By John Bush with David Cherney
FF Players Biased Decisions
Statement of the Problem with Fantasy Football Decision Biases
In the article referenced below *, Dr. Dennis Folds discussed that when people process information, they develop unconscious strategies – or biases – that simplify their decisions. Fantasy Football drafting is clearly an information processing activity. Thus FF Players Biased Decisions are an issue.
* “Rapid-Fire Reasoning: Research Could Help Military Leaders Make Better Decisions Under Pressure” https://gtri.gatech.edu/casestudy/rapid-fire-reasoning”
System 1 vs. System 2 Thinking
Human information processing is bound by our thinking capacity. That capacity has been studied and was the subject of the 2002 Nobel Prize awarded to Dr. Daniel Kahneman. His latest book (Thinking Fast and Slow) encompasses this work and more**. He discusses our 2 “functional” systems of decisions used under uncertainty (System 1 and 2)
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Our system 1 thinking (Fast and Frugal) dominates our system 2 (Deeper Logical) thinking **. Consider Figure 1 and the systems 1 and 2 definitions. System 2 is lazy and system 1 tries too hard and quick to solve a problem. Thus we are all “HARDWIRED” with Fantasy Football Decision Biases during informational processing because our thinking defaults to system 1. In other words, our system 1 marinates our thinking within the sea of human cognitive biases Interestingly, though we fail as a species to realize that fact (Thinking Blind)!
Figure 1. System 1 and System 2**
Fantasy Football Decision Biases
Dr. Folds’ research indicated that nine different kinds of biases could lead to errors in judgment when people are dealing with a lot of information. Meanwhile, the error rate was not as high as researchers expected for individuals used to dealing with large amounts of information under time pressure. Thus there is a light at the end of the tunnel for fantasy football players!
We, therefore, can benefit from the practice of “true” mocking drafting and actual league play. I suggest you start a fantasy diary and note highly key decisions and results. This is the beginning to “teach” your brain to work with large amounts of data under time constraints.
I have developed for myself a view of System 1 and 2 thinking in Fantasy Football. Those thoughts from my viewpoint are organized and presented in Figure 2. I suggest you read these thoughts over and think about when and where you have dealt with these issues. I would print this out and put it into your draft homework documents and cheat sheets.
Figure 2. System 1 and 2 Pros and Cons in FF Thinking
The key from Dr. Fold and Kahneman’s findings that apply to Fantasy Football players is:
“Subjects who were trained to spot conditions that lead to decision-making biases were better at detecting false-alarm opportunities.” (System 1 Traps)
Concepts to Consider for Your Training
- Fantasy Football players should practice thinking about the data/positions/league types where are you weak?
- You must know if and when you are in system 1 cognitive minefield. See Figures 3 and 4
- What are the conditions where decisions seem too good or it came to you too quick? If you are in this zone, you must “slow down” and let system 2 work for you!
- Groups do better are they are slower to decide while individuals are too quick and surf the Fantasy Football data waves on their system 1 reasoning (Fast and Frugal)!
- When you slow down you must dig up or conceptualize a view of the player/pick that breaks the model that system 1 thinking is maintaining. Lazy!
- Does data/evidence exist to “break” the conventional model?
- I am picking this guy off the waiver wire! Ask beforehand “Is this a false alarm? Write it out, walk away and read it again.
- Are you in a bias trap!
Figures 3 and 4. Examples of Cognitive Minefields in Redraft and Dynasty** Fantasy Football
**(Bias in Dynasty as per Dave Cherney)
Fantasy Football Decision Biases Battles
Seven specific biases exist that affect individuals who must wrestle with large amounts of data:
An absence of evidence.
Missing, relevant information is not properly considered. For FF players this is a key one as your system 1 thinking dominates in low information situations. You are not trained to realize that the unknown unknowns are out there. Image you on a mountain and because of the fog (Biases/Thinking), you can not see the second mountain next to you.
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Recent events or well-known conjectures provide convenient explanations. For FF players this is the concept that a “well known” idea about a player or positional usage is a system 1 trap. Everyone knows it to be true? Warning bells should sound.
Players in the off-season need to write down what everyone knows about a team etc. Then go through all the sure things and think about alternatives. I do injury matrixes to accomplish some of this thinking.
Oversensitivity to consistency.
People give more weight to multiple reports of information, even if the data came from the same source (Same report from the same source on Twitter, Facebook, and Websites etc.). This is another aspect of the system 1 thinking which rules within well-known models. So count the number of pundits that are saying the same things. Best to move unilaterally against the public!
Persistence of discredited information.
Information once deemed relevant continues to influence even after it has been discredited. The reason is that system 1 loves its models and hates to give up the “sure” things! FF players must be skeptical about the last year’s results etc. Sometimes players/teams regress to the mean!
People perceive a causal relationship when two or more events share some similarity, although the events aren’t related. Several rookies on different teams have exploded early in the season! Thus others rookies could/might/should do the same! Do not be fooled by randomness!
Evidence from small samples is seen as having the same significance as larger samples. Three players did that last time so it must be going to happen again. Stats works as a guide only when the sample value is high. More samples can provide a better confidence interval!
When people perceive (see or hear) information directly, it has a greater impact than information they receive secondhand (reading about)– even if the secondhand information has more substance. (Seeing is believing – not always!)
System 1 loves a good story. It can build great stories out of a few scraps of data and be satisfied with the story/model. Not only do we love stories but also our thinking is glorious in ignoring the fact that we just do not know about something. An FF player loves a heroic story. That player is a comeback kid /overachieving rookie /tough player etc. If many are telling the same story to beware! A vivid event generates a story!
In addition, Dr. Folds discovered two new biases that can hinder the quality of rapid decisions:
The evidence is considered relevant because of some superficial attribute, such as a keyword in a message title. For example, a hostage situation might have been reported earlier, and then another message shows up in the inbox with the word “hostage” in its header, although the message’s actual content has nothing to do with hostages.
Again the system 1 tells us a story with random information. Think of all the phrases others and I use in FF twitter, facebook, blogs and written pieces. Sensational headlines get your attention. I EXPECT READERS TO BE CRITICAL OF WHAT I SAY. You look at the data and you decide! These common phrases and headlines sooth your system 1 and put you to sleep. Wake up your system 2!
Items containing exaggerated claims or threats influence a decision-maker even when there is no substance to the content. Information presented in vivid and concrete detail often has an unwarranted impact, and people tend to disregard abstract or statistical information that may have greater evidential value.
So in fantasy football language, a player says he drafted one of the top RBs first last year and won his league. That can have as much impact as large-scale data that shows that on average that way wins you little more than by drafting a top WR first.
Case histories and personal anecdotes will have a greater impact than more informative but abstract aggregate or statistical data. Somebody on a podcast said this or that vs. looking at a table of data. The hearing or watching on TV is valued because it is vivid etc. That is the sensational appeal. We are currently in the time when you hear or read that Player Blank Blank is looking/playing/running etc. good.
Nisbett and Ross label this the “man-who” syndrome and provide the following illustrations:
- But I know a man who smoked three packs of cigarettes a day and lived to be ninety-nine.
- I know someone that won an FF league using only 2 RBs all year etc.
The absence of Evidence is a Key Element
A principal characteristic of intelligence analysis is that key information is often lacking. Analytical problems are selected on the basis of their importance and the perceived needs of the consumers, without much regard for the availability of information.
Analysts have to do the best they can with what they have, somehow taking into account the fact that much relevant information is known to be missing.
In the Journal of Experimental Psychology: Human Perception and Performance 1978, Vol. 4, No. 2, 330-344 Fault Trees: Sensitivity of Estimated Failure Probabilities to Problem Representation Baruch Fischhoff, Paul Slovic, and Sarah Lichtenstein Decision Research, A Branch of Perceptronics Eugene, Oregon
These authors use fault trees to represent problem situations by organizing “things that could go wrong” into functional categories. Such trees are essential devices for analyzing and evaluating the fallibility of complex systems. They follow many different formats, sometimes by design, other times inadvertently. The present study examined the effects of varying three aspects of fault tree structure on the evaluation of a fault tree for the event “a car fails to start.” The fault trees studied had four to eight branches, including “battery charge insufficient,” “fuel system defective,” and “all other problems.”
Major results were as follows:
- People were quite insensitive to what had been left out of a fault tree,
- Increasing the amount of detail for the tree as a whole or just for some of its branches produced small effects on perceptions, and
- The perceived importance of a particular branch was increased by presenting it in pieces (i.e., as two separate component branches). Insensitivity to omissions was found with both college student subjects and experienced garage mechanics.
Aside from their relevance for the study of problem-solving, such results may have important implications for (a) how best to inform the public about technological risks and to involve it in policy decisions and (b) how experts should perform fault tree analyses of the risks from technological systems.
As an antidote for this problem, Fantasy Football analysts should identify explicitly those relevant variables on which information is lacking, consider alternative hypotheses concerning the status of these variables, and then modify their judgment and especially confidence in their judgment accordingly. They should also consider whether the absence of information is normal or is itself an indicator of unusual activity or inactivity.
I suggest using this information to create “Fault Trees” for Fantasy Football analysis.
Figure 5. Fault Trees
Judge then the faults maybe assigning a % confidence. Also, note where that is the absence of evidence present. At least you know that area of knowledge is weak!
Other aspects of using fault trees are Injury Scenarios. If Eddie Lacy goes down, what are the fault trees branches for Rawls or Prosise at SEA etc.
I suggest for your top 1 to 3 targeted players by position that you run out fault trees beforehand. That should take a good shot at giving yourself insurance.
Figure 6. Example Fault Tree used to Fight Fantasy Football Decision Biases
Final Thoughts on Fantasy Football Decision Biases
System 1 thinking bias is strongest when the FF information is at the smallest amount.
That system (you) jumps to conclusions! You must start by formulating questions within FF information that is in the smallest amount such as:
- Rookies and their team roles.
- Free Agents and their team roles.
- New Coaches and Team Systems.
- Players coming back from injury.
Thus look at your slate of data and determine where the amount of information is the weakest. Those are system 1 minefields as Dr. Kahneman would describe or false-alarm opportunities as Dr. Fold would say.
End of Part 1
Part 2 includes discussion of Teams with Significant Coaching, Free Agent Additions, and Rookies Draft. What Teams are naturally going to have less information for our decisions?
FYI visit my previous articles
More Information Increasing Accuracy? https://www.fakepigskin.com/?p=35319
Redraft ADP Pattern Analysis 5/9/18 https://www.fakepigskin.com/?p=36403
Non-PPR Player Rankings Part 1 https://www.fakepigskin.com/?p=36513
Non-PPR Rankings Part 2 https://www.fakepigskin.com/?p=36541
PPR Rankings Part 1 https://www.fakepigskin.com/?p=36549
PPR Rankings Part 2 https://www.fakepigskin.com/?p=36554
Fantasy Football Planning https://www.fakepigskin.com/?p=36562
Why Late QB Drafting? https://www.fakepigskin.com/?p=36601
Best at Best Ball Part 1 https://www.fakepigskin.com/?p=36666
Best at Best Ball Part 2 https://www.fakepigskin.com/?p=36677
Best at Best Ball Part 3 https://www.fakepigskin.com/?p=36708
Best at Best Ball Part 4 https://www.fakepigskin.com/?p=36726
Best at Best Ball Part 5 https://www.fakepigskin.com/?p=36734