You may probably feel like expecting results from simulator-style predictors is the type of activity that can give you a head start. Whether you’re meaning to use what they yield to get a sense of foresight, to bet on sports, or to turn yourself into an oracle on social media, there is something to harness them for.
The interesting part about all of this is that all simulation models that are publicly available have risen tremendously in how well they can assess things. Data management drives most operations nowadays, and the world of professional or even semi-professional sports is the same.
One of the readily available ways in which such predictions are part of pop culture, thus widely consumed, is through video games. More specifically, the sports-themed ones, including those that, via licensing, associate themselves with leagues, teams, and players.
As they create entire digital ecosystems that mimic real life, each player, their performance, and their input into their team turn into stats. They’re numbers that, percolating and varying based on very intricate algorithms, give way to the engine that drives these simulations.
In this article, we will approach this aspect from all angles and explain why these elements can be helpful in prediction efforts. These can apply in all ways to numerous sports and their respective video games, which is a plus from the jump.
Sports predictions are increasingly important
The economics of being right have turned into something a bit uncontrollable, and this is a trend that we can track to multiple phases of internet culture. Once the so-called ‘culture war’ started in the public sphere, debating became as ubiquitous as ever in the discourse arena.
Add social media to the mix, and now you have it: an environment in which every statement, correct or not, can be a twisted truth that fits a narrative. If you’re on these networks, you probably know very well that sports haven’t escaped that fate.
If you want the clout to claim correctness, you’re going to need results, and probably a track record of being right (the so-called ‘receipts’). They’re what legitimize your ability to be a real player in the overall discourse sphere.
In a related but somewhat distinct term, having access to efficient simulation models is the bread-and-butter of sports betting. Certain sports are too complex to just go with vibe-based, intuitive wagering, which is why you see football predictions usually go with data-driven approaches.
Regardless of your reason to try to understand what’s going to happen, any simulator with a decent algorithm can be a decent orientational tool.
What goes into a video game’s value engine
Getting very deep into the technical details of the simulation engines of these video games would simply take too long. For this reason, we will talk about what actually brings value to these models if we are to take them seriously.
It all depends on the type of data that goes into them. If the setup is to work correctly, it needs to assess value and performance equitably, based on real-life aspects.
Simply put, if these details strike the right balance, you have realistic simulations that can inform you on what can happen, not necessarily what’s likely to happen.
Overalls and stats are the main breaking point
In the culture surrounding sports-themed video games, the ‘overall’ may be the biggest point of contention. It has caused controversy in virtually any title of this sort, especially when fandom-related factionalism is part of the discussion.
The truth is that, in many ways, getting the stats related to the player right is almost impossible. There are simply numerous contributors to a team whose impact does not come via face-value counting stats.
Thankfully, there are mitigating factors all around. Advanced stats and the use of sports analytics have permeated video games, which means that assessing impact has become more precise.
This still creates issues regarding the so-called ‘untouchables,’ such as leadership, which are very important within a team’s internal politics, especially in the context of a long and mentally taxing season.
Much of the overarching issue boils down to very imperfect player performance and value assessment. When you add numerical value in, ultimately, a somewhat arbitrary way, you do not know if you’re going to have the right valuation, and that’s an issue that should also account for the unknown that is rookie impact.
To conclude this point, if there are numerous incorrect parts in player impact valuations, the simulations operate on flawed principles, which makes it much harder to come up with properly feasible outcomes.
Inserting randomness mitigated by tendencies
It may sound like a paradox, but predicting unforeseeable events is not impossible. In fact, it’s almost like identifying issues that may arise because there are distinguishable signs. They may be hard to correctly simulate, but adding such variations to simulations can help come up with various doable scenarios.
Video games are very limited in being able to predict these random aspects. However, as algorithms become more efficient due to a better and more powerful data processing ability, they can add curveballs that add unpredictability to the mix.
For the longest time, injuries were the most important ones. We’re talking about over 20 years of this mechanic within manager mode simulations. As understanding of a player’s injury proneness has improved, knowing which athletes are more predisposed to it has increased predictive power.
You can also add this to squads, especially when led by certain players and coaches who are unable to secure their lead. Bottling a result is a notorious thing that one can associate with pacing management, tactics, or emotionality, and they’re also the type of unlikely scenario that can work on this front.
Why ‘freak’ events throw the entire system out of the loop
You have cases when coaches may get the boot mid-season. Video games like Madden and EA Sports FC allow you to make coaching moves, and the system can also add the fact that underperformance leads to coaches losing their jobs.
That’s the same way with, say, a player brawl that decreases team morale, or politically-charged disagreements that drive a wedge in the locker room. That’s not even to say when something truly tragic happens and completely dynamites a season before it even begins.
It’s also the case with on-field injuries that simply do not make sense. Any player can be an iron man, but an unfortunate collision can lead to a sudden loss of a season, if not a threat to a career that wasn’t anywhere close to injury-prone.
Conclusion
Simulations work well when they can add curveballs, as we said. However, video games are entertainment-first factors that also need to account for in-game pacing.
That’s not even to mention the short development times that these yearly titles have, which severely reduce the capability of developing a truly strong predictive engine.
In conclusion, video game-based predictions are interesting, but their track record hardly explains the development of tactical nuances of roster-building. As such, especially if you’re looking to use them for betting, please do so responsibly and with a major grain of salt!
