some cute mates, such as 28…Rg8 29.R(either)f7+!, and after 28…a3? 29.Nxe8! there was 29…Rxe8 30.Ref7#. Instead,  28…Bh5! would have kept the game alive, after which I don’t know what the plan was. Just wing it, I guess.




Why I didn’t write

Posted by David Smerdon on Jun 19, 2017 in Economics, Non-chess

I didn’t plan to stop writing. It just sort of happened; I had a lot of fires to put out in my work, and they kept coming, and after a while it all became too easy to forget about this site. I feel a bit guilty – it was seven years of regular writing without a break – but there you have it.

The main reason for the break – the biggest ‘fire’ – was the job market for economists. The job market is really an amazing concept that only economists could think is a good idea. This is a heavily centralised process that allows (or forces) thousands of newly-minted PhD graduates and other junior academics from every country to compete for hundreds of economist jobs around the world. The astute visitor to this site (if I still have any) may have noticed the ‘Economics’ tab in the website header, which directs to my professional site – an essential for the job market. Besides the regular details that you’d expect on a professional site, it also features a cheesy video CV that was surprisingly popular with potential employers. Filming and directing credits to Sabina, naturally…



The main event in the job market is the annual American Economic Association meeting, which for candidates is basically a massive stress-fest with a lifetime’s worth of interviews crammed into a couple of days. I must admit, there was a moment in early January, where I was literally running on the ice-covered streets of Chicago in my suit, sweating little icicles in -20 degrees C with the icy Lake Michigan wind in my face, desperately trying to make my fifth interview for the day on time, and looking up at the giant, menacing letters on Trump Tower… when I began to wonder if it was all worth it. (My interviewers were also late.)

Almost all economists interested in the world of academia will have to go through this baptism of fire once in their lives. For me, despite my job in Milan and finishing my thesis in Amsterdam, the market proved to be a full-time occupation from November to February. To survive, I had to make sacrifices: chess tournaments (including online!), book reviews, commentary and banter blitz, weekends, Christmas… and blogging. There was light at the end of the tunnel, though. At the end of the wash, I found an exciting position at the University of Queensland, back in my home city, which I’ll begin later this year.

I have a lot more to say about the job market, but I’ll save that for a later (but not too much later!) post. In particular, a lot of PhD students in economics really don’t have a good feel for what the market entails, let alone how best to prepare for it, so I’m going to try and provide some advice. Even though November is still a few months away, early preparation is key – something that I wish I’d known a year ago.

But for now, and particularly for those outside the strange world of academia, I can highly recommend this entertaining description of the job market that pretty much sums it up: Speed Dating for Economists.

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