fbpx

Results Oriented Thinking

You know that saying “all’s well that ends well?” Well, I disagree. And so should you. Judging a scenario based solely on the ending is an example of results-oriented thinking, and it’s a logical fallacy that’s plagued multi-cellular organisms since the days of Primordial Ooze

If you’re familiar with the Limited Resources podcast, you might already be intimate with “being ROTTY.” But if you don’t know, results-oriented thinking describes when you forgo logic and instead use the individual outcome of an decision to determine whether your thought process was “right” or “wrong.” 

Winning doesn’t mean your strategy was right. 

Losing doesn’t mean your strategy was wrong. 

It’s true in life, and it’s true in Magic, 

Easy Example: Coin Flip

Let’s bet. I’ll flip a coin. If it lands heads, I pay you $200. If it lands tails, you pay me $100. 

We start. I flip once. It lands tails, and you pay me $100. 

In theory, you were supposed to have the advantage–at least, over the long run. But you lost and it doesn’t feel too good. Your hard-earned money is gone in an instant. All the “theoretical outcomes” in the world won’t change that. 

But the real test occurs when I offer the same bet again. Your brain might be clouded with negative emotion. The previous loss is weighing on your mind. Will you let prior outcomes affect your future decision making? The rational choice has not changed. The odds are still in your favor. 

You have a 50% chance of winning $200–that’s an expected value of 0.5 * 200 = $100. You also have a 50% chance of losing $100, for an expected value of -$50. Your total expected value is $100 – $50 = +$50. If we flipped the coin 100 times, you’d expect to profit about $50 * 100, or $5000. 

The choice should be easy. But after losing $100 right off the bat, your results-oriented brain might suggest you not take the bet. That’s irrationality in action.  

Bad beats hurt

Behavioral economics is the pop science du jour, and the subtopic of loss aversion is one of its most cited ideas. Loss aversion refers to the idea that people would rather avoid a loss than acquire an equivalent gain. The pain of a $100 speeding ticket is greater than the joy of winning a $100 lotto ticket.

Loss aversion helps explain the prevalence of results-oriented thinking. Animals are wired to avoid pain. Anytime there is a painful outcome at play, we tend to over-weigh that outcome. 

Imagine you’re playing Vintage Cube on Magic Online. Your Blue Control deck (obviously) is starting to turn the corner against your White Weenie opponent. It’s turn 5, she draws and plays Gideon, Ally of Zendikar—boom, you Counterspell. You draw on turn 6, drop your 6th land and slam Consecrated Sphinx. This game is yours.

But then your opponent pauses. A long, dreadful pause. Your heart sinks. 

She taps her lone Plains and plays Mana Tithe

Ouch. 

You lose the game, lose the match, and lick your wounds as you enter another Draft Queue. 

So my hypothetical question for you is: will you start to see Mana Tithe lurking behind every open white mana? Will you be haunted by one result and let it affect all future decision making? Will you ever tap out again?

Or will you include this one bad beat into a large matrix of possible outcomes, and evaluate each future situation on its own merits? Of course, getting Mana Tithe’d feels bad. But the real test comes next time around. 

Results-oriented vs. Learn from the Past

I jumped off a barn roof and broke my ankle. I learned my lesson. In the future, I won’t jump off barn roofs anymore.

“BUT! That’s results-oriented thinking! Jesse only decided that roof jumping was bad because he had a bad result. I just learned about this idea from Magic Online!”

Well…kinda. Maybe. Not really. 

The real world is not a coin-flip or a deck of cards. We typically do not have the luxury of knowing probabilities before an event occurs. Instead, we must rely on a combination of past results, common sense, analysis, prediction, estimated probabilities, etc. 

It’s ok to Learn from the Past.

If your Modern brew is constantly getting smoked by your friends’ red aggro decks, it’s ok to think, “I need some early interaction, and maybe some life gain.” Results can, and should, make an impact on your thinking. 

It only becomes a problem when you place too much weight on too few results. For example, think about this classic “new Magic player” trope: the nothing-but-lifegain deck. Every single card gains life, interacts with life gain, gives lifelink, etc. 

Why is this deck so appealing?

If you’re a new player, how do you evaluate the results of a game of Magic? You start at 20 life, you go down to zero life, you lose. You start at 40, go to zero, you lose. 

There’s a pattern here. Life loss = losing at Magic. Therefore, life gain = winning at Magic! You’ve solved Magic! Eureka!

While lifegain can work in some metagames (e.g. Soul Sisters in Modern), most seasoned Magic players understand that the above logic is flawed. Life is a secondary resource in Magic, typically overshadowed by mana efficiency and card advantage.

But it’s easy to understand how results-oriented thinking would push a newer player towards life-gain strategies. 

Bayesian Analysis

Bayesian analysis is used by statisticians to adjust subsequent behaviors by using prior results. For a crazy example, how might you find a submarine that tragically sank or a plane that vanished off the radar? In the case of the USS Scorpion or Air France 447, the answer is Bayesian analysis. 

Search crews start with all possible causes and all possible locations of the wreckage, then apply estimated probabilities to those causes and locations. The result of this task is a map (literally) of probabilities that point to the most likely locations to find the wreckage. A search path is constructed that starts with the most likely locations and works its way downward. And that path is constantly readjusted and recalculated as evidence is (or is not) found. 

Next time you watch Reid Duke or Marshall Sutcliffe or any number of good Magic players, check out how they use Bayesian analysis (even if they might not know it by that name). 

Every little move that the opponent makes provides new information, and the best players in the world constantly use that information to adjust their plays.  

Turn 1 Verdant Catacombs? Well, only certain Modern decks play that land. Therefore, certain decks are eliminated from the tree of possibilities. 

Turn 4, opponent leaves two mana open. So…they didn’t have a 3- or 4-drop? And they didn’t have another 1- or 2-drop? Or, what’s more likely, they’re holding an instant. 

In a typical Limited game, what does a “bad attack” signify? If you’re playing the best player at the card shop, you might respect the possibility that they are holding a combat trick. But if you’re playing the new guy, it might just be a bad play. You evaluate the attack based on its own merits and based on outside information. 

Derek Jeter’s defense

Since sports are cancelled for the near future, I’ll end on this cool example of results-oriented thinking. 

Derek Jeter, if you don’t know him, was the shortstop for the New York Yankees from 1995 to 2014. In January, he was voted into the Baseball Hall of Fame. Jeter will go down as one of the most successful hitters in the history of the game. 

But for the sake of this article, I want to focus on Jeter’s defense. If you ask a baseball fan about Jeter at shortstop, they’d conjure up an image of Jeter sprinting towards a ground ball, scooping it up on the run, and the jumping in the air to throw the ball to first base.

Jeter made that his “signature” play, successfully completing it in the most high-pressure situations. But in the modern age of baseball statistics, there are methods of evaluating defense that go beyond the highlight reel. 

For example, the statistic defensive runs saved tells us how many runs were prevented by Jeter’s presence on the field. A great fielder, presumably, would have a strong DRS impact. But Jeter’s DRS was one of the worst in the league during his tenure. The same holds true for other detailed defensive metrics–such as ultimate zone rating and range runs–both of which Jeter placed dead last among shortstops since 2003.

These stats require data mining. They aren’t obvious—unlike a running, jumping, flashy play. Observing Jeter’s highlights led many fans to a false results-oriented conclusion—namely, that he was a good defender.

It turns out, Jeter often had to rely on his athletic theatrics only because he was so slow at reacting to batted balls in the first place. 

This one Magic anecdote sticks in my mind. I was playing in a Fate Reforged team draft league, and one of my teammates had an absolute schoolboy crush on Return to the Earth. Go ahead, look it up. 

The problem started in his first few FRF matches (especially at pre-release sealed). Return to the Earth was his Derek Jeter. It destroyed a Citadel Siege in one match. It killed Silumgar, the Drifting Death in another match. So flashy! 

It was easy for my teammate to see the Jeter-side of the card. But it’s much harder to evaluate the card for all scenarios, whether flashy or banal. In all the matches against a normal curve-out midrange limited deck, Return to the Earth was dead weight (and not the good kind of Dead Weight.)

What’s the best way to avoid mana screw? Play a deck with all lands. 

Sounds dumb, right? It is. 

So be careful how you let results-oriented thinking affect you. 

For more articles, visit my blog: bestinterest.blog

Discussion

Scroll to Top