Awonder Liang on Chess, Statistics, AI and the Pursuit of Small Gains

Interview with Awonder Liang

Awonder Liang explores how his background in behavioral economics and statistics informs his approach to variance, rating optimization, and the "Lucas critique" in online chess, while admitting his own struggle between over-analyzing strategy and simply playing the game. The conversation also covers his admiration for the "gambler mentality" of players like Gukesh and Arjun, his pragmatic use of AI engines as accelerators rather than crutches, and his cyclical belief that he performs best in even-numbered years!

Interview by Jonathan from Underpromoted.

Johnathan (J): Let’s talk about your current status as a player. You’ve said that a lot of your chess progress simply came from doing what you enjoyed. But as you get further into the elite, do you think you’ll have to sacrifice more things or work on things that don’t come as naturally?
Awonder Liang (AL): I don’t think I’m really at the level where I need to sacrifice so much. Right now, I’m #25 in the world or thereabouts, not really a super high level. Also, the rating doesn’t reflect much; I haven’t really won or even competed in many major events. I spend a lot of time on chess and I work a reasonable amount, but it’s not on the level of the other top players, like the Indian players or the Uzbek players. Maybe that’s a bit of a problem because they’re probably more talented than me, and also they’re working a lot more than me, and they have teams and so on. So probably it’s not a good sign for the overall development of my chess career.

Around the low 2700s, my general estimation is that, it sounds strange to say, but it’s generally not a very high level of chess. There are huge gains to be made just by doing the fundamentals and learning the basics.

-Awonder Liang.

Things generally are going pretty well right now. I’m learning a lot more things that I don’t know about chess. The way I view it is, I spent a lot of time in college and I wasn’t doing chess full-time; I was doing a little bit on the side. Just by doing the stuff I enjoy, I’m already learning a lot of the things that I didn’t know about chess. The last couple percent that we’re trying to eke out at the higher levels, maybe you have to start doing things that are more laborious or tedious. But I don’t think I’m at that level yet. I just keep doing what I like, and maybe not working as hard as I should.

For me right now, around the low 2700s, my general estimation is that it sounds strange to say, but it’s generally not a very high level of chess. There are huge gains to be made just by doing the fundamentals and learning the basics. So it’s mostly about staying consistent and getting the basics down at a pretty high level. Then from there on, it’s like a Pareto-type distribution, so the work gets exponentially harder to climb up. So do the rewards. It’s sort of linear in log-log space.

J: There’s that guideline that you can get 80% of the results with 20% of the effort. Where do you feel like you are, in terms of amount of work for amount of output?
AL: That’s hard to say, because I actually don’t know where I am yet. It hasn’t really gone downhill at any point. In the past year and a half, I’ve started playing more chess and taking it a little more seriously, and it’s felt like I’ve worked more and then the results have naturally been coming. 2024 was when I started seeing huge gains in the summer. But that was a strange year for me in general, because things were just running really well for me. So I think it was a bit of luck too. Last year, in 2025, it was a lot more up and down.

But in general, I had an impression that if I was doing more work, the results were just coming. Not with any particular difficulty, like it was sometimes down, but normally it was because I wasn’t putting in enough work. Technically, almost every month I’m at my peak rating. It’s not really been slowing down for a while. Sometimes internally I feel like this is difficult and I’m working a lot and it’s very tiring. But I’ve never really felt unmotivated. So it’s hard to conclude, “Okay, now is the time to start locking in more and let’s do all these other things that the top players are doing”, “Let’s hire a mental coach”, and this and that. No, I don’t feel that way yet. I guess we’ll have to see how the next couple of years play out, right?

J: You mentioned that, as a player in the low 2700s, there are still obvious ways you can improve. Can you talk more about that?
AL: If you look at it strictly from an Elo perspective, basically, every 50 points of Elo is roughly a 5% difference in expected value. That means in the course of a 9-round tournament, a 2750 player is only expected to score half a point more, right? There’s an element where I’m looking at my tournaments, and let’s say in this tournament, I’m blowing 4 half points. On average, if I just collect one extra of those, that’s already 2750 strength. It’s this interesting problem where it’s actually a very small difference, but it’s enormously difficult to cross that bridge.

But the other thing I would say is that humans in general, we’re pretty bad at most things. Being right, or being good at things, is very difficult. So I’m really trying to eke out the small 5% to, let’s say, cross into the top 10. When I look at it from that aspect, there are so many specific games where I didn’t prepare well or wasn’t sleeping well, and that might have messed things up. There are so many games where I miss this tactic, so if I practiced tactics more, maybe I would have collected this extra half point. When it comes to my past year in 2025, probably there were at least 10 or 15 half points which were extremely obvious. Like I make 1 different move or 2 different moves, and I already get it there.

I’m just looking for 1 extra half point every 10 games. Which is funny because when you frame it that way, it sounds like very little. On the other hand, that’s the entire goal of what everyone is trying to achieve.

- Awonder Liang

That’s not to say that it’s easy to do, because if it was easy to do, then probably other people would have already done it. But it’s the sense that there are a lot of opportunities around. Part of what I’m trying to do is pick up a little more of those. It doesn’t even have to be every single one, right? I’m just looking for 1 extra half point every 10 games. Which is funny because when you frame it that way, it sounds like very little. On the other hand, that’s the entire goal of what everyone is trying to achieve.

In that sense, there are a lot of basic things that I can do to get those things. Like in certain games, I might not have prepared the opening; I forgot my line. So I would just review, and then if I didn’t forget that line, I wouldn’t have lost that half point. It’s when you get to the more elite levels; what I noticed from the top players is they’re a lot more disciplined, they’re a lot more physically fit. There’s a lot less of that low-hanging fruit of “I just forgot my opening line and bam, I lost the game because of that”. What they’re working on is a little different from what I’m working on, I’d say.

J: What did you study in college?
AL: I did economics and, I say applied math, but it’s some long major like “computational and applied math”.

J: The way you talk about chess has a lot of those concepts. Like elite players having less variance in their performance. Or in improvement, it’s like you want the compounding effect of these little gains. Do you feel like that’s a common way for chess players to think?
AL: It’s hard to tell. Let’s say, I know Hikaru is actively trading specific tickers in the market. So he understands these concepts at a very intrinsic level. Also, a lot of chess players like playing poker, so you get a feel of variance at an intuitive level. I’m not sure if they think this way, but one thing I notice about a lot of the young, successful players, for instance, is that they have a tendency to get very hot at certain times, and they know and understand that they’re hot, so they go extremely hard when they are. I think this is a classic; it’s a very good habit. Because you can have a string of extremely good results and they feel the momentum. It’s not clear to me if that’s something they intuitively do, or if they understand that this is a good principle.

But I noticed, like Aravindh, when he was making the climb to 2750 (he’s dropped a little bit since then), he was playing nonstop, right? Like back-to-back-to-back tournaments. Keymer also went extremely nuclear at the end of 2025 and climbed to 2770. So you see these elements of, “Okay, we understand that this is a game and we’re trying to maximize our expected value.” I think a lot of chess players that are successful, if they don’t consciously think this way, they do act in that way. And part of what makes chess interesting is that it’s mimetic. We look at how other successful players rose to the top, and then we try to emulate what they did. So it spreads throughout.

To the extent that they consciously think, “Okay, if I play this opening, I have X percent better chance of winning”; that’s probably not how they calculate those things. But you don’t need to have a super rigorous understanding to apply in the real world. I feel like a lot of the young players understand these concepts and they’re able to apply them very well.

On the other hand, for me, sometimes I’m trying too much to do the meta thinking of what will be successful and what will work. Sometimes I forget to play the actual game (“Let’s actually calculate some lines”) and not just think strategically (“Maybe if I play this opening at this point in the tournament, I’ll have a better chance of winning”). I tend to veer too much into trying to optimize that thing, and I forget, “Oh, I just hung my rook,” and then I don’t think that much thinking will save you. At the end of the day, most players are pretty focused on the chess. But I think they do think about these things.

J: Borrowing from behavioral economics, the assumption that we can apply these principles or statistics rationally is not always good. A lot of times, what people end up doing is actually against the odds. Do you think that happens in chess?
AL: I don’t think so. Maybe insofar as sometimes when I see people make decisions, they make what I feel are poor decisions. But they would still be better players than me, so it’s hard for me to criticize. One example of a player that is very good at decision-making is Hikaru. I think he’s playing extremely close to Nash, given his skill set. Other players, in certain positions or even overall, could be playing better than him. But he tends to choose positions which he plays very well, and also he understands psychology very well. So he’s choosing the right type of game against the right type of opponent.

I think other players are more focused on chess. They just try to look for the right opening idea. If I find an opening idea, I think very much about whether I’d like to play it against a specific opponent. And I think other players, if it just shows up on the board, they’re willing to play against anybody. That’s the interesting part about chess, right? Not everyone’s the same, and we all have different styles. There’s always, for me, this feeling that maybe other players are not optimizing enough.

But it’s hard to say. I don’t really focus that much on it because, at the end of the day, I’m the person that knows me the best. I’m trying to do what’s best for me in this scenario. And other people also know themselves the best, right? It’s hard for me to claim that I understand, let’s say, Arjun better than he understands himself. It’s probably not true. I told a friend recently that, if I were Arjun, I would never play Wijk aan Zee again. Because he would already be 2840 or something without this one tournament. But the thing is, every year he starts off by losing 20 Elo. But he’s a better player than me. He gets more experience from these tournaments. Maybe it makes him a better player in the long run, right? So, it’s very difficult to say. Statistically, he’s performed so badly there, aside from 2022 when he won the Challengers, that it doesn’t make sense to play. But everyone has different goals. Everyone understands things differently. It’s difficult to separate those things.

J: Before moving on, could you elaborate on what you were saying about Hikaru, dominant strategy, and Nash equilibrium?
AL: We have this concept that in finite games, of which chess is one, there exist best strategies that can’t be beaten or exploited. How I intuit that is, given an opponent, if I know exactly what you’re going to do, I can’t beat you in the long run. Now chess is interesting because everyone is different; they have different skill sets. So what does that mean, exactly? How I take it is, given Hikaru’s skill set, he’s very difficult to exploit. It’s very hard to get him into positions that he’s uncomfortable in. And he’s very good at exploiting other people’s weaknesses, is what I noticed.

A lot of players that come from a more traditional backdrop, they criticize Hikaru for not playing the elite competition, or this and that. But I think he has a lot of skills that other people don’t have, for instance, playing tricky moves when your opponent is under time pressure. That’s not something you would ever see in Dvoretsky’s manual, right? So maybe he’s not so good at solving these puzzles, but he’s collecting tons of half points because he’s making tricky moves under his opponent’s time pressure.

Most top players, I don’t think, would train that skill. But from playing so much, he’s vastly better than everyone else at that. Other players, for instance, just yesterday in Wijk aan Zee, Blubaum had a +6 position and his opponent had 4 minutes against his 30, and he drew that position. You would never imagine a player like Hikaru fumbling that opportunity. So I think there are these small skills, like managing your time, playing well under your opponent’s time pressure, choosing your openings well, that he does extremely well, and it makes him very difficult to exploit.

We all have different approaches to the game. Many people think of Gukesh as a very calculating player. Or Arjun is like this gambler, right? It makes it very interesting. The more I get into it, even though I’m very new to playing chess professionally (I don’t know if I really am, honestly), I have a lot of respect for different people’s styles and how they interface with each other. Possibly, as the development of chess goes on, certain styles get stronger and certain get weaker, just because the types of players in the pool are constantly changing.

J: It’s interesting, about Hikaru. One thing he does is these speedruns where he sacrifices his queen, basically playing like LeelaQueenOdds against all these opponents, trying to find the most resilient defense, how to trick people.
AL: What I try to do is look at all the players and recognize they’ve gotten to that level, which is of course far above mine, and try and understand, maybe there’s something interesting there, right? Rather than working from first principles, I work from the result and then construct some principles out of that. Which is not how people like to do rigorous philosophical work. But seeing, “Here are the good players and what they do, and what skills they naturally acquire coming out of that”.

J: You had a Substack post that was pretty mathematically-oriented. What was the motivation for writing that?
AL: So there’s been a lot of discussion about streaks, recently, by various people. At some point, some academic people jumped ship on that. What they were analyzing was the probability of a certain streak, given your opponent set. The main method they used was this Monte Carlo analysis. There are certain probabilities that we know how to compute their actual expressions exactly. And then certain problems are complicated, and it’s not easy to get these exact expressions to use. So they simulate it and get an approximate answer.

Part of what I noticed (for a couple of years already, but was too lazy to ever write anything) was that you can’t actually say, “Because a certain player plays this other player, this is the probability of winning, drawing, and losing.” Because if I’m a player in the Chess.com rating pool, I can choose my opponent. This is a very classic economics problem that Bob Lucas, who sadly passed away a couple of years ago, at the University of Chicago, posed back in the 70s: the Lucas critique.

Back then, they were discussing a lot of macroeconomic policies; I’m actually not too familiar with this, and they were taking a lot of these factors as fixed, like growth, money supply, or money printing. And Lucas says, “Wait a minute. All the people in your economy, if you change some of the parameters, they’re going to change their behaviors.” You can’t assume people’s behaviors are fixed. You see this everywhere, right? If you pass a new law, then people are going to adjust based on that law. It’s not like you’re going to get the entire nominal effect of that law.

So part of my critique, which I think is pretty obvious for anyone who plays online, was: say that I see a player is slightly overrated, and I like to increase my rating because it gives me happiness. I will challenge the overrated player because I will tend to gain rating from them, even if and this is the key point. I don’t actually know the exact probability, because I can have a sense of what their strength is.

From there it became an interesting problem. You can simulate these rating deviations as random walks on the real number line. There’s a nice technique that we can use in numerical analysis to solve this problem because, again, it’s very difficult to solve certain problems analytically. It wasn’t meant to be a serious academic paper because, first of all, the original problem of streaks in chess is so inconsequential that it doesn’t really deserve a paper. But somehow people managed to generate a couple of papers out of that. My critique was similarly so niche that it didn’t really deserve a paper, but I thought, I’ll just write a simple blog.

There’s some interesting mathematical result. There’s a classic problem: say you’re walking on an integer number line and you’re stepping up and down with equal probability; sorry, I’m getting very into the weeds. This is used, classically, to prove that if you’re gambling in a casino and you keep gambling, not just with high probability, but actually with certain probability, you’ll eventually go bankrupt. It’s a very famous problem.

My problem was a little bit different in that the Elo system has this factor where if you get too overrated, you get pulled back down to your true strength. So the mathematics works out a little bit differently. It’s a different flavor from what I learned in my undergrad days, so it was interesting to tackle. I don’t think it’s new to the literature, but it was new to me.

It also helps me to think, intuitively, what natural deviations or swings would we see for players in the rating system? There are a lot of good examples of this in the real world. There’s a concept of people who are very easily fooled by essentially random results. They got good luck of the draw, and then they think higher of themselves. In chess, we see that certain players have been on hot streaks. If you look at the long term rating curve, it’s actually pretty hard to distinguish if they’ve been randomly lucky or not.

At least personally, when it comes to my results, I’m always a little bit insecure, even if I’m doing well; maybe I’m just lucky, or maybe I’m not really 2700 strength. So it motivates me to work more because I look at my results and I’m like, [laughs] “Statistically, it’s hard to distinguish this from the null hypothesis.”

J: You’re quite familiar with playing opponents who are weaker than you, from various opens when you were at university. I feel like there’s a consensus that it’s undesirable to play against weaker rated opponents. Do you think that’s true in chess overall? And if so, do you think you’re immune from it?
AL: I think statistically it is true. If you look at a huge sample size, I think 2600s will generally underperform relative to their rating against a 2200. I’m not sure if I’m immune to that. At some point I saw that, statistically, I was outperforming myself at certain, to be honest, almost all rating ranges. I’m generally rating neutral or slightly positive. So I don’t really mind playing those games, of course.

I work a lot and prepare a lot. As long as I generally keep my level high, then it’s a pretty good bet. And to the other point…I play all the tournaments I’m invited to; I’ve never declined an invitation. I understand that it’s how the world works; first of all, there are younger players than me, and there are also better players than me. So why would they want to invite a college graduate? It’s understandable. I like playing chess. If I’m not playing closed tournaments, I prefer playing open tournaments compared to no tournaments at all. Also, they have reasonable prizes, especially in America.

First of all, there are younger players than me, and there are also better players than me. So why would they want to invite a college graduate? It’s understandable.

- Awonder Liang.

When it comes to playing lower-rated players, it’s funny that they got rid of this 0.8 rule, let’s say, because Hikaru was doing some activities. I was also, to some extent, a beneficiary of this rule. On average, I was gaining around 0.3 rating points per game against below-2400 rated opponents. But on average, your 2600 player was losing a crazy 1.5 rating points per game against such opponents. So I was way outperforming my competition, but my rating was increasing more slowly.

For me, I just like playing the game. It’s a good way to get more and more practice. A lot of people sometimes think, because I play all these opens, that most of my rating gain is from farming lower-rated players. But it’s not really true. My largest rating point gain per game has been against 2600+ opposition; on average I’m gaining around 1 or 1.5 rating points per game against those players. It’s just hard to find those players very consistently, because you have to play extremely strong tournaments like the World Cup or Grand Swiss. Without those tournaments, it’s hard to play against them.

If I’m not playing against them, I still prefer to be in practice and get in shape. Playing chess is, in general, fun. Well, most people don’t really find it extremely enjoyable. There’s a very tedious and laborious task in preparing and analyzing. But yeah, I enjoy it. I like going to tournaments; I like playing. If I get invited to good tournaments, then I play and that’s great. If I don’t, then I’ll play these smaller events. It’s good either way.

J: In one interview, you talked about falling asleep during games. Is that just a physiological thing, or a broader reflection of your stress-free relationship with chess?
AL: Well, I don’t know. [Laughs] Sometimes I just say things in interviews. I do think a lot about my mood and how I feel during games and whether those games tend to go well or not. For instance, I’ve found an extreme negative correlation between walking around during the game and my overall result. It’s only been very recent that this has happened. So now I try not to walk around anymore.

As I said earlier, as chess players, we really only know ourselves very well, because I’m thinking all the time about myself and what I can do to improve. Wait, that sounds a bit conceited [laughs], but like what is happening inside of me.

J: You’ve talked about certain players that you admire because they play the game with a certain ambitiousness or fearlessness, rather than being happy with an easier draw. Do you feel like there’s some aesthetic quality that chess players should have, beyond simply accuracy?
AL: There’s a famous joke with the French and the British. It’s like we admire what we don’t have. To some extent, I play a style which is not as courageous. In general in life, I don’t tend to take that much risk. So I admire people who I view as more courageous, in different aspects.

I’m thinking a lot about how to take tiny advantages and optimize in the long time horizon. My style is somewhat agnostic. There’s no specific design style, but maybe there are certain types of positions I play better. And for that reason, maybe it looks a little bit worse. One example of a thing I do is I force draws with the White pieces, which is generally pretty bad practice; a lot of tournament organizers don’t like to see that. I understand, right? If you’re hosting an event, you don’t want someone refusing to play a game. But in different circumstances, I feel it’s the right decision, so it’s one I’m very comfortable taking, myself. Which is probably a weakness of mine that I’m not fighting a lot, but I don’t think there’s specifically a right or wrong way to do things.

But I admire a guy like Gukesh or Arjun, where they have a bit of this gambler mentality. Their mental strength is very strong, and the way they bounce back from losses is extremely admirable to me. How they are so courageous, I think that’s let them climb very quickly to the top. Insofar as chess is mimetic, probably those are the type of traits that I would like to copy from them and learn to get better at.

J: Five years from now, if not pro chess, what would you likely be doing?
AL: Right now, it’s a bit too far to think about. At some point I would like to go back to school, though. I think I was a pretty bad student at Chicago, and I was a horrible researcher as well. Part of it was that I lacked the discipline. There’s a lot of foundational stuff that I really missed out on at UChicago, especially because I was going to school at the same time ChatGPT was starting to eclipse the average undergrad student. By the time I was in my senior year, it was clearly smarter than any undergrad student. At that point, I stopped doing schoolwork.

I think there’s a lot of basic stuff that I never grasped really well, like linear algebra. I didn’t really understand what it was about. Especially in economics, we were doing a lot of work in econometrics or machine learning. I was doing well on the exams and projects. But it would be nice to go a little further and understand what this is about.

So I would like to go back to school at some point. Of course now it’s much easier, because you can just open up a textbook and learn by yourself. But there’s a part of me that misses it, not because it would help me get a job or anything like that, but just, maybe I left something on the table there. That’s part of why I pursued chess, because I felt like I didn’t make the most of my potential in chess and it’d be nice to see, if I took it seriously for a bit, where we could go with that.

J: Just like ChatGPT would be a better student than you, LeelaKnightOdds is going to be a far superior player to you. Apart from the practical implications of analysis, does the existence of engines make you feel positively or negatively about chess?
AL: I really like engines, just like I’m a huge ChatGPT fan. Most of my friends were absolutely disgusted with ChatGPT when it came out and probably still are. I’ve always had an overreliance on these tools, not in the sense that I only listen to what they say, but I’m very used to using them. And if used correctly, they are great accelerators. One mistake people often make is they don’t invest enough time into things. You can’t get the same results without investing a large amount of time. Using the engine can sometimes trick you into thinking you can do things faster. But if I spend 8 hours without the engine, versus if I spent 8 hours with the engine, it’s still quite useful in that sense.

Where the engine helps the most is that it can help you understand a lot of positions and structures much faster than you otherwise would. You can read books or see what other people have said or see what other people did in their games. But the engine does show you what the correct move is. It’s always the responsibility of the human or the operator to try to understand why things are.

We have thousands of thousands of lines of engine analysis, and then it’s your job as the human to abstract away all that analysis into one page or a couple of paragraphs about what a position is really about.

- Awonder Liang.

Engines have gotten so much better recently that it feels like they always say what is true. That’s very useful, because you don’t always, in life, know whether something is correct or not. I have a very strong belief that what is correct does matter. All the other things, like understanding, are useful abstractions to help us remember what the engine says.

That’s the main goal of the work I do in general. I think what most top players do is we have thousands of thousands of lines of engine analysis, and then it’s your job as the human to abstract away all that analysis into one page or a couple of paragraphs about what a position is really about. Like our goal is to trade off these pieces, or this piece would like to go here. Or more often, it’s like a flow chart: if White does this plan, then Black does this plan; if White does this other plan, then Black can do this other plan, and so on.

How useful it is depends on the user. I used to say about ChatGPT, which all my friends hated, that ChatGPT never gives wrong answers; there are only wrong prompts. Not saying that I was a prompt engineer or anything. Yeah, it’s very much how I view things: that these are just tools. If they’re giving wrong outputs, I think that’s more about the user than it is about the tool itself. So I think it’s tremendously helpful.

J: Speaking of your enjoyment of chess, how has it changed over time?
AL: My enjoyment of chess has waxed and waned. Every chess player goes through this cycle, especially when we started very young. If you talk to any prodigy, we’ve all had periods of intense burnout, and periods where we hadn’t looked at chess for months and years. I also went through that period for maybe 4 or 5 years. But I was in high school and college at that time. I was homeschooled for 4 years, and I was doing a lot of chess then. Then I finished high school and went to college on top of that.

It’s hard to do only one thing your entire life… There are many interesting things in the world and many things are very beautiful. Chess is just one aspect of that.

- Awonder Liang.

I think it’s a very common thing in chess: many players who were very strong when they were young no longer continue pursuing chess and go on to do many other excellent things in life. It’s hard to do only one thing your entire life; it’s not really a way to live life. There are many interesting things in the world and many things are very beautiful. Chess is just one aspect of that.

I began to enjoy it more when I was in college and had more of a break, for a couple of reasons. First of all, it was a good way to make money that will always be very motivating. [Laughs] Also, I would go to tournaments with friends, and just by luck or happenstance, I was winning a lot when I was in college. Even though I hadn’t played for a couple of years and wasn’t really studying, I was going to tournaments and winning all the big opens in the US, and not with much difficulty at that.

When I look back at my chess self when I was 15 or something, really it was incredible. Sometimes I look at the games I played, and it’s just amazing that I played like that at such a young age. But my results are much better now. Part of it is because when I do play the game, I’m much more motivated; I’m much more focused. I do the work before the tournament. When I sit at the board, it’s like, “This is my life and this is my goal right now”.

That motivation helps a lot, because when I’m in worse positions, I do spend a lot of energy trying to defend. When I’m in better positions (I’m still working on it), I’m trying to convert. It gives you extra motivation in that fifth or sixth hour when you’re trying to defend, where other players might give up or you might not try that hard. And now I’m like, “Let me really try and save this game,” or “Let me really try and convert”, compared to when I was 15 and playing off of raw talent, but not much of anything else.

I think motivation actually matters an outsized amount, in terms of all the little things at the board and before the game that I do. I’m not perfect, of course. I could be much more disciplined. But definitely better than I used to be. I mean, I’m very happy with where I’m at. It’s kind of all you can be, to be better than you used to be, right?

J: Wrapping up, is there anything you’re looking forward to outside of chess in the coming year?
AL: I don’t know, it’s hard to say. I had this recent realization that I tend to run very well in even-numbered years. So 2026, I was like, “Okay, let’s go. Time to start going hard, I guess”. For whatever reason, it tends to be true. I have this very cyclical nature about myself. 2025 was very choppy in certain areas. I was investing a little bit in that period of time, and you know, Trump was doing his thing. That was very interesting. Chess as well, overall it was pretty good; I finished the year all right. But I definitely had the feeling that I left a lot on the table in terms of my professional results, personal as well. I can’t really say whether it’s good or not. You have to wait until it’s over, and we’ll see how it goes.

J: Thanks for taking the time to talk. Next time, maybe we can talk about all the questions in life that statistics and ChatGPT can’t answer.
AL: Oh no, that’s my exact weakness! Thank you for having me; it’s been a blast!

Check out the full video interview here:

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