In the world of online chess, there’s this curious phenomenon of many people having a relatively easy time outsmarting their robotic opponents.
Going head-to-head with other humans requires strategic thinking and the ability to adapt on the fly. But when it comes to playing against bots at comparable ratings, many chess players notice that the bots seem to struggle against the backdrop of predictable patterns and tactical blunders.
This intriguing observation sparks a question that has puzzled many chess enthusiasts:
Why is it generally easier to beat bots than human opponents on Chess.com?
This article provides an in-depth answer to this question.
The Rating Discrepancy
If you’ve played against bots on Chess.com before, you probably noticed that their rating system isn’t very accurate.
In fact, many people find that they can regularly beat a 1500 bot, but struggle against humans rated 1200!
The computers on Chess.com are indeed overrated by around 200-300 points.
When it comes to human chess players, the Elo rating system measures their relative strength based on their performance in games. Each player is assigned a numerical rating that reflects their skill level.
Elo ratings are dynamic and are adjusted after every rated chess game — the winner gains rating points, and the loser loses rating points.
However, the ratings assigned to bots are not “real”; bots don’t gain points when they win, nor do they lose points when they are defeated. Rather, a bot’s rating is just an estimation of its strength by the programmer, and that, of course, is not very easy to quantify.
That’s why many people have suggested that Chess.com give their bots a real dynamic Elo. It remains to be seen whether or not this will be realized, but I believe it’s very unlikely for the following reason:
There is a considerable chance that Chess.com intentionally overrates bots to attract newcomers and make chess seem less intimidating to them. If a new player constantly loses against the lowest rated bots, then that could very discouraging. They may end up going somewhere else to play.
In this sense, you may want to think of a bot’s rating as a number that resembles the level of a boss in a video game; you beat the low-level mobs and advance to the stronger ones.
The Challenge of Emulating Humans
The development of bots has come a long way in terms of making them play in a more human manner, but it’s still very challenging to program them to precisely imitate a certain level.
For this reason, a bot’s playing style is very different from that of a real person, especially at the lower levels. A low-rated bot tends to move strangely and hang pieces in a way which looks very unhuman.
It’s not easy to program a bot to do a good job at emulating what someone with an Elo of 1000, for example, actually knows about chess. There is in fact a lot of variation among real people at any given rating. Some may know a few opening variations by heart, others may be good at finding middlegame tactics but struggle in endgames, and so on.
If we think about it, with the powerful chess engines available today, it’s easy to have a 3600 Elo bot: just program it to play the top computer move every time, but how exactly is a 1000 Elo bot programmed?
Such a bot would be a nerfed or “dumbed down” version of Stockfish, Komodo, or any other chess engine, but the extent of this weakening is the tricky part.
With the gigantic database of all the games played on their website, Chess.com has analytics which suggest the average frequency of mistakes or blunders a player with a certain rating makes, perhaps as a percentage of their total number of moves.
Bots at a comparable rating would be programmed to make mistakes or blunders at the same frequency, but the way in which they make these blunders is very different.
For example, a 1000-rated human may have tunnel vision and move a pawn to attack an enemy knight, not noticing that this pawn can be captured by a bishop on the other side of the board. This is a classic human blunder — at least you can understand the thought process, no matter how faulty or short-sighted.
On the other hand, a bot rated 1000 may suddenly play a weird king move, or hang their queen by sliding it one square forward for no obvious reason at all!
This bot may do a reasonably good job emulating the frequency of blunders, but its vague and inexplicable thought process would have many loopholes that are easily exploitable. That’s why this bot would be much easier to beat than a person with a similar rating.
The Difference is More Prominent in the Lower Levels
Because of the system of blunder frequency, the big difference in level between bots and people is much more prominent in the lower levels. At the higher ratings, the frequency of blunders decreases so the bots wouldn’t have much imitation problems — they would be closer to their natural habitat of consistent top computer moves.
Another reason the discrepancy is much larger at the lower levels is the learning curve.
A beginner chess player with a steep learning curve may be rated 800, but chances are, they are progressing very rapidly, so their current Elo would be only a short-term indication of their strength. They may, in fact, be playing at a 1000 level, so that would be their steady-state rating after things settle.
If this person happened to be your opponent, you will definitely find them much more difficult to beat than a 800-rated bot.
At the higher ratings, however, the learning curve is much flatter, so people wouldn’t usually gain hundreds of points of Elo in a short period of time. Therefore, the higher-rated bots resemble their human counterparts more accurately.
Predictable Playing Style
Another important factor which makes bots easier to beat is their predictability.
While bots have the ability to execute complex calculations and tactical maneuvers, their adherence to repetitive patterns and strategies can be exploited by astute human opponents.
The primary reason for a bot’s predictable playing style is its reliance on algorithms and pre-programmed responses.
Unlike real people who adapt their strategies based on the opponent’s moves and the evolving game situation, bots often rely on a set of predetermined patterns and tactics. This predictability allows human players to anticipate the bot’s moves and devise strategies that exploit its weaknesses.
For example, some bots may favor specific openings or tactical patterns regardless of the opponent’s playing style or the specific position on the board. This rigidity can make it easy for human players to identify and counter their predictable moves.
My Personal Experience with Bots
Recently, I played a game against Antonio, an advanced bot rated 1500. I had the White pieces.
In the game review, this is what the Chess.com algorithm itself had to say about Antonio’s performance:
Now, this in itself does not necessarily mean that Antonio doesn’t deserve a rating of 1500. Even we humans underperform quite often.
However, I can say with full confidence that an actual person with an Elo of 1500 is levels above Antonio.
Let me show you some of Antonio’s mistakes that someone with an Elo of 1500 is extremely unlikely to make.
Mistake 1: Hanging an important pawn
In this position, Antonio played Nd4, completely allowing me to take the pawn on h7 with check.
Would a 1500-rated player hang this pawn? I don’t think so.
Mistake 2: Hanging a rook
Just a couple of moves later, Antonio played Qe7, allowing me to play Qh8+, winning his rook through a skewer.
Again, it’s very unlikely that a human with an Elo of 1500 would hang a rook like that.
Frequently Asked Questions
Q1) How are chess bot ratings determined?
To rank chess engines like Stockfish and AlphaZero, they are usually matched up against each other in tournaments, and their results in these tournaments are used to determine their ratings.
However, the bots on Chess.com are given ratings by their programmers, who estimate the bots’ strength with some degree of error. As we’ve discussed in this article, there is a good chance Chess.com intentionally overrates bots by a few hundred points to attract newcomers.
This is one of the reasons why bots are generally easier to beat than similarly-rated real people.
Q2) What are the different types of chess bots?
In general, there are two main types of chess engines: tactical and positional.
Tactical engines are designed to excel at calculating complex variations and executing precise tactical maneuvers.
Positional engines, on the other hand, are designed to understand and exploit the strategic nuances of the game. Most chess bots are a hybrid of these two types, with varying degrees of tactical and positional skill.
As for the bots on Chess.com, there is a wide selection varying in terms of both strength and style of play
- Beginner bots: Rated 250 to 850.
- Intermediate bots: Rated 1000 to 1400.
- Advanced bots: Rated 1500 to 2100.
- Master bots: Rated 2200 to 2450.
There are also many bots modeled after famous athletes, YouTubers, chess streamers, and top chess players.
Chess.com also has special bots:
- Coach bots provide insights about the game as you play against them.
- Adaptive bots play stronger moves if you’re winning, but go easy on you if you’re behind.
However, a basic account on Chess.com only has access to a few bots. To unlock all the bots, you need to upgrade to a premium plan: a gold, platinum, or diamond membership.
I have written an in-depth review of these memberships, discussing all their features and whether it’s worth it to upgrade. You can have a look at it if you’re interested.
Q3) What are the benefits of playing chess against bots?
Here are some of the key benefits of playing against chess bots:
- Improved strategic thinking: Bots can provide a stress-free environment to practice strategic thinking and planning.
- Enhanced tactical vision: Playing against bots can help develop the ability to identify and execute tactical opportunities.
- Opportunity to experiment with new openings and strategies: Bots provide a safe environment to experiment without fear of facing a formidable human opponent.
- Improved pattern recognition: Playing against bots can help develop the ability to recognize and exploit patterns in the game.
Q4) What are the disadvantages of playing chess against bots?
Playing chess against bots also presents certain drawbacks. Here are some of them:
- Predictable playing style: Bots often exhibit predictable patterns and strategies that can be easily exploited by experienced players.
- Lack of adaptability: Bots struggle to adapt to their opponent’s playing style, making it easier to maintain a positional advantage.
- Inability to assess human element: Bots may make mistakes in complex positions or when faced with unexpected tactics due to their reliance on algorithms and inability to assess the human element of the game.
Q5) How can I improve my chess skills by playing against bots?
To improve your chess skills by playing against bots, keep in mind the following tips:
- Choose bots of the appropriate level: Playing against bots that are too easy or too difficult may be fun, but it won’t provide optimal practice.
- Analyze your games: After each game, take some time to analyze your moves and identify areas for improvement.
- Focus on positional play: While tactics are important, don’t neglect the importance of developing a strong positional understanding.
- Vary your openings: Experiment with different openings to expand your repertoire and improve your opening knowledge.
Despite the relative ease of defeating bots, it’s important to acknowledge their value as practice partners and learning tools.
By playing against bots, you can refine your strategic thinking, improve your tactical vision, and develop an ability to exploit weaknesses. Bots also provide a safe and stress-free environment to experiment with new openings and strategies fearlessly.
I have written an article explaining whether you should play against bots on Chess.com or only stick to real opponents. I highly recommend you take a look at it.
If you have any questions or insights you’d like to share, feel free to leave them in the comments down below. I’d be more than happy to have a chat with you.