I’d like to explore an interesting intersection between traditional sports and esports: The importance of data analysis. Specifically, let’s talk about Moneyball / baseball and esports / the video game Overwatch. Hundreds of millions of dollars have already been invested into Overwatch’s one-year-old competitive league, so I would make the argument that the league’s teams take data analysis very seriously.

The sports term “Moneyball” has become distorted over the years. These days, many people associate Moneyball with any situation where a team performs data analysis more advanced than counting fingers. It’s not necessarily anyone’s fault; it was bound to happen when the term entered sports lexicon.

The spirit of “Moneyball” involves using data analysis (not traditional scouting) to find and sign undervalued players (not necessarily the best players).

In respect to the Overwatch League, I’ve seen the term “Moneyball” used to describe what coaches, analysts, and teams are doing. DC’s WizardHyeong, Toronto’s Barroi (see below screenshot), and the Boston Uprising have all been name-dropped by fans and/or esports journalists. Random controversies aside, I’m sure these people/teams are doing great work - but let’s not mistake what they’re doing as a proper “Moneyball” approach.

A Google search of “Moneyball” and “Overwatch”.

The original “going Moneyball on the league” involves overperforming in the regular season and falling short in the playoffs. :)

Feel free to skip parts 1 and/or 2 if you’re already familiar with them.

1. What is the Overwatch League (OWL)?

Overwatch is a video game developed by Blizzard Entertainment, a division of Activision/Blizzard. The game’s competitive league had its inaugural season in 2018 and was set up to mimic an American sports franchising model, with team buy-ins set at roughly $20 million.

The OWL has also received lots of traditional media attention thanks to Blizzard’s aggressive PR push, sports media’s continued expansion into esports, and traditional sports groups investing in teams.

The game is played 6v6 and there are 29 playable characters (as of writing). The OWL features a regular season and playoffs. All of Season 1’s teams lived in the Los Angeles area and competed at the Blizzard Arena, but Blizzard’s eventual plan is to move teams to their assigned city and set up home/away matches. Check out the OWL Wikipedia for more info.

The OWL’s Dallas team name and logo. Like most OWL team names and logos, the Fuel’s logo is inoffensive and vaguely specific to the region.

Texas teams love oil-themed sports teams; the NFL had team named the Houston Oilers for nearly 4 decades. And yes, their logo was literally an oil rig.

The American Basketball Association’s Texas Fuel. Seeing a pattern yet?

2. What is Moneyball?

Moneyball is a book written by Michael Lewis, a non-fiction writer who has a knack for turning true sports and financial stories into engrossing books. For those who haven’t picked up a book since high school, Lewis’s Moneyball, The Blind Side, and The Big Short (note: these are Amazon affiliate links) have all been turned into critically acclaimed movies.

“It began, really, with an innocent question: how did one of the poorest teams in baseball, the Oakland Athletics, win so many games?” — Michael Lewis, Moneyball

Moneyball traces the steps of Billy Beane, the General Manager of baseball’s Oakland Athletics (dubbed the A’s for short), during the late 1990s and early 2000s.

Major League Baseball only had a soft salary cap and teams with deep pockets could spend way more on player salaries than poorer teams. In 2000, the difference in spending between the teams with the highest and lowest payrolls was $76 million ($92.5 million to $16.5 million). The A’s had a $32 million budget that year, the 6th lowest in the league (out of 30 teams). They also had the 6th best regular season record.

Scott Hatteberg’s signing is one example of Moneyball tactics at work. He features prominently in Lewis’s book. Image source.

Moneyball isn’t magic — it’s math.

“The idea is that we were seeking undervalued assets in an inefficient market. What we tried to do was find value in areas where most people weren’t necessarily applying the right values. And we did that cost-effectively.” — Billy Beane

Beane and his small team of analysts discovered that Major League Baseball teams were not properly valuing players; players’ salaries did not accurately reflect their ability to help their team win games.

What caused teams to incorrectly value players?

A tendency to overpay players with “sexy” stats like slugging percentage, stolen bases, batting average, and home runs over less “sexy” stats like walks. A reliance on scouts and their “gut” feelings to evaluate player value.

There were other factors, such as valuing a player for their marketability, but for the sake of simplicity we’ll ignore those.

The holy grail stat that Beane and the A’s ended up using to inform their player signing decisions was on-base percentage, which took into account hits, walks, and hit-by-pitches. Pitchers were also evaluated, but for the sake of simplicity we’ll ignore them.

The A’s “Big Three” in 2001. Sorry, guys. Source.

“…we find that hitters’ salaries during this period did not accurately reflect the contribution of various batting skills to winning games. This inefficiency was sufficiently large that knowledge of its existence, and the ability to exploit it, enabled the [A’s] to gain a substantial advantage over their competition.” -Hakes, Jahn, K., and Raymond D. Sauer. 2006. “An Economic Evaluation of the Moneyball Hypothesis.”

Lewis’s book was a hit among sports circles (including other US-based sports) and the general public. It catapulted Beane and the A’s to fame. Once Lewis’s book was published, other teams caught on — some quicker than others. Bigger-budget teams that also took measured approaches to data analysis, like the Boston Red Sox, ended up nabbing World Series titles.

Believe it or not, Moneyball tactics never won the A’s a World Series. The A’s outperformed compared to their spending, but they never actually won a World Series in the Moneyball era. The Moneyball approach worked well over the course of a long season, but not so much in the playoffs. In the book, Beane summed it up quite eloquently:

“My shit doesn’t work in the playoffs. My job is to get us to the playoffs. What happens after that is fucking luck.” -Billy Beane

Brad Pitt plays you in a movie. Not bad, eh?

A note on the OWL’s Boston Uprising

The Boston Uprising finished 3rd in the OWL’s first regular season standings with what was rumored to be a low budget. Somehow a myth spread across OWL fan circles that Boston had “Moneyballed” their way into a 3rd place finish.

HuK, President of Gaming, said in an interview that “We used a five-check system [to assemble the Boston roster] and I would say one and a half of those checks were stats.” So the team was mostly put together based on good old fashioned scouting — the opposite of a Moneyball approach. Another Huk quote from the article: “I think measuring how good a player is and can be is always going to be a soft science and something that other teams and other GMs didn’t necessarily do as good of a job as we did. With all that being said, the number one thing that we were looking for, and I think I’ve emphasized this a lot, is having players that are coachable.” HuK’s approach was a perfectly valid way to put together a team, but it wasn’t a Moneyball approach.

A note on Moneyball naysayers

People have made compelling arguments against the Moneyball thesis, including sports writer Allen Barra in this article. Feel free to enter this rabbit hole at your own risk.

3. Moneyball in the Overwatch League? Not quite, and not yet.

A) OWL player salaries are private. This is probably the most obvious reason why we can’t apply traditional Moneyball tactics to the OWL. Without access to player salaries, it’s not possible to mathematically determine undervalued players - which is the whole point of the Moneyball approach. We could use something like team status as a proxy — whether a player is signed to a league team or a lower tier team that competes outside of the OWL.

I don’t think OWL salaries will become public in the near future. From an economic theory perspective, public player salaries increase the negotiating power of players, which on average results in higher salaries. Teams don’t want to spend more money than they have to, so I don’t see them voluntarily releasing player salary data. I also don’t see any pressure on the OWL to release player salaries.

B) OWL stat tracking is incomplete (but improving). Major League Baseball has easily accessible stats for players in the league and its minor leagues. The OWL is only one season old. Prior to its formation, where could teams turn to for reliable player statistics? Websites like Winston’s Lab and paid third-party computer vision programs (which only give you stats on your own players) existed, but teams were scattered across continents and they weren’t consistently competing against each other regions.

Earlier this year, Blizzard accidentally released expanded API stats. To my knowledge it’s been re-hidden from the public, but I assume teams have access to this data. Blizzard also recently launched an in-game viewer that allows spectators to view any player’s perspective. This will allow teams to collect more detailed data on other teams’ players (via the aforementioned computer vision programs).

C) Due to the nature of Overwatch’s gameplay, it’s more difficult to pin down the stat(s) that contributes to wins.

Baseball’s win condition is pretty simple: Score more runs than your opponent. There’s no time limit (the presence of a timer can dramatically affect player behavior) and every scenario begins with a 1v1 between a batter and a pitcher (ignoring base runners and fielders). Additionally, the batter’s goal (score runs) almost never changes and is limited to a few actions (get on base or perform a sacrifice fly/bunt). All of these characteristics make the sport easier for number crunchers.

It’s much more difficult to statistically identify an individual player’s contributions in Overwatch. The game more closely resembles two teams of six repeatedly smashing into each other, so every scenario begins with twelve players’ actions to account for instead of two. The game’s win conditions also greatly vary depending on which of the four game modes is being played, so it’s not simply a matter of scoring more points like it is in baseball. Players can also make in-game switches between playable characters (there are 29 as of writing) and roles (damage, tank, healing), which also complicates things.

OWL team fights are utterly incomprehensible to people unfamiliar with the game. Video source.

D) Large and frequent shifts in Overwatch’s meta make it difficult to compare current and past performance.

In Overwatch, new characters are released every few months and existing characters are tweaked. These meta changes can have a dramatic effect on players’ stats. In comparison, baseball’s rules don’t change quite as frequently or drastically. The baseball equivalent to Overwatch’s meta shifts might be moving the pitcher’s mound forward/backward or allowing batters to use metal bats.

4. Conclusion

The benefits of a Moneyball approach in the OWL do exist. For example, we know that OWL general managers have a limited budget to sign players — the same dilemma that Billy Beane faced.

The first half of the Moneyball approach (finding Overwatch’s equivalent to baseball’s on-base percentage) could conceivably be solved. We can’t complete a proper Moneyball analysis without knowledge of player salaries, but we could use something like “player x is signed to an OWL/contenders/trials team” as an indicator of value.

That said, the advent of Moneyball in sports is not the human equivalent of discovering fire; teams were conducting lots of perfectly valid data analysis before Billy Beane joined the A’s. The same goes for the OWL; there’s plenty that can be gleaned from soft science (i.e. scouting) and the existing data that teams have available to them. I’m only asking is that we not blindly refer to it all as “Moneyball”.