Ter0o

Ter0o — CS2 Stats

FI76561197968575194[U:1:8309466]Steam profile ↗✓ No bans

1,377Tracked matches30%Win rate2020Tracked since
CSDB Rating4.2 DevelopingPositional Player
CSDB Leaderboard#75446 of 260011 tracked
FaceitLevel 6Top 54.0% of ranked FACEIT players
WingmanDistinguished Master Guardian
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 20,584 +2,908 9 Nov – 18 Jan · 12 days played
16,49920,584peak 20,5849 Nov18 Jan
20,584Peak Premier in tracked matches
45Days played since 2024-11-08

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

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CSDB.GGTer0oFACEITLevel 6STANDINGTop 54.0% of rankedcsdb.gg/stats

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Performance scores

Aim58
Positioning42
Utility37

0–100 skill scores via Leetify.

Recent form

COLD51–47–2Last 10051%Win rateLWLLLLWLLW

Last 10 vs previous 10: −10pp win rate · −0.01 avg rating · +7.7pp headshot accuracy · +49ms reaction

Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 26%
  • Avg reaction 592ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 21%
  • Avg reaction 597ms

Last 20

  • 7–13 · 35% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 17%
  • Avg reaction 572ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Positional Player — Positioning stands above the rest of this profile (+1.6 against its own average).

Aim5.8
Utility3.7
Positioning4.2
Opening Duels0.0
Clutch2.4

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

iM

Plays most like iM 91% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim profile; lower opening-duel success.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Areas to improve

Reaction time. 576ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim5.8
Positioning4.2
Utility3.7
Mechanics6.9
Opening Duels0.3
Win Impact0.0

Composite 4.2/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.04−0.02
first ⅓ avg -0.02 → last ⅓ avg -0.04
Reaction time573ms−7ms
first ⅓ avg 580ms → last ⅓ avg 573ms
Headshot accuracy17.1%−0.6%
first ⅓ avg 17.7% → last ⅓ avg 17.1%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.11Best match rating · 13–4 · ancient, 28 Dec →
36%Best headshot accuracy · 5–13 · ancient, 28 Feb →
422msFastest reaction time · 13–6 · ancient, 15 Mar →
13–3Biggest win · nuke, 9 Jan →

Across the last 100 tracked matches.

Highlights

6Longest win streak
6–5In matches decided by ≤2 rounds
8Overtime games

Map breakdown

anubisBest map · 70% over 23trainWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
anubisS2316–770%-0.01
infernoS2215–768%-0.02
ancientB2110–1148%-0.01
nukeD143–1121%-0.03
dust2B84–450%-0.03
trainD61–517%-0.01
overpass—21–150%-0.06
mirage—20–20%-0.07
office—21–150%-0.01

Across the last 100 tracked matches.

Faceit stats

Combat

518Matches
51%Win rate
0.95Avg K/D
68.9ADR
43%Headshot %

Clutches & streaks

32%1v1 clutch win
17%1v2 clutch win
8Longest win streak

Recent Faceit resultsWLLLL

MapMatchesWin rateAvg K/DAvg kills
Anubis9861%0.9713.6
Ancient9258%1.0013.0
Inferno8461%1.0013.3
Nuke3842%0.9313.5
Mirage2536%0.699.7
Vertigo2417%0.7611.8
Overpass1450%0.8712.9
Dust2617%0.7110.5

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

16.9%Headshot accuracy
28.7%Accuracy (enemy spotted)
31.8%Spray accuracy
81.3%Counter-strafing
9.5°Preaim
576msReaction time
19.9%T opening success
32.0%CT opening success
0.47Enemies flashed / flash
5.3%Flash assists
6.97HE damage / grenade
14.59Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

  1. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.4703 — below the 0.5 mark we flag

    Grenade Lineups →
  2. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 19.8504% — below the 40% mark we flag

Spend your practice time on Train

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
ancient3–13-0.0323%14 Jun →
nuke13–10-0.0517%14 Jun →
inferno8–13-0.0531%28 Feb →
ancient5–13-0.0936%28 Feb →
nuke11–13-0.0326%6 Feb →
ancient9–130.0019%6 Feb →
inferno13–10-0.0124%6 Feb →
nuke3–13-0.080%4 Feb →
ancient10–13-0.0415%2 Feb →
dust213–9-0.0316%19 Dec →
overpass2–13-0.1022%17 Jul →
overpass13–4-0.0313%17 Jul →
ancient13–90.0712%22 Mar →
nuke13–16-0.059%21 Mar →
train7–13-0.0314%20 Mar →
nuke20–22-0.0311%20 Mar →
ancient13–6-0.017%15 Mar →
mirage5–13-0.0911%15 Mar →
nuke10–130.0314%15 Mar →
ancient16–12-0.0216%7 Mar →
inferno13–110.0016%7 Mar →
dust213–16-0.0821%27 Feb →
nuke3–13-0.0411%27 Feb →
ancient8–13-0.0219%27 Feb →
anubis6–13-0.0526%27 Feb →
anubis2–13-0.0620%19 Feb →
train5–13-0.089%19 Feb →
anubis13–16-0.0715%14 Feb →
ancient7–13-0.0622%14 Feb →
dust213–7-0.0119%10 Feb →
nuke9–13-0.0313%8 Feb →
ancient12–16-0.0519%5 Feb →
inferno13–40.0320%5 Feb →
anubis13–10-0.0319%5 Feb →
anubis13–60.016%2 Feb →
inferno7–13-0.0514%2 Feb →
nuke3–13-0.1117%1 Feb →
ancient16–14-0.0119%31 Jan →
anubis13–50.0119%31 Jan →
train13–80.0518%31 Jan →
ancient13–10-0.0217%31 Jan →
train12–16-0.0421%29 Jan →
anubis13–10-0.0221%29 Jan →
inferno11–130.0126%23 Jan →
nuke9–130.0317%21 Jan →
inferno13–11-0.0616%18 Jan →
anubis13–50.0311%18 Jan →
anubis13–90.0120%17 Jan →
ancient7–13-0.0124%17 Jan →
dust213–100.0014%17 Jan →
nuke4–13-0.0924%17 Jan →
anubis13–40.0416%17 Jan →
anubis13–11-0.0311%15 Jan →
inferno13–80.0316%15 Jan →
anubis5–130.0113%14 Jan →
inferno13–100.0123%14 Jan →
train12–120.0714%14 Jan →
ancient10–10.0813%14 Jan →
inferno10–13-0.0816%9 Jan →
nuke13–30.0021%9 Jan →
inferno13–9-0.0723%30 Dec →
ancient13–3-0.048%30 Dec →
inferno13–3-0.0218%30 Dec →
ancient13–40.1113%28 Dec →
anubis13–10-0.0217%28 Dec →
inferno9–13-0.0122%28 Dec →
dust22–13-0.0513%28 Dec →
anubis13–7-0.0426%27 Dec →
inferno6–13-0.0710%27 Dec →
ancient9–13-0.0224%27 Dec →
inferno13–7-0.0319%21 Dec →
mirage6–13-0.0417%21 Dec →
office7–13-0.0412%20 Dec →
anubis13–70.0725%20 Dec →
office13–70.0218%20 Dec →
anubis7–130.0322%19 Dec →
ancient13–11-0.0122%16 Dec →
inferno13–6-0.0226%16 Dec →
nuke13–5-0.0125%16 Dec →
anubis11–13-0.0416%15 Dec →
inferno13–6-0.0119%15 Dec →
inferno8–13-0.0315%9 Dec →
dust213–90.0231%9 Dec →
anubis13–40.0218%9 Dec →
ancient7–130.0118%27 Nov →
train12–12-0.0216%27 Nov →
ancient5–13-0.0624%17 Nov →
nuke6–130.0212%17 Nov →
anubis13–30.0014%17 Nov →
anubis7–13-0.0617%17 Nov →
ancient13–11-0.0617%12 Nov →
dust29–13-0.0718%11 Nov →
anubis13–9-0.0513%10 Nov →
inferno13–9-0.0218%10 Nov →
inferno13–6-0.0514%10 Nov →
inferno13–10-0.047%10 Nov →
anubis13–7-0.0610%10 Nov →
dust211–13-0.039%9 Nov →
inferno13–50.029%9 Nov →
anubis13–60.0126%8 Nov →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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