VALORANT SCOUT

Stop guessing. VALORANT SCOUT delivers instant opponent intel map-by-map tendencies, comps, economy patterns, and clear counter-strats you can run tonight

Comment

Inspiration

Competitive VALORANT is decided before the first round is played. Most teams don’t lose because they can’t aim — they lose because they walk into matches unprepared. Real scouting takes hours, lives in messy spreadsheets/notes, and is usually locked behind analyst time. We wanted to turn scouting into something instant, structured, and usable mid-scrim: not “interesting data,” but a ready-to-run gameplan.

What it does

VALORANT SCOUT is a scouting engine that turns match history into actionable prep for coaches and IGLs.

It generates a team report with:

  • Map tendencies (comfort maps, win rates, repeat patterns)
  • Agent comps + role structure (defaults, swaps by map, role distribution)
  • Economy behavior (pistol impact, bonus conversions, force patterns, swing rounds)
  • Player tendencies (first contact, lurks, support patterns, carry/enable signals)
  • Exploitable habits (predictable hits, weak sides, repeat setups)
  • A tactical briefing that summarizes win conditions + counter-strats you can run immediately

How we built it

  • Data ingestion: Pulled team + match data from the GRID ecosystem
  • Processing layer: Aggregated, normalized, and derived structured stats + patterns
  • Analysis engine: Converted raw metrics into scouting signals (tendencies, roles, habits)
  • Briefing generator: Produced a concise tactical summary from the analysis
  • UI: Presented everything in a clean, fast interface designed for decision-making, not reading

Challenges we ran into

  • Messy real-world data: Normalizing match info into consistent, comparable signals
  • Signal vs. noise: Avoiding “stat spam” and prioritizing what actually changes a gameplan
  • Context matters: Making insights map-specific, comp-aware, and round-type aware (eco/gun)
  • Clarity under pressure: Keeping reports readable and useful mid-scrim, not just post-match
  • Bridging data → tactics: Translating numbers into counter-strats, not just dashboards

Accomplishments that we're proud of

  • Built a scouting workflow that goes from search → report → gameplan in minutes
  • Delivered a report format that focuses on priorities, not walls of text
  • Created tactical briefings that feel like a coach/IGL “prep sheet,” not a data dump
  • Designed the UI around speed: what to ban/pick, what to punish, who to target, what to expect

What we learned

  • The hardest part isn’t collecting stats it’s producing trustworthy, actionable insight
  • Good scouting is about patterns + punish windows, not raw win rates
  • Constraints make products better: optimizing for “usable mid-scrim” forced ruthless clarity
  • Turning analysis into a briefing is a product problem as much as an engineering problem

What's next for VALORANT SCOUT

  • Deeper tactic breakdowns: default exec timings, site hit distributions, mid-round pivots
  • Opponent-specific anti-strats: “If they show X, punish with Y” playbook recommendations
  • Better filtering: by patch, roster changes, recent form, and match tier
  • Shareable outputs: exportable reports for coaches (PDF/links) + quick “IGL brief” mode
  • Scrim workflow upgrades: prep packets per opponent + map veto helper + priority checklist

Built With

Share this project:

Updates