A Data-Driven Approach to Chess Improvement [Part 1 - SRS & Woodpecker-Method]
Hello! I'm back with a new blogpost, but this time it's going to be a bit different. Usually I write about my own opinions on how to improve at chess but for today's article I've decided to write something more scientific while using a way more formal language. A long time ago (August 25th to be exact) I posted a survey with questions on how people train and what they consider themself good at. I've finally decided to use the 2800+ answers I got (Thanks!) to come to some conclusions about different training methods. I will divide this into a few parts and the first one will be about spaced repetition and the woodpecker method. I hope you find this interesting! It took me awhile to digest all this information so feel free to leave a like <3If you want to participate in the analytical study, answer this survey
(it's even more useful if you allow me access to your insights)
Link to discord: The Zug-Zwang-Zone
Link to lichess team: The Zug-Zwang-Zone
Spaced Repetition & The Woodpecker Method
Spaced repetition is a learning technique designed to optimize long-term retention by strategically timing the review of material at increasing intervals. This method leverages the brain's natural "forgetting curve," first identified by psychologist Hermann Ebbinghaus in the late 19th century. Ebbinghaus demonstrated that information is forgotten exponentially over time unless it is reviewed periodically. Spaced repetition aims to reinforce knowledge just as it begins to fade from memory, effectively interrupting the forgetting process and enhancing recall.
In chess, where memorization of things like tactical patterns and opening theory is essential, spaced repetition provides a powerful tool for learning. By systematically revisiting positions or concepts at optimized intervals, players can strengthen their grasp on complex ideas without overloading their cognitive resources. Chess-specific platforms such as Chessable have adopted this approach, allowing users to learn chess through "move trainer" systems that apply spaced repetition algorithms. This method tailors review sessions to individual progress, ensuring that difficult or unfamiliar positions are revisited more frequently while more familiar patterns appear less often .
Research in cognitive psychology supports the idea that spaced repetition significantly improves learning efficiency compared to massed practice, where material is crammed in one session. Studies have shown that spreading learning across time not only improves long-term retention but also helps learners develop deeper, more flexible understanding of the material . In the context of chess, this could translate to faster recognition of tactical motifs, improved opening repertoire memorization, and better overall performance during games.
The Woodpecker Method, developed by Grandmasters Axel Smith and Hans Tikkanen, is an intensive training approach designed to rapidly enhance tactical proficiency through repeated problem-solving. While it differs in structure from traditional spaced repetition, it still leverages key principles of spaced review to reinforce pattern recognition and tactical accuracy.
At its core, the Woodpecker Method involves solving a large set of tactical puzzles in a concentrated timeframe, followed by repeating the entire set multiple times over progressively shorter intervals. The first pass through the puzzles may take several weeks, but subsequent cycles are completed in increasingly compressed periods—often a week, a few days, or even a single day. This form of repetition mirrors the spaced repetition concept, where review happens at specific intervals, but here, the intervals are intentionally shortened to challenge the player’s speed and accuracy.
The shortening of intervals is crucial: just as spaced repetition leverages the brain's forgetting curve by reviewing information before it is forgotten, the Woodpecker Method forces players to re-encounter tactical motifs repeatedly in a compressed period. This reinforces neural pathways related to pattern recognition, making common tactics easier to spot and execute during actual games. In effect, the method helps transfer tactical knowledge from conscious problem-solving to near-automatic recognition—a key advantage in fast-paced, competitive settings.
While traditional spaced repetition focuses on gradually increasing the time between reviews, the Woodpecker Method intensifies the process by decreasing the intervals, aiming to create a form of “overlearning.” This repetition consolidates chess patterns into long-term memory, similar to the way spaced repetition enhances retention, but with a focus on rapid-fire review to build both familiarity and speed.
Data of the Woodpecker Method's Effectiveness
Confidence In Tactics
The effectiveness of the Woodpecker Method has been supported by numerous anecdotal accounts and performance improvements from chess players of various skill levels, most notably GM Axel Smith. To better understand its impact, data from players who have implemented the method in their training offers valuable insights into the tangible results it can deliver. Below, we analyze the outcomes reported by users of the Woodpecker Method, focusing on key metrics such as rating increases, tactical sharpness, and overall game performance.
An analysis of the survey data reveals that players who have integrated the Woodpecker Method into their training report a 38% higher confidence in their tactical abilities compared to those who do not use the method. However, it is important to note that this conclusion does not fully account for a key variable: Woodpecker Method users tend to study tactics 55% more frequently on average, which may also contribute to their increased confidence and performance.
However, even after adjusting for the increased frequency of tactical study, it can be estimated that Woodpecker Method users perceive themselves to be approximately 30% more proficient in tactics compared to the average player within their rating range.
Tactical Awareness
These conclusions are based on subjective self-assessments from players. To provide a more objective evaluation, data from Lichess insights were analyzed, focusing on tactical awareness. Tactical awareness is defined as the frequency with which a player exploits their opponent's mistakes, expressed as a percentage.
The scatter plot below displays the relationship between tactical awareness (y-axis, in percentage) and Lichess blitz rating (x-axis). The data indicate that users of the Woodpecker Method tend to have slightly higher tactical awareness overall. However, this advantage decreases as player rating increases. It should be noted that the sample size for lower-rated players, especially among Woodpecker Method users, is limited. This is likely due to lower-rated players being less familiar with the method.
Y-axis = Percentage of opponent’s mistakes exploited
X-axis = Current lichess blitz rating
After excluding the players unaware of the woodpecker method from the analysis, the difference is minimal. The sample size remains restricted, due to the limited availability of Lichess insights.
Conclusion
The Woodpecker Method offers a structured, high-intensity approach to improving tactical awareness in chess through repeated problem-solving. By applying principles of spaced repetition in a compressed time frame, the method enhances pattern recognition and tactical speed. Survey data indicates that players who adopt the Woodpecker Method report significantly higher confidence in their tactical abilities.
Objective data from Lichess insights further suggests a modest improvement in tactical awareness among Woodpecker Method users, particularly at lower and intermediate rating levels. Limitations in sample size, especially among lower-rated players, suggest that further data is needed to fully assess the long-term impact of the method.
I hope you found this interesting and I'd love to hear your feedback as this is my first scientific report. I'll probably write more about SRS (spaced repetition) in my next part, but this time with more emphasis on chessable. If you have any suggestions, feel free to let me know :)
