How Data is Driving Fantasy Sports Competition


When fantasy sports first began, the idea was to create a game that could capture the fun and excitement of running a franchise while remaining in your own living room. This hooked me to fantasy sports right from the jump. Those of us who yearned to grow up to be general managers of professional sports franchises turned to the only plausible alternative: managing these players in a game setting without them knowing about it.

Since fantasy sports captured the current landscape of sports, things began simply enough. Those statistics that fans cared about at the time were those used to score fantasy leagues as well. It only made sense. Baseball utilized the standard five categories for hitters: runs, home runs, RBIs, steals, and batting averages. Some leagues were even simpler than that, just accumulating home runs and batting average numbers.

Early basketball leagues just counted points, rebounds, and assists. Football leagues didn’t care about turnovers or defenses. They just counted the stats that were available to us in the newspapers each Monday morning.

But as sports statistics grew through the explosion and fine-tuning of analytics, so too did fantasy sports change. They had to adapt to stay current or else go by the wayside.

This adaptation wasn’t so much about altering the games, though. The games remain great. The idea cannot be ruined. Just settings need to be altered. Available data really opened the door up to this opportunity. Even if players and league commissioners of decades past wanted to revamp their leagues, they couldn’t. The resources weren’t there until recently.

That recent data boom obviously had a large impact on how real sports are played today. It also shaped how fantasy players and owners set up their leagues, run their teams, and shape their rosters.

Let’s take baseball as a starting point. The majority of leagues today continue to use a standard 5X5 scoring system or something close to it. The game hasn’t changed. However, owners know so much more information about their players. It shapes how decisions are made.

Slow starts for proven veterans are different than they once were. In the old days, I would see my second-round pick with four RBIs after April and be worried sick. What was wrong? Why wasn’t he hitting in clutch situations? Why was he choking? Today, knowledgeable owners know those are the wrong questions to be asking, and they know what the right questions are.

Over the years, we learned that RBIs are a pretty baseless baseball stat when it comes to determining an individual’s value. Instead of describing the hitter’s value, they point almost exclusively to the aptitude of the hitters in front of said player. Why the low RBI total? Perhaps the guys ahead of my star hitter aren’t getting on base. Why wasn’t he clutch? Because data this decade has told us that being clutch isn’t really a thing to begin with. Players are their own skill levels over a large enough sample. A low RBI total could be nothing but bad luck or statistical noise. These are all conclusions I could not have drawn years ago when fantasy baseball first began. We didn’t know enough.

Instead of freaking out and wanting to trade my recent second-round draft pick, I may instead be looking to trade FOR a player in a similar spot, hoping one of my opponents had that old-school, panicky mindset.

The same thing happened on the other side of the plate. Pitchers used to be judged almost exclusively based on their win-loss record and ERA. Now, an enlightened baseball fan realizes a win doesn’t always have a ton to do with the pitcher himself. Too many outside variables play into whether that win is won, including the rules of what it takes to accumulate a win in the first place. The same goes with ERA. Data advancements have given us better stats than ERA to determine the skill level and success rate of a pitcher.

The important distinction to make, though, is to know that fantasy leagues don’t have to completely do away with outdated stats. Leagues can still be fun that count wins and ERA as scoring categories. It is the owners that change to account for that. High ERA players from one year could be excellent draft targets the following year if their underlying numbers were of a high quality. A good FIP is a better judge of who to draft one year to the next than ERA is, even if ERA remains the actual scoring category!

In other sports, the jump in available data has had a smaller impact, but the changes in fantasy owners’ decisions are similar. Basketball data is so extreme and detailed that it is often hard to tell what could plausibly be used in a fantasy league and what is simply useful information. On-court, off-court data, five-man unit data, real plus-minus, and tons of other analytics give fans the fullest picture we have ever had of who is succeeding on the basketball court. But instead of using a messy stat like RPM as an actual fantasy scoring category, it shapes owners’ decisions as they attempt to collect the most points, rebounds, assists, etc.

The old categories remain. The wildest change my fantasy leagues have utilized is counting targets for football pass catchers. This isn’t an incredibly nuanced statistic, but it doesn’t have to be. It is another data point that tells us something we didn’t used to know. Old fantasy owners understood who garnered the most receptions in a given year, but they weren’t aware of how efficient receiver-quarterback combinations were in accumulating those receptions. And we couldn’t tell without watching game tape who the underachieving or overachieving players were based on their chances.

As data continues to develop in real life, fantasy sports will follow suit. But such switches don’t have to shift the foundation of the game we love. Instead, they simply shift focus on how we create and run our teams…just like the real general managers we still yearn to become.

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