Swarming MLB: Midseason Report


Swarm Intelligence evolved in order to help organisms make life-or-death decisions. Fish, bees, birds and countless other animals are faced with complex, multi-variable problems like where to put their hives and find food. These problems are so complicated, in fact, that no individual bird or bee could even conceive of the problem,  much less solve it consistently. Swarming allows these comparatively simple organisms to amplify their intelligence and optimize their decisions, but the process took eons to evolve.

Here at Unanimous A.I., we don’t have that kind of patience. So, while our Swarm AI platform brings the power of Swarm Intelligence to humans, allowing them to amplify their intelligence, we’re constantly revising our methodologies to increase the efficacy of that amplification. In other words, the last three years of research have provided ample evidence that swarming allows groups of people to perform better, so we’re now focused on maximizing those gains. Followers of this blog know that Major League Baseball provides a perfect test-bed for these experiments, and our midseason results provide a striking example of how swarming transforms performance.

Predicting the winner of MLB games is especially difficult early in the season, when little is known about the teams and players. Perhaps as a result, the MLB Swarm’s first quarter performance was in line with its two major competitors. Our researchers track three data sets for comparison: the swarm’s, the average individual’s, and the most popular answer from the survey given to all participants. Through the first quarter, all three records were within three games of a .500 record, essentially an even race.

But, as the season progressed, more reliable information about the teams and players was made available. And as we’ve often seen, the presence of better and higher quality data empowers the Swarm AI to truly unleash the intelligence of the group.

35 Games Above .500

So, how is Swarm AI’s performance at the midpoint? In a word: remarkable. The MLB Swarm is currently 35 games over .500! That’s the kind of record that gets you kicked out of a sportsbook.

 Curiously, the average individual and most popular answer records improved by just 10 games in that time, a far smaller margin. This supports two hypotheses. First, that some small improvement can be expected as 2017 iterations of the teams becomes familiar to the group, and second, swarming can yield a stunning amplification of intelligence. In short, at this point in the season, the Swarm AI is not only separating itself from its individual and crowd competitors, its running away from them.  You can see a breakdown of the improvement in the chart below.


What’s next for the Swarm? Individual breakdown and analysis of the MLB Swarm’s output has produced some memorable victories at the sportsbook, like last week’s six team parlay. But, as we said at the top of this post, our researchers are always looking to improve the efficacy of our Swarm AI platform. On our end, that means constantly tweaking the algorithms and improving our methodology. But, we need your help. too. As we’ve seen time and again, the swarm can only amplify the wisdom, insight, and intuition of the group that composes it. As we saw at the Kentucky Derby last year, when a group of twenty enthusiasts nailed the “holy grail of gambling“, the right group can produce incredible results.

Think you have what it takes to help our MLB Swarm? Please click the button below to join our growing group – thanks! 

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