In my most recent Detroit News column, I look at the American League landscape and find it devoid of all but one true contender.

It was kind of an argument that the Tigers could not sell their players and make a run at the playoffs. However, the Tigers did sell, a healthy move for their franchise.

The one AL team that I did like was the New York Yankees. In the 9 nine days since the column appeared, the Yankees have surged. They now have the best record in the AL and are 2nd in my MLB team rankings.

To read the Detroit News article, click here.

A version of this article appeared in the Detroit News on Monday, June 15th, 2015. The ideas on how humans view randomness apply far more widely than just Tigers baseball.

Do you remember April 20th? The Tigers had an 11-2 record and looked like an offensive juggernaut.

There were many ways to rationalize the success of the Tigers. Miguel Cabrera was finally injury free and back to his first ballot Hall of Famer form. Shane Greene allowed one earned run through 3 starts and looked like a Cy Young contender.

Now let’s fast forward to June 5th. The Tigers had just dropped their 8th straight game and had a 28-28 record.

There were also many explanations for the losing streak. Ian Kinsler was cold as ice, and the Tigers couldn’t get a clutch hit if the fate of the world depended on it.

It also didn’t help that 7 of these 8 losses came against the A’s and Angels, two underrated top 10 teams in my baseball rankings.

As fans, we find all kinds of reasons for winning and losing streaks. However, there’s an additional reason for these streaks not often talked about: randomness.

Let me show you.

Random flipping of a coin

In baseball, any team can win any game, even the Phillies over the Dodgers in 2015. Because of this uncertainty, it’s useful to have a probabilistic model for game outcomes.

We’ll do a simple experiment to see the relationship between the randomness of this model and streaks. Suppose a baseball team has a 50% chance to win each game.

To see how this average team’s season plays out, I flipped a 50-50 coin on my computer 162 times. The visual shows the results through 63 games.

Team average catches fire on game 19 of the season and rips off a streak of 10 straight wins. They lose a game but then win another 4 games in a row. Two of their young pitchers look like Cy Young contenders.

However, the bottom falls out at game 34. Team average can’t buy a clutch hit as they go 6-13 over the next 19 games. Fights break out in the clubhouse because of the lack of team chemistry.

Despite the losing streak, team average still has a strong 38-25 record after 63 games.

For the record, I made zero effort to find a random sequence with streaks. I generated this sequence once for an article I wrote a few years back. Randomness looks streaky.

The next visual shows the wins and losses for the Tigers through 63 games.

Both visuals contain quite a few streaks.

What the Hot Hand paper says about streaks

To understand how humans view randomness, consider a famous paper by Amos Tversky, a Stanford professor. In 1985, he published a paper called The Hot Hand in Basketball: On the Misperception of Random Sequences.

In the study, Tversky asked participants to look at a sequences of X’s and O’s that represented made and missed shots in basketball. Some of these sequences were generated at random and looked like the my coin flipping visual. However, only 32% of participants called this random shooting, while 62% called it streak shooting.

People tend to see patterns or streaks in randomness, just like you most likely saw patterns in the random sequence above.

The authors of the study also generated sequences in which it was more like to get an O after an X and a X after an O. Only with this increased tendency for an alternating sequence did more people call the sequence random shooting.

Perceptions of randomness from a young age

I’ve also done my own experiment on perceptions of randomness. At Summers-Knoll, a project based school in Ann Arbor, I brought a bag with a white and black chess piece into the kindergarten class.

I told the kids they would take turns picking a piece from the bag, which replicated the random flipping of a coin I performed on my computer above. But first, I asked them what they expected the sequence to look like.

Most of these five and six year olds wrote down an alternating sequence of X’s and O’s. A few children had a sequence of two X’s in a row. We tend to think of patterns in randomness at a very young age.

When the children picked out a chess piece from the bag, they saw that the sequence looked quite different from their expectation.

Another interesting thing happened during the experiment. After a few pulls from the bag, the children started chanting for the black piece to get picked. Cheering for randomness? That’s exactly what sports fans do. It’s ingrained in us from a very young age.

What this means for Tigers fans

From June 9th through the 14th, the Tigers played 5 games against the Cubs and Indians. They alternated wins and losses as you can see in the final 5 games of the Tigers visual above.

As humans, we view this alternating sequence random. Win some, loss some, just hope the Tigers get to the 88 wins they need to win the division. (The coin flipping experiment I did above produced 91 wins in 162 games.)

This perception changes drastically when the Tigers win 11 of 13 or drop 8 in a row. Their play no longer seems random, and fans go in search of explanations for the streak.

It’s fine to rationalize the causes behind these streaks. Baseball is far more complicated than the flipping of a 50-50 coin. However, remember that randomness alone would generate these types of streaks.