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Data Science Blog > Python > Exploring Chess Openings: Can We Pinpoint a 'Best' Opening?

Exploring Chess Openings: Can We Pinpoint a 'Best' Opening?

Zachary MacTaggart
Posted on Oct 24, 2023

Chess, one of most popular and well recognized board games in the world, has experienced a recent resurgence over the past few years. This revival has attracted many new players to chess, including myself. Even though the knowledge of strategy and tactics in chess is vast, openings stand out as one of the most interesting features. Openings are the first few moves each player decides to play and dictate the flow of the rest of the game. As I delved deeper into chess and its openings, I often found myself wondering if a 'best' opening exists, and whether that is even possible to discover. In this project, I take the initial steps to try and answer this question.

Data Exploration

Dataset Information

The dataset is from Kaggle.com and is a collection of chess games from the popular chess website Lichess.com. The dataset can be found here. It includes features such as the opening played, the variation played, rating of each player, game ID, and number of turns for approximately 20,000 chess games.

Data Transformation and Outlier Removal

The data was transformed for the project by:

  1. Including only unique game IDs to remove any duplicates.
  2. Including only ranked games to remove any unranked games.
  3. Filtering out games with a rating difference between players of 479 rating or above. This was the maximum value in the boxplot below. These games were removed as players that had the high rating difference advantage had a significantly higher win rate (chi-square test between the win rates of the high and low rating difference groups produced a p-value of 2.14e-48).

Win Frequency and Rating

Player Rating Distribution

I created two histograms displaying the distributions of player ratings for each color/side. They both exhibit a fairly typical normal distribution and are an effective visualization for player ratings. On average players had a rating of approximately 1593. Players on Lichess.com start at 1500 rating so it makes sense the majority of players are centered near that number.

Win Frequency by Each Side/Color

Looking at wins by color reveals that playing black (having the second turn) is not as disadvantageous as I previously thought. The win frequency between each side is relatively close.

First Look at Openings and Variations

Most Popular Openings

The bar graph below displays the top 20 most popular openings within the entire dataset out of the 227 unique openings. The Sicilian Defense emerged as the most popular opening overall, likely due to its widely recognized effectiveness as an opening.

Opening Variations

Openings also have their own variations, involving an extension of moves played after the initial ones. Though this project only focuses on openings, I created a Sankey diagram to illustrate how complex openings can become when the variations are included. However, only variations with 5 or more games played were included in the diagram as including more made it too difficult to read.

Opening Analysis

Opening Win Rates

Top 10% Rating Bracket (Advanced Players)

Examining popular openings (>50 games) among 10% of players (1952.5+ rating), we can observe the successful openings they use: the Nimzo-Indian Defense, the English Opening, and the Scandinavian Defense. All of these openings have a positive win rate above 50% for advanced players.

Majority Rating Bracket

Similar to the top 10% rating group, this graph shows the preferred openings and win rates of players in the majority rating group (group within one standard deviation of the mean rating). Notably, the majority of players share popular openings with advanced players, but their win rates differ. Majority of players have a positive win rate with the Queen's Gambit Declined, the English Opening, the Ruy Lopez, and the Sicilian Defense.

Openings and Checkmates

What is a checkmate?

Checkmate means forcing the opponent's king into a position in which it has no way to escape being captured. Beyond win rates, checkmate frequency offers an alternative measure for evaluating openings. Chess players might explore this metric alongside win rates to supplement their strategies.

Openings with High Amount of Checkmates

Below is a graph displaying openings with the highest proportion of checkmates per game. The Van't Kruijis Opening, the Hungarian Opening and the King's Pawn Game all result in checkmates in about 40% of games they are played in.

Checkmates and Resignations by Rating Group

Checkmate frequency might not be the most accurate gauge of opening effectiveness due to resignations. Players could resign a match before the checkmate process finishes. Below are two graphs displaying the proportion of checkmates and resignations by each rating group.

We see as rating increases checkmates decrease, but resignations also increase. This is likely due to more advanced players seeing the checkmates moves ahead and resigning before they are completed. This leads to checkmate frequency not being a robust metric to measure opening effectiveness.

Conclusions and Future Work

Conclusion on Openings

In summary, pinpointing a single 'best' opening is probably not possible due to numerous factors that influence openings. However, analyzing popular openings and their success based on win rates and other metrics can provide valuable insight for chess coaches and players to enhance their opening repertoire and potentially improve their win rates.

Future Work

For future work on this topic, there are a few features I would like to explore further. Specifically rating differences between players, seeing how the variations of openings impact win rates, and seeing what openings 'counter' or have a high win rate against other popular openings.

Rating difference ended up being a more interesting feature than I expected, revealing notable variations between games. This finding could be of interest to platforms like Lichess.com to enhance their matchmaking fairness and ensure players are being evenly matched.

A future project I would like to implement would be making an interactive app using R Shiny. This app would allow users to input their chess rating and receive an output or graph showcasing the top openings and their corresponding win rates, offering chess players easy access to successful openings within their rating group.

Links

Github: zmactag/Chess-Dataset-Analysis: Python project for NYCDSA bootcamp. First project coding/using python. (github.com)

About Author

Zachary MacTaggart

Experienced medical laboratory scientist with a passion for data analytics in healthcare. Looking to transition into my first data science role, driven by an interest in machine learning techniques and the desire to bolster my analytical tools and...
View all posts by Zachary MacTaggart >

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