Team Scouting

Team Scouting lives at /faceit. You search for a FACEIT team by name and open a profile that lays out how they play and what to play into them. It is the surface you use to build a map veto and a ban plan before a match.

Finding a team

The search page is a single search box. Start typing a team name and a list of matching teams appears, each row showing the team name and how many tracked matches it has. Pick one — by click, or with the arrow keys and Enter — to open its profile. Only teams that have tracked matches show up, so a team you cannot find may simply have no scouted history yet.

Reading the profile

The profile is a single scrolling report, top to bottom, made of the sections below.

Header and team strength

The top of the page carries the team name and a strip of headline numbers:

• Record — wins–losses, with the total number of matches played.
• Win rate — overall win rate, with a recency-weighted win rate alongside it, so recent results count for more than old ones.
• Team FSR — the roster's combined FACEIT Skill Rating, blended from each starter's per-role FSR, with a note of how many players on the roster are rated (for example, 4/6 rated). It reads "how good is this five at putting up output for their level" rather than "how often do they win." Check the rated count before trusting it: a team number built from only part of the roster is a partial read.
• Team TSR — the roster's combined TSR, again with rated coverage. Because TSR is built from match results and FSR from in-game stats, the two can disagree — a team that wins more than its raw output suggests will show a higher TSR than FSR, and vice versa.

If the team shares core players with other scouted teams, a related teams line appears with links to those teams and how many core players they share. You can toggle a combined view that rolls those related teams together — useful when a roster has played under more than one team name and you want their full body of work in one place.

Game plan

A condensed, actionable summary near the top, grouped into four buckets:

• Maps to force — maps where they are weak, so you want to pick them.
• Heroes to ban — heroes whose ban hurts their win rate the most.
• Maps to avoid — maps where they are strong, so steer the veto away.
• Heroes not to ban — heroes whose ban does not hurt them, so don't waste a ban on them.

Each entry carries the supporting numbers (win rate and sample size, or the win-rate swing with and without the ban). If there is not enough signal to make calls, this section says so rather than inventing recommendations.

Overview — how they play

• Recent form — a row of recent results (W/L), so you can see whether they are trending up or down.
• Attack vs Defense — win rate when attacking first versus defending first, each with the maps-won-of-played behind it. This tells you which side they would rather start.
• Tiers played — a distribution of which tiers (Open through OWCS) their tracked matches came from, so you know what level of competition their record was built against.

Patch timeline

How the team has performed across Overwatch balance eras, so you can tell whether a strong record is current or was built on an older patch. Each row is a patch window:

• Patch — a season patch (by name) or a mid-season patch (by date), with the date range it covers. Matches from before patch tracking began are grouped into a single pre-tracking bucket.
• Win rate — their win rate during that era, shown with a bar and colored for above or below 50%.
• Matches — how many tracked matches fall in the window; thin windows are marked low sample.
• Most banned — the heroes most often banned in their matches that era, with counts.

If the team has no tracked matches since patch tracking began, the section says so instead. Read it alongside recent form: a team that fell off after a balance patch that hit their comp is a different opponent than their all-time record suggests.

Map performance

Two tables: win rate by map and by mode (the game modes such as Control, Escort, and so on). Rated rows — the ones with enough games to trust — are sorted to the top by win rate; thin samples fall below and are marked low sample. This is the backbone of your veto.

Hero ban environment

A map-level read on which hero bans actually move the needle. For each hero, the table shows their win rate without that hero in the ban pool versus with it, the delta between the two, and the sample sizes. The heroes whose ban hurts them most are tagged as ban targets.

A toggle reveals low-sample heroes that are hidden by default, so you can see the full list when you want it.

Roster

The roster table lists each player with:

• Player — nickname, a starter or sub tag, and their Battle Tag if known.
• Role — Tank, Damage, or Support.
• Share — how much of the team's recent maps they appeared in, so you can tell the regular five from fill-ins.
• FSR — their FACEIT Skill Rating, on the 1–5000 scale.
• TSR — their TSR.

Each player links to their full player profile. An inline "How FSR works" explainer is available next to the section if you need a refresher.

How to use it

• Build the veto from map performance and the game plan. Force their weak maps, steer away from their strong ones, and check the attack/defense split to decide what you want when the side picks land.
• Set bans from the hero ban environment. Spend bans on the heroes whose removal actually lowers their win rate, and skip the ones the data says don't matter.
• Sanity-check the record with the tiers played, recent form, and patch timeline. A great-looking win rate built against Open lobbies, earned mostly in older matches, or banked on a since-patched comp should be weighted differently than one earned recently at Expert or above. The recency-weighted win rate already leans toward current results for this reason.
• Use related teams and the combined view when a roster has played under more than one name, so you are scouting their real body of work.
• Drill into the roster to decide who to target and who to respect, then continue on the Player Scouting page.