Esports and Gaming

Competitive gaming is a performance domain that combines mechanical skill, real-time strategy, team communication, and psychological resilience — and it has produced infrastructure (coaching, analytics, collegiate programs) that increasingly mirrors traditional sports. This article covers Jason's direct experience building Midgame (esports voice analytics), research into collegiate esports programs, and the broader argument for why communication is the underappreciated variable separating good teams from great ones.

Esports as a Performance Domain

The standard objection to esports — "it's not a real sport" — misses what's interesting about it. Competitive gaming is not primarily a physical competition, but it is a performance competition, and it shares more structure with elite sport than it does with leisure entertainment.

A Georgia Tech esports leader described it precisely: "In other sports, there's only the physical aspect. In academic debate, there's only the cognitive. But in gaming, you work with a team, use mechanical skill, apply strategy, respond to teammates in real time, and adjust your mental state under pressure." That combination — team coordination, individual skill expression, real-time adaptation, and high-stakes psychological performance — is the full stack.

Games like Dota 2 and League of Legends require players to:

• Choose team compositions (strategic planning before play begins)
• Execute individual mechanical actions under time pressure (reflexes, precision)
• Track and communicate information about enemy positions, ability cooldowns, and resource states
• Make coordinated decisions in under a second as conditions change

The pro Doublelift (League of Legends, Team SoloMid) put it directly: "The biggest myth in esports is that veteran players don't get nervous. Everyone gets nervous." The psychological performance demands are real.

Prize money is extremely top-heavy. The top team at major tournaments takes home $10M or more; 20th place takes home almost nothing. This creates an environment where marginal improvements at the top have enormous financial consequences, which is partly why pro teams have begun investing heavily in coaching, analytics, and communication tools.

Georgia Tech Esports — A Case Study in Collegiate Infrastructure

Georgia Tech's esports program is among the oldest collegiate gaming organizations in North America, dating to the early 2000s as a support group for top StarCraft: Brood War players. By the time Midgame was researching the space (~2019-2020), the organization had:

• 350 members, 100 of whom competed across SC2, LoL, Dota, CS:GO, Hearthstone, and Rocket League
• Institutional backing from the College of Computing and GT Athletics
• Funding from local tech companies and national esports-adjacent sponsors
• A knowledge transfer problem: rosters turn over every 3-6 years as players graduate, and institutional knowledge has to be systematically documented or it disappears

Post-game review is more valuable than pre-game prep — and it's almost always skipped. A Georgia Tech coach noted: "Post-game review is a lot more important. Often overlooked. You feel so good after a win, you just move on. Those games are worth reviewing." And for losses: "A lot of teams overlook that. Watch why they lost. Missed out on money. Huge part of improving. Watching at half speed, pointing out what happened."

This is a structural failure common to many organizations, not just esports teams. Victory is its own reward and produces no natural demand for analysis. Defeat is aversive and generates motivation to move on rather than study what happened. The review habit has to be built artificially.

Pre-game prep, by contrast, can sometimes be overrated: "Sometimes you don't need to know about the other team, just run your strategy, if you know your team and your game."

Gender dynamics. The Georgia Tech program was predominantly male, and the dynamics of online gaming culture were a direct cause. One interviewee noted that his girlfriend — a Dota player — "never uses the mic. Dynamic of women being treated differently online. Part of the minority." This is a market failure in the esports talent pool: women who game competitively often opt out of team voice communication due to harassment, which means they're functionally excluded from team roles even when their mechanical skill is comparable.

Collegiate programs as a structural stepping stone. In the broader ecosystem, the skill gap between college teams and pro teams is enormous. The system lacks the tiered minor-league structure that traditional sports use to develop talent from amateur to professional. Scholarship programs at schools like UC Irvine and University of Utah (with dedicated facilities) represent early attempts to close that gap, but as of 2019-2020, most of the southeast was "behind the western and midwest area."

Midgame: Building Communication Analytics for Esports

Midgame was Jason's startup (co-founded with Wayne), initially pivoted from Headlight, an HR analytics tool. The core insight: among all the things an esports team can improve — gameplay mechanics, metagame knowledge, and communication — only communication was underserved by existing tools.

Why communication, not gameplay or metagame?

Gameplay analytics is owned by the game developer. They have access to every action a player or team takes and already provide reasonably granular data. Improving gameplay analysis further requires access to raw game data or computer vision — neither of which a startup could easily acquire.

Metagame analytics (optimal character picks, item builds, patch-specific strategies) was already well-served by sites like Op.gg, YouTube channels, and community wikis. Players could easily find up-to-date information.

Communication analytics — how teams talk to each other in real time — had essentially no tooling. "Coaches usually try to take notes on comms as the game happens but it's super hectic. One of the coaches of a pro Overwatch team actually transcribed the team audio by hand and writes out corrections on calls she thinks were bad." That team was spending 18 hours manually reviewing audio from a single 3-hour game (six players, six audio tracks). The effort demonstrated that pro teams believed communication mattered enough to invest that kind of time — and that there was nothing better available.

What the product did. A Discord bot joined team voice channels, captured individual audio tracks from each player, transcribed the audio, and provided a dashboard for reviewing:

• Call-out analysis (who called what, when, in how many words)
• Talk time distribution across players
• Cross-talk detection (who was interrupting whom)
• Keyword frequency tracking (e.g., how often "blue" was called at key game moments)
• Interactive transcripts synced to audio for post-game review

The core principle: "VODs tell you what happened. Comms tell you why."

What 50 interviews confirmed. Over 8 weeks, the team contacted about 100 collegiate esports teams and interviewed 50 players and coaches. "Communication came up as a top priority" — across teams, levels of play, and game types, the ability to coordinate verbally in real time was identified as the primary differentiator. The specific pain points were: individual player call-outs (are they clear? timely? too wordy?), cross-talk (are players stepping on each other?), and transcript access (the ability to resolve "I didn't hear the call" vs. "you never made the call" disputes with actual evidence).

Case study: Colorado College Tigers. After receiving Midgame data, the Colorado College Tigers switched their primary shot-caller to a player shown to be significantly more active on comms. The result: they beat teams ranked 400 SR (Skill Rating) above them. The strategic implication is striking — communication quality could overcome a meaningful mechanical skill gap. Being organized and clear in the moment mattered more than raw ability.

Communication as a second language. One of the observed effects from teams who used the tool consistently was that players developed "a second language for callouts" — abbreviating and clarifying their communication over time, getting more information across in fewer words. This mirrors what Northeastern players described as the ideal for Counter-Strike: words per call decrease, information density increases, and the team can operate on shorter, cleaner signals. In CS:GO, with its 15-second buy phase and precise timing windows, "CS is a game of seconds" and "golden rules" include: never talk during a 1-vs-multiple situation, and if you are dead, don't talk.

Overwatch had different conventions: "generally accepted shotcalling strategy is hive mind — shout what you are shooting, keep calling the target until they die, then call the next person." Both games required explicit communication norms, not just good intentions.

Reporting hierarchy. Midgame built separate outputs for different audiences:

• Individual player report cards (what did I say, when, for how long)
• Coach-level weekly summaries (trends across games, comparisons between players)
• Management-level high-level views (is the team trending better or worse on communication metrics?)

Different granularity for different decision-makers — a core product management discipline.

Business Model and Market

The business had two primary revenue streams:

Consumer/collegiate tier: Freemium at $25/team/month (roughly $5/player/month on a 5-person team). Addressable market: 120M team-based game players; if 10% compete seriously, that's 12M potential customers and ~$720M annually at scale.

Pro/enterprise tier: $20,000/month for professional teams competing for million-dollar prizes. With 100 pro teams at launch growing toward 500, that's a $120M market. The pricing reflected the value proposition: a tool that helps a team competing for a $10M prize purse improve performance is not a discretionary cost.

Midgame was eventually acquired by Facebook (now Meta), which saw the underlying voice analytics infrastructure and team communication insights as applicable beyond gaming.

The Transfer Principle: Esports Coaching to Executive Coaching

The patterns that make communication analytics valuable in esports apply directly to other high-stakes team environments. The core problem is the same: teams working together in real time, under pressure, where small communication failures cascade into strategic failure.

From the esports work, several transferable insights:

Post-performance review must be structured or it won't happen. Winning teams don't naturally review; losing teams don't want to. Any coaching system that relies on voluntary review will systematically skip the review that matters most. Structured debrief — with data — is the intervention.

Communication patterns are a leading indicator of team health. If one player stops talking after losses, or if the shot-caller goes quiet in close games, those patterns are visible in the data before performance breaks down visibly. Communication analytics functions like an early warning system.

Data resolves disputes that perception can't. "I didn't hear the call" vs. "you never made the call" is an unresolvable conflict in a team that relies on memory. With a transcript and audio, it has an answer. Removing ambiguity from interpersonal feedback is one of the most significant things data can do for a team's communication culture.

Small habits compound. The Colorado College Tigers case, and the second-language effect observed in teams over time, both suggest that communication improvement is not linear. Teams that practice clean, structured callouts for several weeks start building communication as muscle memory — and the improvement compounds in ways that raw skill development does not.

Voice Technology and Gaming More Broadly

At a TED Summit talk (Techstars Seattle), Jason argued that voice technology was becoming the third wave of transformation in gaming, after graphics and mobile:

1. Voice communication — Discord normalized real-time voice coordination for hundreds of millions of players. Fortnite became "the new mall" — kids hanging out socially, not just competing.
2. Voice-first games — Alexa skill games like "Yes Sire" represented an early, rudimentary layer of games designed entirely for voice interaction. The comparison to early mobile games (which seemed trivial before becoming enormous) was deliberate.
3. Voice-enabled tools — Tools that let players access game data, strategy guides, patch notes, and coaching while staying in-game, rather than alt-tabbing to a browser. Midgame was building in this direction: maintaining immersion rather than breaking it.

The broader argument: human language is what separates us from other animals (fine-tuned vocal tract control, desire to share non-essential information, syntactic comprehension). Games that integrate voice are closer to how humans actually think and coordinate. That's not a niche — it's an alignment with human nature.

Related Topics

• product-management — Midgame as a PM case study: pivoting from Headlight, landing on communication analytics, structured beta testing, tiered reporting
• startup-pivots — Midgame's journey from HR analytics to esports voice analytics and eventual acquisition by Facebook
• deliberate-practice-and-performance — Feedback loops in performance: why post-game review is the highest-leverage intervention
• extreme-human-performance — Parallel performance principles across esports and traditional athletics
• cofounder-conflict-coaching — Communication as a proxy for team health; how small habits compound