The Professional Effect

In a recent discussion with a friend, I talked about why the ability of polls and  markets to predict political outcomes seem to have taken a beating as of late. I described an effect whereas the more faith people place into a certain predictive tool and gain more knowledge of it, the less reliable it becomes. I vaguely remember hearing about it somewhere but when pressed for an academic source, I came up short. I couldn’t even give a name for it, which leads to the disturbing possibility that I simply made it up.

However, weeks later, I found a name for it in a rather unorthodox source: this video on the video game Hearthstone. At around the 11 minute mark, Trump talked about something he named the “professional mage effect”, which I shortened to simply the professional effect, which I believe is one of the main causes in the crumbling of the accuracy of polls and other statistical tools as of late. Trump himself summarized the effect fairly succinctly in the video, but for those of you who don’t know the language of Hearthstone, I will give you an explanation.

In Hearthstone there are nine playable classes. Each class has a distinct set of accessible cards and hero abilities. In the current incarnation of the game, the mage class was given several new cards that gave it a significant advantage over other classes. This meant that every time it was possible to select a mage, people tend to select mage; the difference in win rate between mage and the other 8 classes was staggering. As a consequence, Blizzard decided to introduce some changes to try to balance the game, most notably removing several problematic cards for mages. However, after a month of the changes, it seems that mage still maintained a sizeable lead. Blizzard explained this with the ‘professional mage effect’, where strong players who tend to read the statistics instead of choosing at will or from word of mouth, tend to still prefer mage because its previous high win rate and its current average win rate still gives an above average win rate; and since these players tend to be the strongest, their superior skill allows them to win more, which is conflated with the class being strong.

It appears that a similar phenomenon is at play when it comes to high frequency trading. Whenever too many algorithms use similar methods to choose stocks, a slight advantage is exaggerated and causing many buyers to buy into it, significantly overvaluing the stock. This then creates a lot of uncertainty in the valuation of stocks and makes the market rife for bubbles.

This seems to give a rigorous justification that a diversity of ideas is quantitat


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