Believe it or not, fantasy football analysts aren’t trying to trick you. They WANT you to win. THEY want to win. There’s no secret cabal of hooded statisticians plotting behind the scenes with the sole intention of making you lose your work league. The FF Deep State doesn’t exist. No, the problem isn’t fantasy analysts trying to trick you. It’s that they are tricking themselves.

And, in most cases, fallacies are to blame. A fallacy is a mistaken belief, especially one based on an unsound argument. The argument might seem eloquent or reasonable or even air-tight. But, somewhere along the chain of logic, there is a broken link. And that is often the difference between fact and fiction. The fantasy analyst is sharing what they believe to be true - but they may have fallen for fallacies along the way, the real truth eluding them.

The writing of this article may be a mistake. Because I know for a fact that I have fallen victim to many common fallacies before. I can guarantee you that I will fall for them again. And I’m sure that, following the publishing of this article, folks will respond to future takes of mine across the wide world of social media with accusations of me falling for or abusing fallacies myself. But that’s a sacrifice I’m willing to make.

So here you have it. The big list of fantasy football fallacies, sorted by alphabetical order to reference in your future internet arguments. You’re welcome. And I’m sorry.

 

 

 

Fantasy Football Fallacies

Ad Hominem

Latin for “to the person”, the attack is shifted from the facts at hand to the person making the argument. They are calling into question the character, motive, or other attributes rather than arguing the substance of what is actually being said. Those witnessing the discussion might also dismiss the facts being presented if they believe the presenter might not be reliable. Even if the person’s credibility might be questionable, that does not mean that what they are saying is untrue. 

Fallacy: Analyst A shares a take on his favorite defense to draft in fantasy football. They discuss their players, their schedule, the statistics. Someone responds, “Didn’t you get fired from Super Secret Fantasy Site last year? Why would we listen to you?”. Once others realize that it is true that they no longer work for Super Secret Fantasy Site, they call into question whether they should take their advice or not.

Reality: Whether it’s true or not, it does not matter whether they were fired from the site. It has nothing to do with the argument they have presented. The response is an attempt to smear the presenter instead of addressing the points they’ve presented. Being a jerk is a fairly common tactic, especially on the internet, but you never actually win the argument that way, only distract from it. No one is going to look to you for you for advice, even if Analyst A was wrong about the defense, because you didn’t actually give any advice yourself. And you certainly won’t make a lot of friends along the way.

 

Affirming A Disjunct

This is also known as the false exclusionary disjunct. Consider the very simple statement “A or B”. You might assume that, if A is true, B cannot be. But that assumption leaves out the possibility that the “or” is defined inclusively rather than exclusively, where perhaps both or neither can be true. The argument presenting using the exclusive logic may even sound logical, but the result is unsound.

Fallacy: We don’t know who the starting running back for a particular team is. Player A could end up being the backup running back or he could be relevant in fantasy football. Player A ends up as the backup running back so he will not be fantasy-relevant. 

Reality: This train of thought sounds logical. But it leaves out the possibility that Player A is the backup but is still relevant, something we know is possible. We’ve seen backup running backs who were just as good if not better in fantasy football than the guy who is labeled as the starter. And we’ve certainly seen backups for one team that were better than the starters for another. Just because the first half of the statement is true it does not mean the second half is false. 

 

Anecdotal Evidence

This is where a person draws a conclusion from an isolated example. The example is often something that they experienced personally, making the incident more vivid. They draw their conclusions based on their limited experience, assuming future experiences or outcomes should be similar.

Fallacy: An analyst is discussing an incoming rookie quarterback. They share a story about a college game that they attended with their father where the quarterback threw five touchdown passes. They looked great. The analyst then tells their followers to draft that quarterback on their fantasy football teams. 

Reality: One college football game is an incredibly small sample size. And the vividness of their experience at the game may be swaying their overall opinion on the player. The game could have been against a far inferior team. It could have simply been an outlier. Or maybe the quarterback’s skill set fits the college game but won’t translate to the NFL. Seeing one good college game live is a nice story but more research is needed before making a call on the player.

 

Appeal To Antiquity

Also known as an Appeal to Tradition, this is where you claim that a thesis is correct based on past or present tradition. It’s always been done that way so that is the way it should be done. Now, the traditional way could actually be the correct way. But you should consider all the alternatives as well first, rather than outright dismissing them in favor of what has historically been done. Tradition alone is not logical proof.

Fallacy: Many analysts have said that “you should never draft more than one tight end”. That’s just the way that you should build your fantasy football team. That’s what the magazines said in the early 2000s and it has worked for us for years. It’s the only way to play.

Reality: You will always want to draft in a way that is specific to your format. In some formats, you might want to treat certain positions differently. But that doesn’t mean that it is true for all leagues and strategies. Even if you won a league in the past with one strategy, that doesn't guarantee that is the best strategy even for that same league in a different year. The fantasy football landscape is always changing. At one point, it may have been popular to only draft one tight end, but we have since learned that other strategies are also viable, especially for deeper formats. There are many ways to build a championship roster and, in order to prove a strategy is ideal, we need more evidence than “that is the way it has always been done”. 

 

Appeal To Authority

An authority figure of some kind presents an idea. Because they are viewed as an expert in their field, their declaration could be taken at face value despite the lack of proof. Some might even ignore the counterarguments because they trust the authority figure. This can often lead to Circular Reasoning, where the expert’s declaration is used to justify the conclusion and the conclusion is only based on the expert’s declaration.

Fallacy: A hypothetical analyst referred to as The Tight End Gossiper proclaims that Tight End A is the best. The TE Gossiper is widely regarded as an expert on tight end analysis so he clearly knows what he’s talking about. The community at large proceeds to draft Tight End A as the first tight end off the board.

Reality: Even experts in particular fields can get things wrong. You should always ask for proof of work to make sure the logic presented is sound. If the arguments for Tight End A are filled with fallacies or flat-out inaccuracies, he might not be the best option after all. The Tight End Gossiper might not be completely immune to fallacies himself, even if he understands them. He might even appreciate you checking his work to make sure we’re all giving ourselves the best chance to win.

 

Appeal To Consequences 

This is where a premise is deemed true or untrue based on the consequences of what might happen as a result. The consequences can either be good or bad but the possibility of those outcomes incorrectly leads to the assumption that the original premise is true. For instance, if one of the outcomes is unfavorable, we might assume that the argument leading to that result is wrong. Our brains want the argument and the result to be the most comfortable one.

Fallacy: Two running backs are vying for a starting job. Player A is viewed as a good pass-catcher while Player B isn't. If Player A gets the job, he will likely play every down and have big upside for fantasy. If Player B gets the starting job, he will still likely split work with Player A which isn't ideal. If Player A were to get the job that would be the best outcome for fantasy football so we should draft him and hope for that. Player A ends up going earlier than Player B in average draft position (ADP) using this logic.

Reality: Player A getting the job might be the best case scenario. But we should not simply rush out to best case scenario because it's comfortable. We should analyze the data at hand to assess what is most likely to happen. Player B might just be the better rusher and deserving of the starting job. That could easily make him the more valuable player - most backfields are split anyway. In this case, the fallacy working to raise Player A's ADP benefits those who select Player B later on.

 

 

 

Appeal To Novelty

This is the implication that something new or modern is naturally going to be better. That is not always the case, however, as new ideas or products fail all the time. Or, even if they succeed, they are not guaranteed to be better than older alternatives. 

Fallacy: A team has an incumbent veteran quarterback, Quarterback A. They then select Quarterback B in the NFL draft. This exciting new rookie QB will surely be the better pick of the two in fantasy football. Think of the upside potential of this younger, unknown commodity.  

Reality: Being the newer player doesn’t guarantee that they will be better, even if their hypothetical upside is higher. Quarterback A could hold the job down all season with Quarterback B having zero value. That might actually be the team's intention, with the plan to start Quarterback B next year. The threat of Quarterback A getting benched for the new commodity could lower his draft stock, creating a value in fantasy football. But the newer model isn't always better.

 

Appeal To Ridicule

This is when an argument is attacked by making it seem absurd or laughable. It’s often combined with other fallacies, like a strawman, to distort the take and boil it down to something simple and easy to criticize. The plan is to ridicule the argument itself to dismiss it - laughter is a powerful tool in debates but it’s not a substitute for logic. 

Fallacy: Analyst 1 compares the situation this year for Player A to the situation for Player B last year, who was the MVP of the league. Analyst 2 comments, “Look at this bozo, he thinks Player A will be the MVP!” A bunch of other people then join in ridiculing Analyst 1. His take has pretty much been dismissed by this point.

Reality: Analyst 1 never actually said that Player A was going to be the MVP - they were just comparing the situations. Regardless, Analyst B did not actually provide any evidence to refute the initial statement of Analyst 1. Instead, Analyst B distilled and distorted the statement down to something that they could then make fun of. They created a straw man to attack with the MVP argument (see below for Straw Man Fallacy). No real argument was presented outside of what amounts to an ad hominem attack against Analyst A and his take. Being mean on the internet is not a substitute for logic, even if it is funny.

 

Appeal To Pity

This fallacy is an appeal to emotion. They are looking for your empathy. And, sometimes, they might deserve it. But, in some cases, the pity they are looking for has nothing to do with the actual argument at hand. Or maybe they are overexaggerating the situation to get what they want. It can be difficult to discern whether or not they are deserving of your grace.

Fallacy: Player A and Player B are working on a trade in a dynasty league. Player B asks Player A to throw in an additional pick. They say, “Your team is so good and my team is so bad - you won’t need the pick nor will you miss it. You’ll probably win the league this year”. Maybe you should help them out - they are your friend after all. 

Reality: The entire point of a dynasty league is to not only win now but also win later. You do not owe the other members of the league anything beyond a fair trade. Player B might have actually set their team up purposely to be bad now in an attempt to tank and build a really good team for later. They are attempting to get something extra from you that, in this case, they do not deserve. Fantasy football is only a game - a game with only one winner and you are both trying to win.

 

Appeal To Probability 

The Latin name for this one, possibiliter ergo probabiliter, means “possibly, therefore probably”. It’s a logical fallacy where you assume something is true because it’s possibly or even probably true. This can be especially deceptive if we have data showing that the odds are in favor. We assume the most likely outcome will come to fruition but it’s only guaranteed if the probability is 100%.

Fallacy: A quarterback, who was drafted in the sixth round of the NFL draft, earns the starting job. He plays pretty well in his first few games. We know, historically, that the hit rate for quarterbacks drafted in that range is less than 5%. It is probably in your best interest to trade that player away in your fantasy league because there’s a 95% chance that he doesn’t actually amount to anything meaningful, based on what we know analytically. 

Reality: Even the existence of that 5% already tells us that there are outliers. And, even if a player drafted in a specific spot has never been great, that doesn’t mean it could not happen in the future. The draft is an inexact science. It might be the prudent move to sell the player now, given the information we have. But that doesn’t mean that the player won’t succeed. 

 

Association Fallacy

This is also known commonly as an appeal to spite. By definition, it means that you assert that properties of one thing must also be properties of another if they belong to a similar group. You are attempting to win the argument by exploiting the audience’s opinion of the other party or their argument, especially if that opinion is negative. You are guilty by association.   

Fallacy: Analyst 1 shares a take, saying they like Player A this season. Analyst 2 comments on their post saying “Remember when this guy liked Player B last year and he was terrible?”. People see that reply and decide that maybe they should not trust Analyst 1 on his take on Player A because, if he liked Player B last year, he must not be good at this.

Reality: The analysis of Player A this season has nothing to do with the analysis of Player B last year. Analyst 1 could have been correct on a lot of things outside of Player B last year. Analyst 2 is attempting to associate the first analyst with his take from the previous year in an attempt to appeal to folks who might be spiteful against Analyst 1 because of the previous take. At no point does Analyst 2 actually provide a meaningful argument against Player A, outside of what amounts to an ad hominem attack against the other analyst. 

 

Bandwagon Fallacy

This is the belief that something must be true because others believe it. If many people think it’s good, then it must be good. Another fallacy that goes hand in hand with Appeal to Authority and Circular Reasoning. In fantasy football, this could be reflected in ADP.

Fallacy: Slot Wide Receiver A had a decent year last year. Five of your favorite experts have talked about him on their podcasts so far this summer, including the most popular one, The Fantasy Football Dude Bros. They all think he is ready for a big breakout. Your friends also love Slot Wide Receiver A as well. He must be ready to break out.

Reality: Just because he is popular among the analysts that you like, that doesn’t mean that they are right. You might just like those analysts because they think like you. Your friends might like those analysts for the same reason. The large number of people touting Slot Wide Receiver A, especially ones with large follower bases, could be pushing him up draft boards to the point where the potential upside is not actually worth the risk. It’s tempting to join the angry mob but, even when they have the numbers, that doesn’t make them right. 

 

Cherry Picking

Also known as the fallacy of incomplete evidence, this is the act of pointing to certain data points to confirm your position while ignoring significant portions of related data. If you isolate certain information, the argument looks great but, once the data set is expanded or other similar cases of data are considered, the argument isn’t as sound. They are not lying about the information but they are leaving out some inconvenient details either by accident or on purpose. 

Fallacy: Over his final five games, Running Back A averaged over 100 rushing yards per game and scored a touchdown in each game. That performance will likely carry over to this season, where he should be a great pick in fantasy football.

Reality: The running back was good in those games. But, when you expand the sample size to the full season, it turns out he was not that good. There are a number of factors that could have caused that. Maybe those five teams were among the worst defenses. Maybe the starting running back was hurt and he will be back next season. Maybe Running Back A simply got lucky in such a small sample size of games. Regardless, the larger context should not be ignored for the favorable stretch of games.

 

Circular Reasoning

This is when an argument loops back on itself, using its own claim as proof. It seems like valid reasoning, especially when presented by a reliable source. But, once you break the argument down, there isn’t any actual evidence presented outside of the claim.

Fallacy: Tight End A is the first tight end drafted in fantasy football drafts because he is the best. That’s why he gets drafted earlier than the other tight ends. If you want to have the best tight end, you’re going to need to draft Tight End A early. 

Reality: Our minds sometimes enjoy a nice, clean loop. The argument seems to check out - the best tight end goes first and he goes first because he’s the best. But there’s not actually any factual proof presented here that he’s the best. We not only need proof that he is the best tight end but we also need data to suggest that the best tight end is worth a high draft pick. The best RB and WR are often worth very high draft picks but that’s not always the case with other positions like tight end, quarterback, kicker, and defense. 

 

Continuum Fallacy

This is where you incorrectly reject a claim because it is vague. We would like the claim to be precise. If the argument is that we could not know the answer or that the results could vary drastically, that might not appeal to us. 

Fallacy: Analyst A is asked about an incoming rookie. Analyst A says that, based on his research, the range of outcomes for this player are wide. He could be great, he could be terrible, or he could just be okay. The data does not point to anything definitive. His analysis is dismissed because we were expecting a more definitive answer as to whether the player could be good or not. Analyst B is saying he will definitely be great so we will side with them - he must have better information.

Reality:  Football is a game with a lot of moving parts. And we sometimes don’t have definitive answers. The correct analysis might be to warn potential drafters that this is a high risk, high reward pick. And the incorrect analysis might be to say this player is going to be definitively good or definitively bad. We need to accept the possibility of variance in this case, even if that makes it difficult to rank a player. 

 

Data Dredging

This is also referred to at times as “p-hacking”. This is when someone violates the rules of statistics to influence the data collection process in order to produce statistically significant results. Rather than starting with a hypothesis and testing it to find a result, they often have the result in mind and then tweak the statistical tests to provide the positive results. This increases and also understates the risks of false positives.

Fallacy: Analyst A pulls up a list of wide receivers that got 10 carries in a season. Many of them were good but some of them were bad. They then narrow the list to only players who got 10 carries and also 125 targets. It removes some of the good players but also removes all of the bad players, leaving only good players. They then conclude that we should be looking for wide receivers we can expect to get at least 10 carries and 125 targets. That must be the secret.

Reality: What they essentially did was manipulate the data until it provided a result that seemed statistically significant. And it seems to make sense - if you can hit those parameters, the player will be good. But the tests were not done honestly and the data is not necessarily meaningful. First, it left out a number of good players that did not meet the minimums. It also doesn’t necessarily prove that the carries were significant for the players - it could have just been the targets. On top of that, carries for wide receivers are notoriously difficult to predict. The results of the study doesn’t provide meaningful information for us to utilize, even if it seems logical. 

 

Division Fallacy

The division fallacy is where we assume what is true for the whole must be true for each individual part. If the combined entity is great, that must be true for the pieces. 

Fallacy: The Green Birds just won the championship game. Pretty much all of their weapons were great in fantasy football. Their starting running back, Running Back A, then leaves in free agency. The Green Birds were the best team with good players - Running Back A should be great once again this year. 

Reality: The Green Birds may have some great players. But that doesn’t mean that every player is great. The performance of the team is a combined effort. The truth could be that they have a great coach, quarterback, and offensive line and that made things easy for Running Back A, even if he’s not that good himself. And, even if he is good, he might not have success if his new team is bad. Just because he was a part of a great team, that does not mean he is great or will be great this year.

 

Double Counting

This is a mistake made where, when counting events or occurrences in probability, a solution counts events/probabilities two or more times, resulting in an erroneous number of events or occurrences that is higher than the true result. The result may be calculated as a sum of the probabilities for all possible outcomes. That calculation could even go higher than 100% which obviously isn’t possible. In many cases, the probabilities overlap and are already accounted for.

Fallacy: Let’s say hypothetically, the hit rate on a tight end drafted in the first round is 60%. And tight ends that run a 40 yard dash of 4.55 or better have a hit rate of 60%. Also, tight ends that have 1,000 yards or more in a college season hit 60% of the time. Tight End A was drafted in the first round while running a 4.52 and having 1,100 yards receiving last year. So he’s virtually guaranteed to hit - 180% guaranteed. 

Reality: The data in this case does not stack because it overlaps. If you run a 4.52 as a tight end, you are more likely to have a lot of yards. If you have a lot of yards, you are more likely to be drafted in the first round. The first round draft capital already encapsulates the underlying metrics. You are double counting the data by compounding those data points. 

 

Equivocation

This occurs when a word or phrase is used with two or more different meanings. The word is often used in the same argument in the context of the multiple different meanings. Whether intentional or not, the ambiguity in the language creates misdirection in what the actual message is.

Fallacy: An analyst posts a simple message - “Player A is RB1”. That has everyone excited about Player A. Fans of Player A like and share the post. To say such a thing, the analyst must think Player A is a good fantasy football pick. Later on in the comments, he mentions that he believes that Player A will earn the RB1 job for his team.

Reality: The term “RB1” carries multiple different meanings in fantasy football. Player A could be the RB1 on his team, meaning he’s the starter and one of the league's 32 RB1s. He could also be an RB1 in fantasy football, typically meaning top 10-12. The term RB1 is also used to describe the top overall scoring RB. Being an RB1 on a team doesn’t guarantee they will be an RB1 in fantasy football which also doesn’t guarantee they will be the RB1 overall. The initial post is intentionally vague, allowing the analyst to get engagement from fans of Player A. He later hedges by saying he simply meant that Player A would be the starting RB for his team. The use of a term with multiple meanings creates misdirection. 

 

False Dilemma

Also known as “false choice”, this is when an often complex issue is boiled down into a black or white question. Good or evil. Us or them. The fallacy corners you into choosing one of the two options when a choice might not even be necessary - options like choosing both, neither, or a third option might also be on the table. 

Fallacy: You have two wide receivers on the same team - Player A and Player B. The quarterback is naturally going to favor one of those two players. Therefore, if you like Player A, you should be out on Player B, and vice versa. You have to pick one. 

Reality: The false dilemma implies that there are only two outcomes: Player A is good or Player B is good. In reality, there are many possible outcomes. The two options presented aren’t even mutually exclusive. BOTH players could be good. Both could be bad. A third player, Player C, could be the quarterback’s favorite. In a fantasy football draft, there are no black or white dilemmas. You are not required to draft either player and drafting one does not exclude you from drafting the other.

 

False Equivalence

Also known as false balance, this fallacy is where you treat two things as equal when they are not. In terms of information, both pieces could be valuable but the importance of each piece of information is not weighted equally and should not be considered equally. This is sometimes referred to as “bothsides-ism” where our mind believes that both sides of an argument deserve to be heard but we sometimes don’t recognize when one side has overwhelming evidence in its favor. Sometimes, the debaters are not equally qualified to discuss the matter either.

Fallacy: Analyst 1 suggests that Player A will have a good season. They present several well-researched points with three years' worth of data backing it up. They even provide clips from games showing what the data is telling us. Analyst 2 then says that they are a fan of the team that Player A plays for and that they watch every game. They don’t think Player A will have a good season. Looks like we have a stalemate with two opposing viewpoints.

Reality: In this case, you have two differing opinions. But, based on the evidence presented, the two opinions should not be weighted equally. One analyst clearly did the research on top of watching the film. The other analyst only gave their opinion based on watching the games - an opinion that may be biased one way or the other as a fan of the team. To treat both opinions equally is false balance.

 

 

 

False Precision

This is when numerical data is presented in a manner that implies better precision is likely to make a prediction more accurate. In reality, it might not even be a matter where a precise prediction is possible. But the idea that the person making the argument could narrow it down to such an exact number appeals to us. If they are confident enough in their process to be that precise, we might have a bias towards their argument.

Fallacy: An Analyst is touting Wide Receiver A. He says, “Based on my model, Wide Receiver A should have 113 catches for 1,678 yards, and 13 touchdowns this year”. A season like that would easily make Wide Receiver A one best players in fantasy football. So he must be a great pick.

Reality: Football is an incredibly fluky game. Anything can happen from week to week and play to play, including injuries to both offensive and defensive players. We really do not have the capability to predict the exact statistics of players down to the yard. This analyst may have a good process but the excessive precision of his prediction does not make it any better than analysts painting their picture of the upcoming season with a broader brush.

 

Gambler’s Fallacy

A coin has a 50/50 shot of landing on heads or tails. It lands on tails five times in a row. The fallacy is believing that, based on the odds, heads is now “due” and more likely to come up this time. But each individual flip has nothing to do with the previous flips. The odds of heads or tails are still exactly 50% each time. The past flips do not influence the future ones.

Fallacy: Kicker A has been a great kicker historically. He hits roughly 90% of his field goals. This game, he missed his first two kicks, which is out of character for him. He’s very likely to make the next one based on the percentages.

Reality: Each individual kick is its own event. Assuming the conditions have not changed, missing the previous kick does not make it more likely that Kicker A will make the next kick due to some kind of regression to the mean. The fact that he is a good kicker matters in terms of predicting the next kick. Other factors could affect the likelihood of him making the kick, like distance or injury. But the results of the previous kick and relation to overall probabilities do not affect the likelihood of subsequent kicks. Each kick is still its own individual event. 

 

Hasty Generalization

This fallacy is when your first impression or a limited sample size shapes everything that follows. You’ve formed your opinion already. Any subsequent data or information that confirms your bias will be looked on as favorable and anything that goes against it may be dismissed as a fluke.

Fallacy: You sit down to watch Monday Night Football in Week One. Quarterback A comes out and throws 4 touchdown passes, running for another. You watched the entire game and Quarterback A was great. He must be a great quarterback. 

Reality: It takes a lot of time to watch every NFL game. You might just catch bits and pieces of most games. If this primetime game was your only exposure to Quarterback A, that might be your only reference point. When you look at his stats for games moving forward, that might have you categorizing any good games he has as the norm and any poor performances he has moving forward as “bad luck”. The truth is that you need a bigger sample size before solidifying your opinion. You may have been too quick to make a determination based on that first experience.

 

Loaded Question

This is where a question is asked that contains a controversial or unjustified assumption. The question is designed as a trap to make the respondent potentially admit to something that they might not believe in or that isn’t relevant. The question itself can often be an accusation. 

Fallacy: Analyst 1 says they don’t like Player A for fantasy football this year. He lays out his argument statistically. Analyst 2 asks them, “Aren’t you a fan of the Green Birds, a rival team of Player A?”

Reality: The goal of the question is to imply that Analyst 1 might be biased against Player A because he plays for a rival team. Analyst 2 likely already knows the answer and understands what the loaded question implies. The truth is that the favorite team of an analyst should not matter for their unbiased player takes for fantasy football. If Analyst 1 simply answers “Yes” to that question, observers might take the implication at face value that he is biased. They now need to defend themselves against the loaded question on a topic that should be irrelevant to the actual argument.

 

Middle Ground Fallacy

Two sides are at odds on a topic. They may even be sitting at extreme ends of the matter. The fallacy is that the actual truth must lie somewhere in between those two views when, in reality, it could lie anywhere along the spectrum - or even outside of it.

Fallacy: One group of analysts loves Player A and they are drafting him early. Another group hates Player A and they are ranking him very low. His ADP ends up somewhere in between. That’s probably where he should be ranked and it’s probably the best picture of where he will finish.

Reality: The truth might not be in the middle ground. Either the first group or second group might actually be exactly right or far more right than the other. This can especially be true with positions that have a linear depth chart like quarterback. If one group thinks Player A wins the job but the other thinks Player B wins the job, both of their ADPs could be suppressed to the middle ground. But only one player will win the job and that player will likely outperform their ADP with the group supporting him being right and the other group being wrong. The player could even be better than the first group believes. In that event, the truth was not in the middle ground or even on the spectrum that was created by the two groups.

 

Moving The Goal Posts

This is a logical fallacy that is especially interesting given our discussion is football-related. Picture your team lining up for a 50 yard field goal. Right as you go to kick it, the other team moves the goalposts back to 80 yards. Where 50 was sufficient before, now they are requiring a nearly impossible feat. They literally moved the goalposts. And that’s the idea of the fallacy. You dismiss the evidence presented while requiring additional, greater evidence to be provided. Even if the initial evidence is satisfactory, the arguer claims it isn’t until you cannot meet their demands, at which case they dismiss your claims.

Fallacy: Analyst 1 claims that rookie Tight End A will be good this year, citing their research with a recent example of a similar player doing well. Analyst 2 then mentions that they only provided one example. They then point out that there have only been eight tight ends ever with similar opportunities and all of them have performed well, expanding the examples to eight. Analyst 2 then says that it is still too small a sample size and any less than 15 is not meaningful. You cannot find 15 examples so they dismiss your claim. 

Reality: In this case, you already gave ample evidence with all eight players having performed well. Knowingly or not, Analyst B then changed the requirements to the point where you couldn’t possibly meet their demands because there haven’t been enough examples in the history of football. They moved the goalposts so far that the field goal could not possibly be converted, even though your argument should have easily cleared any logical objections. 

 

Post Hoc Ergo Propter Hoc 

One thing happens. And then another happens. Because the first thing happened and then the second thing happened, we assume that the first thing caused the second thing. The truth, however, is that those two things might not be related at all. That’s post hoc ergo propter hoc, which translates to “after this, therefore because of this”.

Fallacy: The head coach had been calling the plays. He then gives over playcalling duty to the offensive coordinator. In that next game, the quarterback throws two touchdown passes to Wide Receiver A who had not caught one TD all year. The fantasy community says to spend all of your free agent auction budget (FAAB) to add Wide Receiver A off the waiver wire. The new playcaller must LOVE him.

Reality: There is a chance the new playcaller loves this new wide receiver. But we need to consider all of the facts. Maybe Wide Receiver A simply had an easy matchup? Maybe other pass-catchers on the team were hurt but are returning soon? Maybe the two touchdowns only happened on three total targets, suggesting it might have just been a fluke? The idea that changing the playcaller is the sole reason for the performance and that similar performances are sure to follow might be a fallacy. 

 

Sunk Cost Fallacy

This is when a person refuses to abandon a strategy or course of action because they have already invested heavily in it. They are reluctant to abandon their investment without realizing that they are only causing more damage by not pivoting to a new solution. 

Fallacy: Player A was your first-round pick but he is not playing well. He’s been hurting your team so far. You did spend your first-round pick on him because he was supposed to be good. You continue to start him in your lineup because you invested so much in him already. He’s bound to turn it around. 

Reality: That may be true. But the argument that “you invested a lot in him so you should continue to start him” is not a good reason. Depending on what your actual research suggests, the best course of action might be to bench him, trade him, or even drop him to waivers for another option. Or the research might say to stick with him. But your previous investment should not dictate your future plans. The meaningful data should dictate the plans.

 

Straw Man

This is when you refute an argument that is different from the one actually under discussion while not recognizing or acknowledging the distinction. If you engage in the fallacy, you are “attacking a straw man”. It’s difficult to combat it because the moment someone has to say “that’s not what I meant”, the discussion has already been completely derailed. Often simply shifting the argument in this way can hurt the original argument. 

Fallacy: Analyst 1 lays out an argument for why Running Back A will have a good season. It includes both statistical and film analysis. He says he has him ranked over Running Back B and Running Back C. Analyst 2 then says, “Oh you think Running Back B is bad then?”. The discussion now shifts to Running Back B and his merits.

Reality: Analyst 1 never actually said that Running Back B is bad. Those might actually be his two top-ranked running backs where he likes both of them more than consensus. But, rather than refuting the statistical argument in favor of Running Back A, Analyst 2 uses Running Back B as the strawman argument. The illusion he is creating is that, if Analyst 1 can’t argue that Running Back B is bad, then he will have won the argument. Analyst 1 now has to clarify that he does not believe Running Back B is bad, he simply likes Running Back A more with hopes that he can get Analyst 2 back onto the real topic, which is Running Back B. But the diversion created might already have been enough to sidetrack the discussion. 

 

Texas Sharpshooter

This is where you focus on similarities while ignoring differences then declare a meaningful pattern. The name comes from the classic example where a sharpshooter shoots randomly into a wall then paints the bullseye around the tightest cluster of shots afterward. He then shows the bullseye with the shots and declares his accuracy. 

Fallacy: Wide Receivers A, B, C, D, and E all have high contested catch rates, meaning they all catch a high percentage of their targets with defenders in the vicinity. Wide Receivers A, B, and C were among the top wide receivers in the league last year. Wide receivers D and E are likely due for a breakout this year.

Reality: This one data point is certainly a positive one. But it doesn’t tell the whole story. Wide Receiver A could play 95% of the snaps and his 70% contested catch rate could be based on catching 14 of 20 contested targets. Wide Receiver E on the other hand might only play 30% of the snaps and his 80% contested catch rate might be based on catches 4 of 5 contested targets. He might not even get a bigger role this year and that contested catch rate might not translate to increased snaps. Being good at the one facet of the position also doesn’t guarantee he will score a lot of fantasy points. There could also be really good WRs with low contested catches or bad ones just outside the 70% arbitrary cutoff. The pattern is not actually meaningful - it has just been framed that way in hindsight. 

How Can I Avoid Fallacies?

You can't. They are always going to be prevalent, not just in fantasy football but in the wide world of disagreement. Arguments spring up when you least expect it - and you have to be ready to dissect them. More than ever, media literacy is crucial in our society. 

In your journeys you are undoubtedly destined to run into bad faith actors. And you're also likely to run into good faith actors who have simply fallen for a misconception. You yourself will fall for fallacies again at some point - as will I. But, now that we're aware of at least a few of them, hopefully we can spend more time on the path of reason and logic. At least for a little while. So good luck out there and, remember - use your noggin and pick your battles!