How To Understand Winning Streaks
Are winning streaks the result of luck or the result of superior talent? Are winning streaks more random than we might suspect? In this article we discuss winning streaks, when to follow them, when to avoid them.
An Introduction to Winning Streaks
Whether we are having fun with our friends predicting who will win the next match, playing fantasy football, or placing a bet on this weekend’s matches, we try to look for information and patterns that will give us potential insight or an edge for us to reap personal or even financial reward. In this article we will look at some statistical and psychological perspectives on the topic of winning streaks and psychological momentum. Is there truly such a thing as a winning or losing streak? And is there a way to predict them?
Leonard Mlodinow is a teacher of randomness at Caltech who published an article - The Triumph of the Random - discussing why baseball player Joe DiMaggio’s record 56 game hitting streak may have been as much a matter of luck as it was a display of skill.
Mlodinow discusses the psychological disadvantage humans have when they attempt to predict outcomes, especially at the absence of a true pattern. He gives the example of a series of green and red flashes presented to an individual that alternate randomly but with the red flash occurring twice as often as the green flash. It’s then posited—what’s the strategy to predict the next flash?
Mlodinow gives two answers:
- A non-human animal would more often than not guess red.
- A human will more likely than not attempt to notice a past but false pattern.
This is an evolutionary aspect of human psychology as we tend to notice patterns and interpreting them for our survival i.e. seeing a garden hose move and just briefly being frightened that it may be a snake. Though this has been beneficial for our survival, this can lead us astray when trying to predict future outcomes.
Mlodinow further adds this interesting gem to looking at randomness. If we took a graph of occurrences; say a series of wins, losses or draws having the idea of randomness in mind, we’d probably think the graph looks scattered without any real sense of stability or consistency.
But! An example of 100 coin tosses will yield a 75% chance of seeing a streak of 6 or more heads/tails and a 10% chance of seeing a streak of 10 or more.
While given these stats, Mlodinow is quick not to easily dismiss the role of talent in the case of DiMaggio for example. Factoring in his lifetime batting average of .325, this gives DiMaggio’s side of the “coin” an increased weight of 75% in his favour. Moreover he adds the human tendency for the need of control and deeply associating with progress and triumphing over the odds.
He showed this with an experiment in coin flipping among a group of Yale students who understood the randomness of the action but when asked if distractions or practice would influence the outcome, quite a few responded that it indeed would. If anything, it makes me think twice if an Ivy League education is all it’s really cracked out to be.
His concluding example adds in the subtleties of season-to-season performances. Using a computer analysis, they compiled randomly generated seasons from 1871 to 2005 from actual player statistics of each year and repeated the process 10,000 times (or 10,000 alternate universe baseball histories). They found 42% of the simulated alternate histories matched or exceeded DiMaggio’s streak with the longest being 109 games.
Other studies looking into the concept of psychological momentum have also been inconsistent and mostly have come from the perception of those watching the action. It’s been attempted to use the physics definition of momentum of velocity multiplied by mass wherein velocity is described as a “big play” and mass as “game importance” and “emotional investment”. Even while showing short clips of a game to a number of “fans” do indeed lend to the support of this model, the overall end result did not always follow suit.
There are limitations to these studies especially when measuring “big impact” moments as opposed to say a collective of “small impact” moments and ambiguity with the terms of psychological momentum and flow/zone.
Regardless of these things, it’s quite apparent that understanding and predicting momentum from game to game is indeed complex but it most definitely should be kept in mind the strong influence of chance.
If randomness has anything to teach us, it’s to be weary in certainty when comparing two patterns (WLWW or WWLL) and attributing false meanings to which one will indeed come out the victor.