Bet the Election

Nate Silver's FiveThirtyEight, which came closest to predicting Trump's win in 2016 and has the best track record among modelers, gives Trump just a 12 percent chance.

But people who "put money where their mouths are" give Trump a better chance: 37 percent.

That's according to roughly that often., the website I created with Maxim Lott. It tracks multiple betting sites around the world.

Though 61 to 37 percent seems like a giant lead for Joe Biden, 37 percent means Trump is likely to win one-third of the time.

Four years ago, most bettors were wrong about Trump and Brexit. I assume they learned from that and adjusted their 2020 bets.

Because betting is a better predictor than polls, pundits, statistical models and everything else.

ElectionBettingOdds.com has tracked hundreds of races. When bettors think a candidate has a 37 percent chance -- they really do win roughly that often.

A research scientist at Amazon concluded that in the last presidential election, ElectionBettingOdds.com beat all other existing public prediction models except for Nate Silver's polls-plus model.

Silver says: "Betting markets are populated by people with a sophomoric knowledge of politics... Traders are emotionally invested in political outcomes." Also, "Markets (are) not super liquid... way different than sports where you have a much more sophisticated player base and more liquidity."

But our site takes odds from betting sites in Europe, the U.S. and a cryptocurrency-based exchange. More than $200 million has been bet.

As Silver says in his excellent book, "The Signal and the Noise," "A lot of smart people have failed miserably when they thought they could beat the market."

Overall, bettors have the best track record. Last election, The New York Times' "expert model" had Hillary Clinton ahead 85 percent to 15 percent. The Princeton Election Consortium gave Clinton a 99 percent chance. (Now they give Biden 98.2 percent.)

Daily Kos had Clinton at 92 percent. Huffington Post had 98 percent. Those two stopped operating after that embarrassment.

Silver is one modeler who's often beaten the market. In 2016, he gave Trump the highest odds, and in 2018, he was the most confident that Democrats would win the House.

On the other hand, his FiveThirtyEight model was confident Democrats would win Florida's and Indiana's Senate races, making Democrats 70% favorites in both states. But Republicans won. Bettors were closer to predicting the actual results.

Bettors do well because they consider many things not easily captured by polls and statistical models.

How many mail-in ballots do not get counted? In the New York state primary this year, 20 percent were disqualified for irregularities.

FiveThirtyEight "built in an extra layer of uncertainty this year because of the possibility that the pandemic will disrupt usual turnout patterns." But bettors believe it's not enough.

In 2016, polls showed Clinton well ahead in Wisconsin, Michigan and Pennsylvania, but pollsters hadn't questioned enough voters without college degrees. Who knows what mistakes pollsters are making now?

But our site takes odds from betting sites in Europe, the U.S. and a cryptocurrency-based exchange. More than $200 million has been bet.

As Silver says in his excellent book, "The Signal and the Noise," "A lot of smart people have failed miserably when they thought they could beat the market."

Daily Kos had Clinton at 92 percent. Huffington Post had 98 percent. Those two stopped operating after that embarrassment.

Silver is one modeler who's often beaten the market. In 2016, he gave Trump the highest odds, and in 2018, he was the most confident that Democrats would win the House.

Bettors do well because they consider many things not easily captured by polls and statistical models.

How many mail-in ballots do not get counted? In the New York state primary this year, 20 percent were disqualified for irregularities.

FiveThirtyEight "built in an extra layer of uncertainty this year because of the possibility that the pandemic will disrupt usual turnout patterns." But bettors believe it's not enough.

Well, betting and voting are two slightly different things.

I was watching one of Bill Whittle's videos last night, and in it, he discussed a famous incident that happened at the world fair in 1904.

One of the attractions was a large ox they were giving away. You could guess the weight of the ox and write it down on a piece of paper. Whoever got the closest guess to the real weight won the ox.

The did a statistical analysis on the guesses (they had all the names and addresses) and were able to find out some interesting data.

The best guess was the mean of ALL the guesses submitted. The mean of all of them together came within a pound of what the ox actually weighed.

Using their researched data, they divided the people who submitted guesses into classes such as "Farmer", "Butcher", "Rancher", "Office worker", "Factory worker", "Housewife", and so on.

They found and interesting phenomenon-the average of no single grouping's guess was as accurate as the mean of the whole.

Even more interesting is...the people who should have been able as a group to guess better...didn't. The experts, people who SHOULD have been able to make on the whole more accurate guesses at the weight of the ox, missed it, and in some cases, missed it worse than other groups.

One would think Ranchers who were well versed in evaluating flesh on the hoof, or Farmers, or even Butchers, would be able to guess more accurately, didn't.

This oddity engendered studies, many of them to replicate and study this phenomenon. They found the same type of result again and again, replicating the initial one, the experts rarely, if ever, did better at making guesses on something they had expertise on.

In analyzing it, they realized two things had to happen for this to hold up:

The people in the population had to be a diverse group. They had to include everyone available from the town drunk to the Mayor, housewives, maids, stevedores, accountants, railway workers, men, women, etc.

They had to be unbiased. That is, they could not be exposed to "experts" would opine openly...it had to be guessing in a vacuum.

They found that if the audience was not representative of a complete cross section (that is, they only included farm workers, or only included miners), but they also found that if "experts" were allowed to influence the guessers...people would change their guesses because they became "biased".

This is a very meaningful type of study, and tells us why Capitalism works where a huge cross section of people vote for goods and services using their hard-earned dollars as ballots.

It also tells us one of the reasons why socialism does NOT work-a small group of experts typically does not make judgements as accurately as a large and varied group that is a real cross section.

There have been studies done and redone since the initial one, that all validate it.

I think all of those things apply here...to the polling, to the election voting, to capitalism vs. socialism, and to the economy in general.

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