Fantasy Frameworks
Tools for making better decisions.
Introduction
I've been obsessed with decision-making for as long as I can remember. I am not an ‘expert’, but I consider myself a ‘decision science enthusiast’. I spent over five years at university researching decision-making, and now my day job revolves around helping people navigate uncertainty in business and compliance. I am enthralled by trying to understand what conditions lead to the best outcomes and designing strategies to improve decision success. Six years ago, this obsession naturally led me to one of the most fascinating games of making decisions amid uncertainty: Fantasy Premier League.
This experiment has gone quite well. At the time of writing, I have the best average rank over the six years I have played. Of course, a lot of that is luck, but perhaps there’s some signal buried in there. People often assume that any signal is linked to being an ‘analytics’ manager and the quality of data I use. Indeed, I was an early adopter of FPL Review and elevenify.com is popular mainly because I share my data and models. Naturally, people seek out the best projections and tools, but you might be surprised to hear that I don’t think having the best data is the most important factor in improving at fantasy games (excellent comment to devalue my website!).
The idea that models ‘play fantasy for you’ is completely wrong. Even with perfect data, you are still the one making decisions. You can’t remove the human element from the process, and having the best tools doesn’t automatically make you a logical, rational decision-maker. Sometimes, it does the opposite. There will always be aspects of the game that humans can navigate better than machines. Data is important, but what is more important is a proper marriage between the human and the data.
Fantasy will always be a game of incomplete information and luck. But that doesn’t mean we should be nihilistic about success. In the long run, fantasy is a game of skill. The best way to think about your actions is that they don’t guarantee a specific outcome, but they shape your distribution of outcomes. So, your goal is to find strategies that help you make the best possible decision given uncertainty. Refining your decision quality will improve your fantasy performance more than anything else. I believe techniques like those in this article would give you an advantage over others even if you only had access to worse data than they did. This article comes from the general notes I’ve kept over the years on improving my process, now expanded with specific applications to Fantasy Premier League.
My fantasy decision-making process generally starts with: Do I have a rule or heuristic I can apply? If I do, I use that as my foundation and build from there. This article contains 23+ frameworks, each with an application to fantasy decision-making. It will serve as a dedicated resource that I’ll continue to refine over time. Please message me or comment if you see any fantasy-specific examples when reading through this, and I will add them to the article.
It’s important to recognize that there is no reason to believe that fantasy games or the tools we use to help us are set up to encourage good decision-making by default. The hope is that these frameworks can act as a counterweight, creating a better system and a better environment for making strong decisions. I firmly believe that these skills can be trained and developed like muscles. Your goal is to implement and practice them as often as possible, and over time, you will get better. I truly believe that implementing these ideas correctly will improve your fantasy management more than anything else.
Switching Cost
Framework: The higher the switching cost, the more reluctant you should be to explore and try new options.
Fantasy application: In fantasy, the cost of switching between players is generally high because your resources are limited: one free transfer per week, hits required beyond that, and only two wildcards per season.
Beyond these tangible costs, there are also intangibles to consider:
Football is inherently unpredictable, so you don’t get immediate, clear feedback on whether a switch was good or bad.
Players are dynamic so there’s always a risk that both the player you bring in and the one you move out shift in unexpected ways, especially early in the season.
If these intangibles lead you to make a mistake, you often end up paying the tangible cost twice: once to bring a player in and again to transfer them out. The cost might be even greater if it involves expensive players or a shift in team structure.
From my experience, a conservative approach (exploring less than you might feel tempted to) is a solid rule of thumb. You want the moves you made 2–4 weeks ago to support the decisions you’re making now. Some might find this playstyle "boring," but I encourage you to see it differently: rolling transfers (exploring less) gives you more flexibility and freedom to make better decisions when they matter most.
Resources and related frameworks: (1) Free Rolls Framework; (2) Upstream Problem Solving Framework.
Understand The Meta
Framework: Try to understand the wider context of how games are played.
Fantasy application: If you understand the fundamental philosophies of a game, you can adapt your play to capitalize on opportunities. It’s not just about updating your assumptions about players and teams, you should also be reassessing the broader landscape (meta) as it evolves. The game has a fixed set of rules, but what is important within the game rules can shift over time. This applies both to the game of football itself and to the game of fantasy football:
In football, the meta could shift in a way that increases the average goals per game across the league, making clean sheets less common. In this scenario, you might feel dissatisfied with your defensive options (especially the expensive ones) and look for alternatives. Recognizing this meta-shift and adjusting your strategy accordingly might lead you to view defenders as less valuable. Instead of simply trying to find better defensive options, you might decide to allocate fewer resources to defence altogether, opting to play three at the back more often. You can make similar analogies for shifts in football rules that make (1) penalties more likely (penalty takers become more valuable), or (2) red cards become more common (certain players e.g., defenders might become less valuable). These are examples of how understanding broader meta-trends in football can help you make better decisions in a fantasy context.
In fantasy, it’s crucial to remember that it’s a game with a specific set of rules. While everyone is aware of the rules (e.g., forwards earn 4 points per goal, midfielders earn 5, etc.), few take the time to truly understand what those rules mean in practice. The Fast Fantasy Model I released serves as a useful heuristic, showing that, on average, defenders and goalkeepers score fewer points than other positions. As a result, they tend to be less important, and in most cases, your resources (e.g., transfers, budget) are better spent elsewhere.
Resources and related frameworks: (1) Fast Fantasy Model; (2) the rules page of the game you are playing; (3) any articles or statistical resources about football more generally.
Blinding
Framework: Limit conscious or unconscious bias by concealing key information.
Fantasy application: I structure my data with an extra page that removes team and player names to eliminate biases and preconceptions. This approach is especially useful for sensitivity analysis, as that process tends to highlight players with minutes risks and surfaces options I might not have otherwise considered. I don’t think this should be a core technique (as you still need to be engaged with the reality of your potential decisions) but I think it is a good check and balance you should be using infrequently. I typically check in this way first thing after a gameweek and then once or twice throughout the week.
Resources and related frameworks: search for blinding (or masking) in clinical trials.
Upstream Problem Solving
Framework: Solving problems before they happen rather than reacting to problems.
Fantasy application: The earlier Switching Cost framework emphasized that fantasy resources are valuable and limited. If you’re constantly using them just to fix problems rather than preparing for the future, it’s usually a sign of poor play. If this sounds like a habit in your game, you need to address the root cause. Bad habits creating these kinds of problems might include:
Buying injury-prone players.
Making unnecessary “luxury” transfers.
Bringing in players with minutes risks.
Constantly chasing the “best” player each week.
Eliminating these kinds of habits will help you manage your team more efficiently and reduce the need for reactive moves.
Resources and related frameworks: (1) Upstream by Dan Heath; (2) Switching Cost Framework.
Wisdom of the Crowd
Framework: Collect multiple different independent data points and average them together.
Fantasy application: try to gather multiple data sources to inform your decisions. For example, you could aggregate: (1) starting lineup predictions; (2) team predictions; and (3) player projections.
A unique method to improve decision-making is leveraging your past self. If you document your decisions over time, you can refer back to them, creating a kind of "wisdom of the crowd" effect from your own historical thinking. Since opinions constantly evolve, reviewing past decisions can provide valuable perspective.
That said, always consider the quality of your data sources. For instance, averaging elevenify goal predictions with market-based forecasts is likely a solid process. However, adding mainstream pundit predictions might dilute accuracy rather than enhance it.
You don’t need to do this for every decision, but for major ones, it can be a powerful tool.
Resources for further exploration: (1) The Wisdom of Crowds By James Surowiecki; (2) Make Predictions Framework.
Kill Criteria
Framework: Determine criteria for changing your mind (e.g. what specific information do you need to find out and by what specific time before you can finalise your decisions).
Fantasy application: This framework is an excellent way to know when to cut your losses. Here are a few examples:
Choosing a chip strategy often requires waiting for more information over an extended period. While there’s always the possibility that a better opportunity arises later, delaying too long can cost you points. (For more on this, see the Over-Patience Framework.) To avoid indecision, be clear on what specific information you need (such as cup fixture results that determine double and blank gameweeks) before committing to a strategy.
If you’re unsure about a player (e.g., minutes risk, penalty duties), define in advance what evidence will confirm or refute your belief. For example, if they get benched without any clear explanation or miss out on a penalty they were expected to take, that could be a signal to move on.
To avoid rushed decisions on your week-to-week transfers, determine what you need to see before making a move, such as waiting for a midweek fixture or holding off until a press conference for injury updates.
Resources and related frameworks: (1) Quit by Annie Duke; (2) Over-patience Framework.
Personal Policies
Framework: Establish a hard rule with yourself to counteract unwanted behaviour.
Fantasy application: This framework was inspired by something I heard Adam Grant discuss on a podcast about how establishing personal policies can improve workplace decision-making. I think this concept is useful in the context of this article as a kind of beginner framework. By now, you’ve probably realized that applying all these frameworks consistently is hard. It’s a constant challenge. As a first step, it may help to identify a specific struggle or flaw in your play and create a personal policy to address it. For example:
If you tend to make knee-jerk transfers, set a policy to never move early in the week.
If you struggle with price-change FOMO, create a rule that you must list other valid reasons before making a transfer.
If you constantly chase differential captains, consider a policy of always captaining your most expensive player.
Similar to Effort Allocation Framework principles, these policies might sometimes prevent you from making the absolute best decision at a given moment. However, over the long run, they will help you avoid costly mistakes while you improve other areas of your game. Once your decision-making improves, you can gradually move beyond rigid rules and make more nuanced choices.
Resources and related frameworks: (1) Rethinking the Workplace with Adam Grant; (2) Effort Allocation Framework.
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