Written by: Robert Rotty – Staff Writing Intern (@GrandstandRotty)
An often debated topic in the sports industry is the concept of hot and cold streaks. And if you’ve ever played sports, you probably believe this to be true. You get this renowned sense of confidence after you strike a batter out, drained a 3-pointer, sacked the quarterback, etc… Even if you haven’t ever played a game in your life, you can still see it happen.
Take the 1977 World Series for example. Reggie Jackson hits 3 home runs on three consecutive pitches off of three different pitchers, and ended up hitting 5 home runs in the span of 6 games. You’re going to try and tell me he wasn’t confident after his first 2 home runs in game 6? You hear it all the time too, as teammates yell out, “Stay hot kid!” when a batter is at the plate. Despite all of this, there has been numerous studies that test this theory of hot streaks being real.
This theory is called the hot-hand fallacy. Originally applied to gambling, it meant that gamblers thought they would continue to win, “based on the idea that having already won a number of bets improves the probability that they will win the next bet or the next number of bets.” (business insider) This is poor logic. We know in gambling each event is independent of each other. For example, in the game of Craps. Unless the dice are loaded, then each roll is independent from the last.
Although streaks of randomness may occur (which could involve rolling a streak of 7’s), that in the long run the percentage of each number rolled will regress to the statistical average. Take the chance of rolling a seven. With two dice, there’s a 1/6 chance that a seven appears, or a 16.7% chance. Although someone may roll a 7 in 8/10 of their last rolls, we would still expect that in 1000 rolls of the dice, there would be about 167 occurrences of a 7 being rolled (1000 x 16.7%). This concept can be transferred to sports quite easily, but with one main difference: the psychological effect that success has in a player’s mind.
One of the most famous papers that covered this topic is The Hot Hand in Basketball: ON the Misperception of Random Sequences by Thomas Gilovich of Cornell University and Robert Vallone and Amos Tversky of Stanford University. Throughout several experiments and surveys, they concluded that being so called “hot” does not explain the whether or not the next shot was going to go in the basket.
Since this study, there has been conflicting reports and other studies done that back up this claim, while others refute it. But this concept of being “hot” seems to be widely accepted by many people. We can see it occur both in video games (NBA Jam) and Beer Pong. A player starts to “heat up” being making two shots in a row, and then becomes “on fire” once a third consecutive shot is made. After this, it seems like they can’t miss. What is often overlooked, however, in this situation is the cold streak that usually precedes or follows this.
Initial thoughts may be that there isn’t always a cold streak, but there has to be in almost every case. To explain this, think about dice rolling. As I mentioned before, in the long run the percentage of each number rolled will regress to the statistical average. So whether or not you believe in hot streaks, this remains true. This can be applied to sports for a player’s career average in any given category, but let’s use batting average for example, and create a hypothetical situation with two players. Here are their statistics over the past week on 25 plate appearances each:
Player A: AVG: .375, 4 Home Runs, 12 RBI
Player B: AVG: .120, 0 Home Runs, 1 RBI
If I asked someone based off of this sample alone, they would almost always say that Player A is a better player, and rightfully so. But obviously we can’t draw conclusions based off of one week of data. A large sample size is needed to give us an accurate picture. So let’s say that in 1000 career plate appearances, here are each of their numbers:
Player A: Career AVG: .240, 15 Home Runs, 60 RBI
Player B: Career AVG: .280, 35 Home Runs, 100 RBI
Now most people would say that Player B is a better player in this situation, and rightfully so. We can see that Player A is significantly over performing to their career average, while Player B is significantly underperforming. Unless we can project that Player A has significantly progressed and Player B has significantly regressed (which we can’t when holding all other factors constant), then they are both due for regression back to their career averages. For Player A, this involves underperforming to their relative career average, while Player B has to over perform for a period of time to come back to his career average. Knowing all of this information can lead to a significant edge in Daily Fantasy Sports.
In general, almost everyone loves to target players who have been performing well over their last few games. This makes sense, and can be in part contributed to a psychological razor (a general rule that can help explain certain phenomenon). According to Occam’s Razor, usually the simplest explanation is the better explanation for any given problem. Also known as the explanation with the least assumptions. In Daily Fantasy Sports, this is going to be picking the player that has been doing well, not the player that has been terrible in his last 5 games. When picking the hot player in this situation, however, another psychological razor comes into play. This is Hanlon’s Razor.
Hanlon’s Razor states that, “Never attribute to malice that which is adequately explained by stupidity.” This basically states that people aren’t inherently making bad choices, they just make the wrong choices because that they aren’t smart. Applying this to DFS, means that people more often than not are just going to take the guy that’s playing hot, because they ignore the outside factors of matchups and other things that may affect a player’s performance. This can lead to a massive gap in the ownership between players, and allow us to get a high upside plays at low ownership and a depressed price point.
And besides psychological razors, social proof plays a large role in this discrepancy of the players’ ownership. People seem to look at tons of different articles and write ups about a given slate, and don’t rely on their own research. Many articles will say something like, “Player A has a tough match up tonight, but he’s been playing so hot lately that it doesn’t matter. His price has been rising lately but he’s still a good play.” And “Player B has a great matchup tonight and his price has fallen recently. He’s cheaper than usual, but he’s hard to play.” Because everyone sees that nobody is going to own Player B, they don’t want to either. But we should be targeting these players in tournaments. We know that eventually this player will start to hit again, and it could be at any time. For instance, situations like this are common occurrences:
Player A is a left-handed batter, and in his matchup tonight he faces a tough lefty pitcher in a ballpark that favors pitchers. Generally, this is a situation to avoid. But since he’s been playing so hot lately, he comes in at a price of $4,000 tonight, and ends up with a 15% ownership. His price is usually around $3,500.
Player B is a right-handed batter, and gets a matchup against an average left-handed pitcher. He’s playing in a ballpark that favors hitters. This is a great situation to target. But since he’s been playing so poor lately, he comes in at a price of $4,000 as well, and ends up with a 3% ownership. His price is usually around $4,500.
This is a great opportunity to target Player B when a very small amount of people will be on him tonight, due to his cold streak. Recency Bias also factors in, as anyone who rostered Player B during his bad week will not want to start him again. As mentioned before, this is for tournaments only. In cash games, we want to look towards the player that has been playing well, has a good matchup, is in the right ballpark, etc… This is an oversimplified example, but it gets the point across nicely. It won’t always be this black and white, but it should become evident to you once you start researching a given slate.
If all of that just went over your head, here’s the simplest way to put it. People are willing to start a player that is overall worse at hitting because they are on a hot streak. Why not take the better hitter at a depressed ownership? The better hitter is often cheaper, especially if they haven’t been producing for a while.
Now this example is easily related to baseball, but the same concept can be seen across the daily fantasy sports industry. Players that score 3 touchdowns in a particular week are often highly owned next week, regardless of other factors. The same goes for a player that unexpectedly drops 40 points in a basketball game, or a hockey player that has a 4-point night. Don’t get caught in the trap of hot streaks or great single-game performances. Look beyond this in tournaments and find recently underperforming players in good matchups to give yourself an edge. It may not always pan out, but when it does, you’ll be finding yourself sitting at the top of the leaderboards instead of just barely cashing.