Binghamton University researchers leverage 70-year-old information theory to enhance the strategic approach to the viral word game Wordle. Their findings highlight how a thoughtfully chosen initial guess can significantly boost a player’s odds of solving puzzling words.
Wordle invites players to uncover five-letter secret words through a series of guesses, receiving feedback that helps refine future attempts. Successfully guessing the secret word within six tries is the goal. Image credit: Aladaileh et al., doi: 10.63562/2577-8439.1146.
Wordle is a widely loved online single-player game, where players strive to guess a concealed five-letter word.
Players can win by successfully guessing the secret word within six attempts, or they face defeat.
Post-guess, players receive feedback: incorrect letters are shown in gray, letters that are correct but incorrectly placed are in yellow, and letters that are both correct and in the right position are highlighted in green.
Armed with this feedback, players can eliminate incorrect guesses and refine their strategies for subsequent tries.
“Although Wordle is recognized as a simple word-guessing game, it operates as a dynamic feedback system where each guess reshapes future possibilities,” stated lead author Dr. Congyu ‘Peter’ Wu and his colleagues.
“This ongoing feedback mechanism allows players to evolve their game strategy by learning from hints and narrowing down options, thus diminishing uncertainty.”
“We measure this uncertainty using entropy. As players receive feedback that hones their guesses, the game’s entropy diminishes, transitioning from chaos to organized clarity.”
“Information theory provides a robust framework for analyzing decision-making processes and adapting strategies in Wordle.”
The authors utilized Shannon entropy, a mathematical metric of uncertainty, to identify guesses that yield the most informative feedback.
Instead of merely trying to guess the most probable word, their strategy prioritizes words that maximize information, thereby streamlining the pool of potential answers.
“Imagine making a guess,” explained Dr. Wu. “Past guesses have already eliminated numerous options, so selecting words based on remaining possibilities accelerates the path to gathering valuable information.”
“A crucial insight from this research is that a guess need not be the most likely solution; it simply must provide critical information,” remarked co-author Donald Stevens, a doctoral student at Binghamton University.
“By employing Shannon entropy, our objective shifts from merely maximizing the probability of correct guesses to enhancing expected uncertainty reduction.”
“This approach practically allows players to solve puzzles with fewer guesses.”
While this methodology may appear random, it actually increases the likelihood of a successful guess by the end of the game.
To apply this method in real-time, players may need to run a dedicated script or program alongside the game.
Upon entering the color-coded feedback provided by the game, the program generates optimal second guesses aimed at yielding more insightful information.
In testing, this newfound strategy was compared against traditional methods that focused on guessing common letters (like A, E, R, etc.).
In simulations, the researchers’ technique solved 99% of Wordle puzzles, whereas traditional methods only managed to solve 90%.
“Results indicate that using entropy-based word selection notably enhances performance compared to heuristic strategies based on letter distribution, establishing a systematic decision-making framework in Wordle,” the researchers affirmed.
For more in-depth insights, refer to their paper, published in April 2026 in the Northeast Journal of Complex Systems.
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Talal Aladaire et al. 2026. Solving Wordle Using Information Theory. Northeast Journal of Complex Systems 8(1):6; doi: 10.63562/2577-8439.1146
Source: www.sci.news
