In my last article, I outlined a few skills I think are necessary to be a successful modern gambler. One of these skills I expect to be a bit of a new concept to most readers. In this article I wanted to elaborate on exactly what I mean by counterparty bias.
Many would-be sharp gamblers make a rather critical error. They make the assumption that the betting opportunities that they are presented with are generated in an unbiased and perhaps somewhat random way. An example of this assumption in poker is that your opponents receive random cards and they play those cards according to a predictable strategy. Or in sports betting, an example assumption would be that the more your model differs from a market line, the bigger your edge because the market line is derived in a way that’s unbiased with respect to your model.
This assumption is almost always wrong in gambling, and sometimes it’s very wrong. The reason is that there are two phenomena that tend to bias against you the set of gambling opportunities that come your way.
First is the direct counterparty effect. This is the person you are betting against. With the arguable exception of slot machines and video poker, there is another person on the other end of your bet. And presumably if this person is offering you the bet, it’s because they think the bet is good for them. In general, the sharper this person is, and the more they’re willing to wager on the bet, the greater the chance that you happen to be mistaken about how good the bet may be for you. That is, sharp counterparties willing to bet real money will tend to present you with worse-than-average gambling opportunities. If you don’t take this into account and you trust your own analysis too much, you will tend to bet the most money in precisely those times when you are mistaken.
The second is the competition effect. Again, almost no matter what you are gambling on, you will have competition. These are other people who are also looking to make the same sort of good bets that you are making. The very best bets often get snapped up very quickly by the competition. This tends to bias the surviving betting opportunities against you. Again, depending on how sharp and how hard-working your competition is, this bias can range from mild to very significant. And again, with sharp competition you will often end up in a situation where the bets that look best to your analysis are actually just the bets that you are most mistaken about.
In poker, the counterparty effect is particularly strong in heads-up and short-handed games. If you are a good poker player, it is perhaps not hard to find opponents weaker than you who will play you heads-up or short-handed. But it’s much rarer to find a weaker opponent who is willing to give you all the action you want for as long as you want. It’s not impossible. But if all you know about your opponent is that you think you have an edge, and your opponent is willing to keep playing and playing and playing, the chance that you’re wrong and actually playing at a disadvantage goes up. Over time those you truly have an edge on will tend to quit you. So eventually there is a strong survivorship bias that will increase the chance that your long-playing opponents actually have an edge on you.
The competition effect also applies to poker, particularly in full-ring games. It’s in play any time you have a situation where you are thinking about playing a hand not because of its intrinsic strength, but because of the situation. For example, say everyone folds to you and you are one off the button. You think the blinds are likely to fold, so you raise light.
Well, everyone who folded in front of you had first crack at this opportunity and passed. It doesn’t mean that you’re wrong to raise light, but if the opportunity were truly juicy, there’s a chance someone would have taken a shot at it before it came to you. The fact that no one did is what causes the bias in this scenario. These opportunities that come to you after others have passed will all tend to be worse on average than how you may otherwise assess them.
This is a strong effect in other gambling disciplines such as advantage slot and table games play, sports betting, trading, and so on. The opportunities that survive despite competition will tend to be worse than they may appear—and they may be much worse.
This is also a well-known effect in many other non-gambling disciplines. For example, it’s a well-known phenomenon that in sports, players who are free agents and get signed by a new team tend to perform worse than equivalently-rated players who resign for their original team.
This is because before a player becomes a free agent, usually his current team will have an exclusive chance to sign the player to a new contract. Even for players who insist on going to free agency, nearly all will consider returning to their original team for the right price.
Obviously a player’s original team will have the most information about him since they see him in practice, in the locker room, and so forth. The players who switch teams are those who—for whatever reason—their original team refused to offer a market-competitive contract. These players tend to be biased to be somewhat worse than they might otherwise appear due to the competition effect.
Many aspiring gamblers spend all their time thinking about how to determine if the bets are profitable or not. Their approach focuses on building a mental model that is right more often than not at predicting which bets are profitable and which aren’t.
But the problem with this approach is in the “more often than not” part. The implicit assumption here is often that the opportunities that come your way are unbiased, and so if you just bet your model, you’ll win. This assumption isn’t correct, however. The opportunities you get will be biased against you due to the counterparty and competition effects. How strong this bias is depends on how sharp the other people who have access to the opportunity may be.
In situations where the bias is strong, if you blindly bet your model you will find that you can bet very little or no money on the good bets you are correct about, but you can bet a whole lot of money in the situations where you and your model happen to be wrong. Obviously if you bet little on your successes and a lot on your failures, you will not make money.
If you want to be a good gambler, you must always keep the counterparty bias effect at the front of your thinking. ♠