It would be hard to find someone who hasn’t heard of fantasy football. The resemblance between real football games and DFS is so striking that many people cannot help but wonder: do real football players perform better in daily fantasy sports than in the real world?
Football players do not perform better in fantasy sports than in real life. Daily fantasy sports do not capture all statistics a player accumulates.
But that’s not all! If you want to learn more, you must stay until the end. I will go over the reasons why the above statement is true. So, please keep reading.
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Do Real Football Players Have The Same Stats In Games Like The Real World?
The short answer is yes. But the yes here is not absolute. There are factors at play that can be true or false depending on the players. So, sometimes what is predicted can be wrong.
As a football manager, you’d keep a close eye on all the games of a season. You’ll have to read the news and keep things up to date. Taking all that into consideration, you will form a team, compete in virtual tournaments, earn points, win and get that prize money.
One of the most prominent ways you can learn about the best players is through stats. Stats are indicators that help you determine if this player is worth the price. The stats for football are: touchdown, interception, 25 yards passing, and 10 yards receiving. These factors might differ from website to website. But in general, these are not found.
FFtoday is a great site for player stats. They update daily, weekly, monthly, and all seasons. You will find those factors as I’ve mentioned above. There are other factors as well. These are given below.
- Speed (SPE): This regulates a player’s max speed when running. It considers dribbling as well and determines how fast they are with or without it.
- Acceleration (ACC): Acceleration is the player’s time to reach that top speed. Two players might have the same speed but possess different acceleration.
- Stamina (STA): It shows how fast the energy of a player is depleting. If a player maintains his top speed for only a brief period then his stamina is low.
- Ball Control (CON): This is an important one. It establishes the quality of a player. His skills, dribbling performance, touchdowns, and overall control.
- Strength (STR): If a player is blocked or tackled this stat is useful. It shows how much a player can withstand this pressure and still run with the ball.
- Passing (PAS): Passing is essential for a rugby player. This factor shows a player’s accuracy when he passes the ball to another player.
These days many rugby managers are available online. The apps are made with focus and accuracy. And, managers motion-track players in real life to ensure proper stats for them. So, you can say that stats do determine the overall quality of a player in real life. Moreover, they become the bread and butter for choosing the ideal player.
Do Real Football Players Perform Better In Daily Fantasy Sports than In The Real World?
As mentioned before, no, they probably don’t. Because data science has paved the way for improved predictions. Times have changed and people are boycotting the old ways.
I’ll now talk about how people used to make predictions for fantasy football. And though they are not completely gone, something new has been introduced. This changed the way people looked for players in the real world and fantasy world.
How Fantasy Football Predictions Are Done
In the past, people used to be up to date on news channels, and online sports sites. But this type of on-the-spot analysis didn’t help much. In the short run, people had more luck, but in the long run? It wasn’t that good.
Many fantasy football analysts, like Josh Hermsmyer, dug deeper into factors that did not register on your typical news channel. News channels cared about touchdowns, speed, and the other factors that I’ve mentioned before. While they are an integral part of making a good player, it’s not everything.
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Hence, data science was introduced. It was first done in 2002 for baseball. An American team known as the Oakland Athletics took a data-science approach. There was a movie made for this known as Moneyball. So, this team counted the hidden factors that predicted a player’s efficiency. This made for much better tallies than your average stats or scoreboards.
So, in the past, predictions were made from player averages. But this soon changed after the baseball incident. Wins after wins came down for the American team after they followed it. So, teams in football started to apply the data science approach. But what is this approach? How did it differ from normal stats from news and other sites? If you want to know, then stay tuned!
The Data Science Approach
It is not easy to put this into words, particularly with math and algorithms. But I will try my best to explain it in easy terms. I won’t show the math but the hidden factors they took into consideration. So, here they are!
- ‘’Usage’’ of the data was first termed. Usage means opportunities. Things that truly matter when it comes to football. Things that didn’t fit the general criteria and look useless.
- The number of throws was a prominent target for usage. Normal channels usually tallied catches. Catches were few and far between for a player. If you count catches there will be only 3-4 catches per player. But the accuracy and number of throws determine an ideal player in the long run.
- Useless things were also considered in choosing players. Things like attitude, throw style, face, did not affect the games at all. Yet, this was given a lot of priority. These are eliminated at the data approach.
- The quality of opportunities is also measured. For example, let’s say a player had a bad game count for three weeks straight. People watching this on the news might avoid this player completely. But after analysis, the data shows that he had the most throws, and hit the most targets. He was doing the best in offense and defense. But he was plain unlucky.
- The WOPR method was introduced to see these hidden factors more accurately. It counts player performance through target share and air yard share. Combining these two the system made future predictions for the true efficiency of a player.
Note: The percentage of all team air yards directed towards that one receiver is known as “air yard share.” The distance between the line of scrimmage and the point of a catch is measured in air yards.
DFS (daily fantasy sports) went mainstream in 2015. From then on, teams started to look for more of these hidden factors. And that accelerated the data approach method. Many graphs, algorithms, and value models were created, and they still are. You can find good sites like these online. Some of them are PFF, FO, and RotoViz.
Conclusion
So, do real football players perform better in daily fantasy sports than in the real world? Now you know the answer. By now, you should also know how the fantasy world works and how relentlessly analysts try to make more accurate values. Thank you for reading!