As we continue to expand both the number of pundits and types of pundits we track, we need your help. We are looking for volunteer Moderators and Trackers.
Moderators will take “ownership” of specific categories, helping to shape creative direction. For instance, we are considering tracking Economists in Finance and Pollsters in Politics, but these categories have gray areas that create scoring challenges. For instance, both economists and pollsters frequently revise their predictions/estimates, so how should we go about tracking them? And how should we think about margin of error? Rather than imposing our own views, we think it’s best to give authority to our users, who are more knowledgeable about these specialties than we are.
As far as Trackers, as we scale up the number of pundits we track, it becomes more difficult to catch all the predictions that are being made. As such, we are looking for Trackers who will help us screen the daily newsflow for new predictions in a given category or even for a specific pundit or television show.
Here are some of the categories for which we are looking for Moderators and Trackers, although if you have suggestions for new categories, we are all ears:
Finance: Economists (e.g. GDP, inflation), Stock Market (e.g. stock analysts, annual S&P predictions), General
Politics: Pollsters, General
Sports: NFL, MLB, NBA, NCAA Football, NCAA Basketball, Other (e.g. Hockey, Boxing, Horse Racing, Tennis, UFC/MMA)
Entertainment: General (e.g. Oscars, Emmys)
Use the “Whom should we track?” button on the bottom-right of the page to contact us and we will get back to you promptly. Thanks!
We have previously analyzed how the NFL Draft Pundits (e.g. Kiper, McShay, Mayock) have done with their mock drafts (see here). We would now like to turn our attention to what we view to be a more interesting draft endeavor: figuring out how the pundits’ player rankings actually turn out. In other words, when Mel Kiper ranks his Top 5 QBs for this year’s draft, how accurate will those rankings be five years down the road?
We are actively discussing many different approaches to evaluate and compare players but we’d like to tap into the knowledge of our user base. If you are interested in this subject, please send us a note (just use the “Who should we track” button at the bottom of the page) and we will follow up with you. Thanks!
We are excited to announce some new features on PunditTracker.com:
User Rankings: We now post the three Top-Ranked Users on the Home Page as well as your individual ranking on the My Profile page.
Social Sharing: You can now share your predictions both on Twitter and Facebook. Just click the “Share” button on the rightmost column of the prediction table (My Profile page).
Public/Private Profiles: If you do not want your prediction history accessible by other users, you can now make your profile private by clicking on the Edit Info button on the My Profile page and then checking the Private box.
If you have not been making predictions on the site yet, now is a great time to start doing so! With new pundits being added each week, there are plenty of calls on the site that are currently open for voting. Recall that the three top-ranked users (with at least 25 graded predictions) will earn the right to become Featured Pundits on our website. The current “PT Challenge” ends on June 30, but we plan to make this a recurring contest each year (on a cumulative prediction basis). Therefore, we caution users against making a bunch of low-conviction votes simply to hit the 25 prediction threshold by June.
Technology (e.g. Apple’s next product)?
Entertainment (e.g. Oscars, box office proceeds)?
Let us know!
The 2013 Prediction Lists are already starting to trickle in, and we have put several up on PunditTracker.com, notably in Technology (which can be found in the Finance category for the time being). We also have Heisman Trophy predictions from the college football analysts — today is the last day to make your prediction!– as well as Bill O’Reilly’s thoughts on who will be Time Magazine’s Person of the Year.
Of course, the release of the 2013 Lists means that we are closing in on accountability time for all those 2012 Lists. Starting next week, we will review all these predictions from the likes of Karl Rove, Paul Begala, Byron Wien, and Doug Kass.
In our last post, we highlighted our preference for “second acts”, which we defined as repeated success in different environments. We focused on repeated success in that discussion. Here, we will delve into the second component of the definition: different environments.
As with broken clocks, which are right twice each day, many pundits make the same prediction over and over, knowing that they will be intermittently correct. The stock market offers an ideal breeding ground for this type of pundit, given its long cycles and binary outcomes (the market is either up or down). Those who are always optimistic on the stock market (known as “perma-bulls”) are right during bull markets, while those who are always downbeat (“perma-bears”) are right during bear markets. Both groups are anointed as gurus when the environment happens to be in their favor, but they are dead wrong during the other cycle. The behavioral elements discussed in our One-Hit Wonders post are again at play: recent, vivid, and unusual information are front-loaded in our brains. But another bias comes into play here: the “fundamental attribution error.”
The fundamental attribution error refers to the idea that when explaining successes and failures, we tend to overweight the role of the individual and underweight the roles of chance and context. For instance, in the early 2000s, much ink was spilled in lauding Terry Semel and Meg Whitman (then CEOs of Yahoo and eBay, respectively) as superstar executives. The alternative explanation — that these CEOs were running companies that happened to be at the right place at the right time — never received much thought. That’s not surprising, given that cause-and-effect, character-driven narratives are inherently much more appealing than chalking things up to good fortune.
Similarly, rather than considering that some pundits offer a static viewpoint which happens to coincide with an existing cycle, we elevate them to oracle status. We hope PunditTracker will help distinguish those pundits with the mental flexibility to provide insight in different environments from the broken clock crowd.
At PunditTracker, we place extra weight on second acts: people who demonstrate repeated success in different environments. Examples include former Apple CEO Steve Jobs and NFL coach Bill Parcells.
Just as half-truths are more dangerous than outright lies, the most dangerous pundit is the one who parlays a single correct call into guru status. While the media plays a central role in this game, our brains are culpable as well. Behavioral studies reveal that certain types of information have an outsized grip on our memory, including that which is recent, vivid, and unusual. This explains why we: (1) buy earthquake insurance after a (recent) earthquake, (2) believe that more people die from homicide (vivid) than from stomach cancer, (3) complain that we always get stuck in the slowest-moving line (unusual) at the grocery store.
The pundit playbook fully exploits this dynamic. To understand how, let’s place ourselves in the shoes of a pundit. What is the best way to make a call that meets all three criteria: recent, vivid, and unusual? Well, recent is easy—just make a lot of calls. That way, there will always be a fresh one out there. And vivid is just another word for bold. So if we make bold calls frequently, we are two-thirds of the way there. But how about unusual?
The beauty of the pundit playbook is that unusual takes care of itself. Bold calls are typically incorrect, so the correct ones are by definition unusual. Said differently, bold calls that turn out wrong are less likely to be remembered because they fail to meet the unusual threshold. Pundits are therefore entirely incentivized to churn out brash predictions, knowing that only the correct ones will stick in our mind. And because we tend to confuse ease of recall with frequency, we develop a warped sense of the pundit’s batting average.
This phenomenon is found in all walks of life, including sports. NBA guard Chauncey Billups, for instance, has been dubbed “Mr. Big Shot,” presumably because he has hit many clutch shots in his career. A closer look at the numbers, however, suggests that Billups’ nickname might be undeserved. Data from 82games.com reveals that Billups’ game-winning shot percentage between 2003 and 2008 was a paltry 16% (6 for 37), well below his 42% overall career shooting average. Our hunch is that a few of those game-winners were in high-profile, nationally televised games (vivid), thus sticking in the public’s mind and inflating Billups’ reputation as a clutch shooter.
The real danger comes when actions are taken based on a false premise. In this case, Billups’ inflated reputation is likely to garner him most of his team’s game-winning shot attempts, even though other players would be better options. Teammate Carmelo Anthony, for instance, had a sterling 48% game-winning shot percentage (13 for 27) over the same timeframe.
As anyone in marketing knows, once established, associations are very sticky. This explains how pundits are able to cash in for many years on the “one big call” they got right, despite sporting a terrible track record both before and afterwards. By playing the role of public scorekeeper, we hope that surfacing the data for everyone to see will help expose the one-hit wonders.