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I was a juror in a slip-and-fall case once. It was terrible. If Party-A makes up some absolute bull-shit Party-B is supposed to be the one that catches them at it? Usually there always is a very motivated counter party but it may not always be very skilled or have resources etc. Your example of a poor person vs an expensive legal firm.

You write some crap and essentially no-one has the motivation even to question it critically. This seems to be a very fundamental problem, as eliminating a published result typically creates huge existential problems to someone, either the PI, but often some postdoc or student. Naive first approaches are often needed to trigger deeper thinking about a question.

The problem gets ugly when we are talking about people who entered research without any kind of formal training e. I think the situation could only be made better by significantly increasing the training requirements of getting into a research position in all areas of inquiry that are lagging in this regard. If you take that away, research becomes much more expensive, as no one will do the gruelling part when being called a technician. But this way we have to let basically anyone in.

Well, another aspect is that glorified technicians often become PIs, as there are many of them, and they burn funding on misguided studies, using e. So reducing this kind of behaviour would save a lot of money. I mean look at this clip. Dwyane Wade is literally yelling at his hand it is so hot.

Am I missing something? The harm comes in not admitting an honest mistake. We should be able to acknowledge new evidence without feeling threatened. The English clergyman Matthew Henry made the famous and completely on-point! GVT had Cornell shooters predict their own shots and that of their teammates with a betting task. Unfortunately their analysis was carried out incorrectly, and when we correct for it, there is compelling evidence that Cornell players can predict at better-than-chance rates, and meaningfully better.

See Section 3. Essentially its measurement error in the opposite direction. Even if a predictor is perfect at identifying the hot hand, there is ceiling on how accurate a predictor can be in terms of outcomes. How do you use such a predictor to predict the same outcome which is the only way to measure the predictor in the first place? Bettors bet on the shot outcome of a shooter or his or her own shot.

In the toy example, the bettor can see perfectly when the shooter is hot and bets hit, and when the shooter is not hot and bets miss. So bettor is good at predicting hot state, which is relevant, but not so good at predicting hits. In our paper , on p. Correlations are dimensionless, so it is not obvious on the surface that this is meaningfully large, but because the variance in both hits and the predictions are close, this correlation is nearly equal to the coefficient in the regression of hits on predictions of hits, i.

This difference happens to be 7. More details in the footnotes. How would you even do that? I think that your work is still saying that the hot hand is a cognitive illusion, just a different one. Elin, Rahul: You could imagine hotness is a mental state about reliability and accuracy of motor coordination.

The thing is that hotness could dramatically effect the probability of a hit, say from 0. As Corey said above, the idea is that you could test the time-varying hotness model against a time-constant probability of success model, and in long sequences you could find that the time-varying model predicts the sequence better.

Using additional information from a teammate observer could help as well. GS: Yeah! And, yes, physics does make up unobserved stuff all the time… Later they come up with some specific experimental techniques that can help to observe predicted effects, and this confirmation of the predicted effect is in fact evidence increasing the posterior probability of the model.

At this point the atom was not a definite theory of matter, and Einstein used the unobserved atomic structure of matter to show that it could predict jiggling around of larger particles, he also used this idea to derive concepts related to osmotic pressure and to viscosity of fluids. To explain the radiation of a black body, Max Planck assumed what was essentially a quantization of electromagnetic radiation. In the same year as his brownian motion paper, Einstein posited that a quantum of electromagnetic radiation, now called a photon, could interact with electrons in a metal and knock free an electron, and that this radiation must have a particular sufficient energy to allow the electron to escape the matrix of the metal.

This was known as the photoelectric effect, and the posited unobserved thing was a quantum of light called the photon. So, yes, exactly, that is what physics does. If you try to take the Higgs field out of the mathematics but keep the W and Z particles and the other heavy particles such as the top quark that we have already discovered and know are present in nature, you will find that the mathematics of the Standard Model simply makes no sense. You get a theory that predicts that certain processes including ones that the LHC can study occur with a probability bigger than one.

The probability of anything obviously cannot be bigger than one or less than zero. It might surprise you that it is very hard to write down logically sound theories. Most theories that you can imagine predict negative probabilities or probabilities bigger than one. Only a very, very few make sense. To restore the theory of the Standard Model to working order, you must add a Higgs field, or something like it, to the fields that we have already discovered experimentally.

My guess is that the nonsensical probabilities you mention are closely tied to the mass of certain particles. GS: I know, hey! Otherwise why would the damn stuff flow so slowly? Glen: viscosity is an observed fact things flow more or less slowly , to Einstein atoms were not an observed fact. You know what? Causing sleepiness is an observed fact that is, we give people say Benadryl, and the vast majority of them become sleepy. An H1 receptor in the brain is more or less unobservable not directly at least but you know what?

Drugs which are observed to cause certain chemical assays to come out in certain ways which are consistent with our assumptions about the existence of H1 receptors and which enter the brain as an observed fact through experiments on animals using radioactive tagging assays, consistently cause sleepiness.

Doctors are particularly prone to the disease you seem to be railing against A doctor friend of mine went to an orthopedist complaining of pain in his foot…. Oh, says the orthopedist, you have metatarsalgia. GS: Err…no. Rate of flow is observed well…calculated from observable stuff. DL: […]to Einstein atoms were not an observed fact. The relationship is not perfect — or else the measured accuracies would suffice. DL: You know what? DL: An H1 receptor in the brain is more or less unobservable not directly at least but you know what?

DL: Drugs which are observed to cause certain chemical assays to come out in certain ways which are consistent with our assumptions about the existence of H1 receptors and which enter the brain as an observed fact through experiments on animals using radioactive tagging assays, consistently cause sleepiness. GS: Thanks for the heads up. Then you have to actually think about the differences between how physics goes about positing hypothetical constructs and how psychology does. DL: Doctors are particularly prone to the disease you seem to be railing against A doctor friend of mine went to an orthopedist complaining of pain in his foot….

As for what I am railing against, there seems to be little indication that you know what that is. GS: The devil is in the details — superficially, hypostatisations resemble, formally, legitimate postulations of unobservable stuff. We seem to be talking past each other. DL: We seem to be talking past each other. As an Engineer I understand the concept of feedback control, and I see that a human playing basketball is a system under feedback control,[…].

It sounds like standard mentalism to me. GS: Are we? But if so, then what you are really talking about are the combined effects of several independent-variables on aspects of behavior that ultimately result in the dichotomous hit or miss. We do this in ordinary-language and it is why it is done in ostensibly-scientific endeavors. This is, in part, also driven by the quest for talking about temporally-contiguous causation which fuels the reification of behavior as mental stuff.

GS: I could go along with that. GS: OK…agreed. The signal is tiny and the noise in the data seems to be swamping the signal in the actual data but we still cling to some tiny signal we can discern in an artificial control and brandish it as evidence of the phenomenon? Also, I see no relationship to himmacanes, I mean the two principle issues with himmacanes are: 1 forking paths, and 2 selection outside of NHST. The degree of control here varies, as well as the degree of artificiality, yet the results are consistent.

Should we really restrict ourselves to analyses of game data when forming beliefs about the hot hand in game data? Why can we not perform inductive inference to game data here? We have: 1 a strong estimated effect of a prior streak on subsequent success in relatively controlled settings, and 2 there is some evidence regarding underlying mechanisms, e. I had a feeling, one of the most compelling feelings that I can have, that we were finally done with posts about hot hands.

Dubner has repeatedly shown himself to be an absolute hack. Actually that was his Sophomore year. But he was 20 percent in his conference games, no doubt due to subtle priming effects. Wow… these Yale Websites are hard to negotiate. Actually, a question that came up recently in the NBA was whether having a father who was a superstar prevents you from becoming a superstar.

The fact that a superstar has never had a son who is also a superstar is also an artifact of regression to the mean as well as the fact that few NBA players of any caliber are the offspring of multimilionaires for a number of well-understood environmental reasons. Baseball, on the other hand, has the Griffeys at least although Griffey Sr is not in the Hall, or particularly close to superstar caliber and a number of multigenerational good talents, if not a superstar line.

Baseball used to have few dynasties, but then had a remarkable number in the late 20th Century with the Bonds, the Griffeys, etc. Basketball seems to be filling up with guys who are the offspring of both male and female college basketball players.

One question is whether any famous athletes are the secret illegitimate children of famous athletes. Probably some, but maybe not as many as we might think off the top of our heads. Auto racing has lots of dynasties because the job is kind of like being a political candidate or a movie producer: talent is involved, but also having name recognition and being a plausible leader for other talented people to work for.

First, what is the general nature of the problem? Shooting and sometimes making baskets is operant behavior that is thus, by definition affected by its consequences. This is how skilled and sometimes not-so-skilled operant response classes that are relevant to many sports and other areas — the issue pertains to all operant behavior including, importantly, rats pressing levers get produced.

Initial responses are wildly variable but are not without effect upon the environment. This is not rocket science — it is much harder, as the study of the behavior of animals is probably the most complex scientific endeavor of all time. Just watch a rat emit food-reinforced lever-presses — no two are identical.

But members by definition all have one thing in common — they close the microswitch mounted on the lever. And, of course, that is the definitional operant class. There is a lot of behavior that occurs because of reinforcement of members of the definitional operant that is not, itself, in the definitional response class i. The rat will, for example, sometimes touch and depress the lever with insufficient force to close the microswitch. So, instead of the complexities of the basketball court, turn to the relative simplicity of the rat pressing a lever.

One need not see, for example, that hits per opportunity increase in general. It might be a rare but real phenomenon. Behavior that results in the ball going in also results in the strengthening of behavior that results in hitting the rim. Now…how do such responses change in terms of the arc over time?

Imagine a 3d frequency graph where the axes are frequency, time, and arc. Now…look at that graph for, say, 30 experimental sessions. You would see order but you would also see the hills and valleys of the distribution of arcs drift around. And, keep in mind, we have only been considering the arc. Any given rat presses levers with one paw, two paws, one on top one on the bottom, one paw and the snout, two paws while biting on the lever. All these features of behavior change over time and do so because of the dynamic system that results from a simple dependency between microswitch closures and food deliveries.

Apologies for any typos or unclear writing that I missed. When the effect itself is so small can we be confident that what we detect in the surrogate games is a good indicator what happens in the real games? Rahul: True that there is no guarantee that results will extrapolate.

In some controlled shooting situations the task is quite close, and the main difference from the game is 1 defender, 2 incentives. Even in games there are unguarded shots. In some semi-controlled shooting situations, like the Three Point Contest, the incentives are high. The question is what should we believe given the available evidence. We know that there is no scientific way to measure the strength of the hot hand using game data—-e.

This is using data that GVT considered the critical test of hot hand shooting. GS: LOL. You pays your money and you takes your chances. Every physicist I know starts from the premise that the hot hand is fallacy and refuses to listen to the contrary until presented with a decent explanation why it might not be.

Players get tired, so it might be reasonable to expect the operative p to decline during a game or a season, but basically shooting a basketball is as close to flipping the famous nonexistent Bernoulli p coin as anything macroscopic comes. If your statistics is showing a hot hand effect, the operative premise should be that you are surely doing something wrong.

Exactly my thought. Just coz' there's no p-value waving in our face, do we let down our crap defenses? We all have our blind spots, eh? To me this seems the same old story of obsessing after some subliminal, ephemeral "effect" signal in a mountain of noisy data. When the effect is elusive just keep shifting the goal posts. Sooner or later you are bound to smoke the artifact out. Just make sure you have enough data to through at your data mining machine.

Here we have a situation where the complexity of what it means to play basketball as a Homo sapien almost HAS to ensure that your performance varies through time, and yet because performance is inconsistent any given shot is not perfectly predictable the RandomNumberGenerator-istas assert that it HAS to be the case that we assume that basketball players are Bernoulli RNGs with constant p until proven otherwise through extensive data collection.

This is a disease of people trained in frequentist statistics. And from a qualitative perspective, the people who know the most—players, coaches, dedicated fans— tell you over and over that there is a hot hand. And what they mean is really that p changes. The point of the RNG argument is not really that there is or is not a hot hand, it is that people misperceive reality in basketball and most other contexts.

But when the point of it becomes to make a larger argument about people misperceiving random events that becomes a different issue. To me, the larger argument about human misperception of probabilities risks and benefits is one that I have always found problematic. Now, suppose I have a robot with a hand, and it has a camera and force sensors and some fairly sophisticated software, and there are two of them. End of story. Let me give you some real world issues to consider:.

If my team goes to a small lineup with multiple good passers, they will create good opportunities for me and I will shoot well, so I will appear hot. If the player guarding me is bad at defense, I will shoot well, so I will appear hot. If the other team starts double teaming my teammate, I will get open a lot and shoot better, and appear hot.

I could go on. You should ask Zach Lowe NBA writer at The Ringer who has led a lot of the mainstream discussion around NBA data statistics to suggest a better data-set to run this test against, if the idea is really to discover about the hot hand and not just illustrate a bigger point about human intuition.

Suppose I generate a random number uniformly between 0 and 1 and then use it to as p to generate a bernoulli random number… and I give you the output of this bernoulli stream. I invite you to start with this code and try to find out from just the output of the numbers whether p varied each time, or not:.

The real question is whether some of the factors that affect real world time-variation in performance are in fact detectable by the players themselves and their teammates. This is because I know what it is supposed to feel like when the ball goes in the direction I wanted it to go in. And then you time integrate the euclidean distance from that perfect trajectory for the ball from the time it leaves the hands to the time it first hits any object… Would it be so hard to believe that there are periods of time where players consistently get smaller integrated deviations from perfect, whereas other times they have larger integrated deviations from perfect?

This is more or less the accuracy with which we could extract the initial conditions using several laser scanners or something. If not, sub-divide more than 1M times until you have a constant outcome in each cube.

In both cases, they are vastly over-playing their information hand and arriving at incorrect conclusions. You need to convince me shooting a basketball is not well modeled as a simple Poisson process and that every such process or similar ones does not exhibit what you consider to be hot hand effects. Right, I think this was the intuition behind my idea. There are an infinite family of possible beta distributions from which your bernoulli sequence could have been generated.

Do you have the algebra on this? That would seem to apply as well if you used something like a gaussian process type construct on a sequence of thetas. Well, correlation in the sequence of thetas will induce correlation in the sequence of X values, and given sufficient data that correlation will be detectible. Move out of the basketball context and consider a very very long sequence of Bernoulli variables and slow drift in the success probability from zero-ish to one-ish and back again.

I guess the consolation is that any theta distribution with the right mean also gives the same posterior predictive distribution. Making a field goal tends to lead to tighter defense the next time, making the analytical problem difficult.

More significantly, the Bucs are against the spread—the NFL's joint-best winning percentage this season—as the underdog and Brady is in the same scenario in his career. Brady, however, is against the spread in his nine appearances in the Big Game and while betting against six-time Super Bowl champion remains a risky exercise, some bookmakers don't expect Brady's first season in Tampa to have a fairytale end.

Louis Rams in , Brady's first appearance in the Super Bowl. Favorites are against the spread in the Super Bowl and have covered in the last two and three of the last four. In the past 20 years, 10 Super Bowls have gone over and 10, including the last two, have gone under. The picture has been similarly balanced for the Chiefs and the Bucs this season, with the over hitting in nine of Kansas City's 18 games and in 11 of the Bucs' 19 games.

The Bucs and the Chiefs have the second-best and fifth-best offense in the NFL in terms of points scored this season, at an average of Tampa Bay has scored at least 24 points in its last 10 straight games—including the loss at home to Kansas City in Week 12 of the regular season—and arrives in Super Bowl LV on the back of a franchise-record streak of scoring at least 30 points in six consecutive games, while the Chiefs have scored at least 30 points in six of their last seven playoff games.

On the other side of the ball, the Bucs have allowed Dig a bit deeper, however, and the gap between the defenses is wider than those figures suggest. Read more. Choose your subscription.

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Google Tag Manager. Oddshark logo linked to Home. Close Menu. Odds Shark Top Sportsbooks 1. Visit operator for details. There are currently no NFL trends available. Should we really restrict ourselves to analyses of game data when forming beliefs about the hot hand in game data?

Why can we not perform inductive inference to game data here? We have: 1 a strong estimated effect of a prior streak on subsequent success in relatively controlled settings, and 2 there is some evidence regarding underlying mechanisms, e. I had a feeling, one of the most compelling feelings that I can have, that we were finally done with posts about hot hands.

Dubner has repeatedly shown himself to be an absolute hack. Actually that was his Sophomore year. But he was 20 percent in his conference games, no doubt due to subtle priming effects. Wow… these Yale Websites are hard to negotiate. Actually, a question that came up recently in the NBA was whether having a father who was a superstar prevents you from becoming a superstar.

The fact that a superstar has never had a son who is also a superstar is also an artifact of regression to the mean as well as the fact that few NBA players of any caliber are the offspring of multimilionaires for a number of well-understood environmental reasons.

Baseball, on the other hand, has the Griffeys at least although Griffey Sr is not in the Hall, or particularly close to superstar caliber and a number of multigenerational good talents, if not a superstar line. Baseball used to have few dynasties, but then had a remarkable number in the late 20th Century with the Bonds, the Griffeys, etc. Basketball seems to be filling up with guys who are the offspring of both male and female college basketball players. One question is whether any famous athletes are the secret illegitimate children of famous athletes.

Probably some, but maybe not as many as we might think off the top of our heads. Auto racing has lots of dynasties because the job is kind of like being a political candidate or a movie producer: talent is involved, but also having name recognition and being a plausible leader for other talented people to work for. First, what is the general nature of the problem? Shooting and sometimes making baskets is operant behavior that is thus, by definition affected by its consequences.

This is how skilled and sometimes not-so-skilled operant response classes that are relevant to many sports and other areas — the issue pertains to all operant behavior including, importantly, rats pressing levers get produced. Initial responses are wildly variable but are not without effect upon the environment. This is not rocket science — it is much harder, as the study of the behavior of animals is probably the most complex scientific endeavor of all time.

Just watch a rat emit food-reinforced lever-presses — no two are identical. But members by definition all have one thing in common — they close the microswitch mounted on the lever. And, of course, that is the definitional operant class. There is a lot of behavior that occurs because of reinforcement of members of the definitional operant that is not, itself, in the definitional response class i.

The rat will, for example, sometimes touch and depress the lever with insufficient force to close the microswitch. So, instead of the complexities of the basketball court, turn to the relative simplicity of the rat pressing a lever. One need not see, for example, that hits per opportunity increase in general.

It might be a rare but real phenomenon. Behavior that results in the ball going in also results in the strengthening of behavior that results in hitting the rim. Now…how do such responses change in terms of the arc over time? Imagine a 3d frequency graph where the axes are frequency, time, and arc. Now…look at that graph for, say, 30 experimental sessions. You would see order but you would also see the hills and valleys of the distribution of arcs drift around.

And, keep in mind, we have only been considering the arc. Any given rat presses levers with one paw, two paws, one on top one on the bottom, one paw and the snout, two paws while biting on the lever. All these features of behavior change over time and do so because of the dynamic system that results from a simple dependency between microswitch closures and food deliveries.

Apologies for any typos or unclear writing that I missed. When the effect itself is so small can we be confident that what we detect in the surrogate games is a good indicator what happens in the real games? Rahul: True that there is no guarantee that results will extrapolate.

In some controlled shooting situations the task is quite close, and the main difference from the game is 1 defender, 2 incentives. Even in games there are unguarded shots. In some semi-controlled shooting situations, like the Three Point Contest, the incentives are high. The question is what should we believe given the available evidence. We know that there is no scientific way to measure the strength of the hot hand using game data—-e.

This is using data that GVT considered the critical test of hot hand shooting. GS: LOL. You pays your money and you takes your chances. Every physicist I know starts from the premise that the hot hand is fallacy and refuses to listen to the contrary until presented with a decent explanation why it might not be.

Players get tired, so it might be reasonable to expect the operative p to decline during a game or a season, but basically shooting a basketball is as close to flipping the famous nonexistent Bernoulli p coin as anything macroscopic comes.

If your statistics is showing a hot hand effect, the operative premise should be that you are surely doing something wrong. Exactly my thought. Just coz' there's no p-value waving in our face, do we let down our crap defenses? We all have our blind spots, eh? To me this seems the same old story of obsessing after some subliminal, ephemeral "effect" signal in a mountain of noisy data.

When the effect is elusive just keep shifting the goal posts. Sooner or later you are bound to smoke the artifact out. Just make sure you have enough data to through at your data mining machine. Here we have a situation where the complexity of what it means to play basketball as a Homo sapien almost HAS to ensure that your performance varies through time, and yet because performance is inconsistent any given shot is not perfectly predictable the RandomNumberGenerator-istas assert that it HAS to be the case that we assume that basketball players are Bernoulli RNGs with constant p until proven otherwise through extensive data collection.

This is a disease of people trained in frequentist statistics. And from a qualitative perspective, the people who know the most—players, coaches, dedicated fans— tell you over and over that there is a hot hand. And what they mean is really that p changes. The point of the RNG argument is not really that there is or is not a hot hand, it is that people misperceive reality in basketball and most other contexts.

But when the point of it becomes to make a larger argument about people misperceiving random events that becomes a different issue. To me, the larger argument about human misperception of probabilities risks and benefits is one that I have always found problematic.

Now, suppose I have a robot with a hand, and it has a camera and force sensors and some fairly sophisticated software, and there are two of them. End of story. Let me give you some real world issues to consider:. If my team goes to a small lineup with multiple good passers, they will create good opportunities for me and I will shoot well, so I will appear hot. If the player guarding me is bad at defense, I will shoot well, so I will appear hot. If the other team starts double teaming my teammate, I will get open a lot and shoot better, and appear hot.

I could go on. You should ask Zach Lowe NBA writer at The Ringer who has led a lot of the mainstream discussion around NBA data statistics to suggest a better data-set to run this test against, if the idea is really to discover about the hot hand and not just illustrate a bigger point about human intuition. Suppose I generate a random number uniformly between 0 and 1 and then use it to as p to generate a bernoulli random number… and I give you the output of this bernoulli stream.

I invite you to start with this code and try to find out from just the output of the numbers whether p varied each time, or not:. The real question is whether some of the factors that affect real world time-variation in performance are in fact detectable by the players themselves and their teammates. This is because I know what it is supposed to feel like when the ball goes in the direction I wanted it to go in.

And then you time integrate the euclidean distance from that perfect trajectory for the ball from the time it leaves the hands to the time it first hits any object… Would it be so hard to believe that there are periods of time where players consistently get smaller integrated deviations from perfect, whereas other times they have larger integrated deviations from perfect?

This is more or less the accuracy with which we could extract the initial conditions using several laser scanners or something. If not, sub-divide more than 1M times until you have a constant outcome in each cube. In both cases, they are vastly over-playing their information hand and arriving at incorrect conclusions. You need to convince me shooting a basketball is not well modeled as a simple Poisson process and that every such process or similar ones does not exhibit what you consider to be hot hand effects.

Right, I think this was the intuition behind my idea. There are an infinite family of possible beta distributions from which your bernoulli sequence could have been generated. Do you have the algebra on this? That would seem to apply as well if you used something like a gaussian process type construct on a sequence of thetas. Well, correlation in the sequence of thetas will induce correlation in the sequence of X values, and given sufficient data that correlation will be detectible.

Move out of the basketball context and consider a very very long sequence of Bernoulli variables and slow drift in the success probability from zero-ish to one-ish and back again. I guess the consolation is that any theta distribution with the right mean also gives the same posterior predictive distribution.

Making a field goal tends to lead to tighter defense the next time, making the analytical problem difficult. But free throws are almost all taken under similar circumstances, so free throws should be more amenable to statistical analysis of whether hot hands exist. For other data with absence of defense including Three Point shooting , we discuss that in our papers. See, for example, here: Study published in , followed by successful replication in [sic].

As I discussed here , our awareness of these problems has changed during the past several years. Coincidentally, I wrote a Bem-themed post awhile ago that just happens to be appearing today. It was not written in response to this comment thread. There are definitely Cold Hands. For example, Wilt Chamberlain, who bored easily, experimented with various ways to shoot free throws, some of which worked poorly, others of which work terribly.

For example, when I watched him in , he only made Not surprisingly, he suffered a year-long Cold Hand. On the other hand, free throw shooting is the least difficult and most boring part of basketball, so it could be that free throw shooting is less susceptible to small cold hands than is field goal shooting.

But is a Career Peak different from a Hot Hand? The problem with heat checks is that the players start to take more and more ridiculous shots, thus resulting in some misses. I think one of the best data sets for this might be the 3 point shooting contest. It definitely seems players either miss a bunch in a row or make a bunch in a row, but there is also the factor of rack location to take into account.

His poor percentage this year could be explained by him not having the ball in his hand as much and therefore not getting in rhythm, i. Imagine not taking a shot for ten minutes then having to shoot a 3. If you made the prior shot do the exact same thing. If you were short use some more legs, etc. Sport is an agonistic activity where there is a winner and a loser; as a result, small advantages are worth having. I could write a whole paper exposing example after example.

In fact, I did:. My coworker pointed me at this post though coincidentally I first introduced him to your blog. The method is actually based on the class of cross-validation methods in your recent review paper. Though now I am wondering whether the effect I saw was really the bias reported in Miller and Sanjurjo.

After a set of simulations, I found the bias to be negligible for the string sizes in my data. The bias is on the order of a few tenths of a percentage, some of which is attributable to using a prior. I think the main result in my example still holds. I think that some sort of latent model would be more appropriate, in that whether you just made a shot is not a perfect measure of hotness.

It is hard for instance to pool data across seasons for a given player like LeBron as his percentages have fluctuated annually. However free throws are shot in a more controlled manner and shooters are able to go into the exact same routine each time. The Markovian type models without latent variables are not great but of all the types of shooting I would expect them to work best for free throws.

The messed up column headers and nobody noticed this in the comments does not bring me confidence in these values or the analysis. It is clear there is spreadsheet mangling going on here. However, if they disagreed with my hypothesis I would find the column headers very concerning and throw out this analysis.

Wardrop, Robert L. Jeremy Arkes has some evidence in his analysis of play-by-play data: Arkes, Jeremy. Yaari, Gur, and Shmuel Eisenmann. We played around with Free Throw data and found that players shoot better in the second half of the season, its discussed in a footnote here:.

In all seriousness people have been doing calculations on how unlikely that is given their average 3-point percentage. Just look at Boston who also had a horrific Game 7 shooting performance. Mail will not be published. Isaac says:. April 2, at am. Reply to this comment.

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