TOAO

TOAO — CS2 Stats

PRO“t”Phantom EsportsPolandIGLSettings & gear profile →

PL76561198156373160[U:1:196107432]Steam profile ↗✓ No bans

1,874Tracked matches47%Win rate2020Tracked since
CSDB Rating5.6 SolidSupport
FaceitLevel 10 · 3,188 ELOTop 12.4% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 22 Oct 2026 (11 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 1,874 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Faceit ELO: 3,188 +0 28 Aug – 22 Oct · 11 observations
3,1883,188peak 3,18828 Aug22 Oct
3,188Highest Faceit ELO seen on CSDB
47Days played since 2024-02-04

Faceit ELO

  • At peak — 3,188
  • 0 over 30 days · steady
  • Next: 3,500 ELO at 3,500 — 312 to go
  • Reached: 3,000 ELO · 2,500 ELO · Level 10 · Level 9
  • 3,000 ELO first seen 2026-08-28
  • 2,500 ELO first seen 2026-08-28

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

Share this profile

CSDB.GGTOAOFACEITLevel 10 · 3,188 ELOSTANDINGTop 12.4% of ranked30 DAYS0 ELOPEAK ELO3,188csdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim76
Positioning42
Utility59

0–100 skill scores via Leetify.

Recent form

STEADY53–47Last 10053%Win rateLLLWWLWWLL

Last 10 vs previous 10: −10pp win rate · +0.01 avg rating · +3.2pp headshot accuracy · −38ms 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

  • 2–3 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 20%
  • Avg reaction 509ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 20%
  • Avg reaction 517ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 19%
  • Avg reaction 536ms

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: Support — Utility contribution stands above the rest of this profile (+2.6 against its own average).

Aim7.6
Utility5.9
Positioning4.2
Opening Duels0.2
Clutch2.8

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

ropz

Plays most like ropz 78% 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

Positioning. Positioning trails aim by 35 points — deaths here waste a strong aim profile.

T-side openings. Opening success drops from 34% on CT to 18% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 553ms 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

Aim7.6
Positioning4.2
Utility5.9
Mechanics5.8
Opening Duels0.5
Win Impact3.9

Composite 5.6/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.03
first ⅓ avg 0.01 → last ⅓ avg -0.02
Reaction time550ms+11ms
first ⅓ avg 539ms → last ⅓ avg 550ms
Headshot accuracy18.6%−3.5%
first ⅓ avg 22.1% → last ⅓ avg 18.6%

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

0.14Best match rating · 13–3 · mirage, 8 Feb →
46%Best headshot accuracy · 6–13 · anubis, 28 Feb →
328msFastest reaction time · 13–11 · mirage, 9 Oct →
13–1Biggest win · train, 1 Nov →

Across the last 100 tracked matches.

Highlights

7Longest win streak
L3Current streak
6–9In matches decided by ≤2 rounds
11Overtime games

Map breakdown

ancientBest map · 75% over 12infernoWeakest map · 33% over 6
MapGradePlayedRecordWin rateAvg rating
nukeB2412–1250%-0.01
mirageA1911–858%-0.01
trainC125–742%-0.01
ancientS129–375%-0.01
dust2A95–456%0.00
anubisA95–456%0.01
infernoD62–433%-0.03
overpassD62–433%-0.02
vertigo—32–167%0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

3,399Matches
63%Win rate
1.33Avg K/D
73.1ADR
47%Headshot %

Clutches & streaks

34%1v1 clutch win
20%1v2 clutch win
32Longest win streak

Recent Faceit resultsLLWWL

MapMatchesWin rateAvg K/DAvg kills
Mirage22259%1.2715.7
Ancient12359%1.2415.9
Nuke10957%1.1815.8
Anubis9059%1.2115.9
Dust25963%1.1714.9
Overpass3647%1.1516.2
Train3551%1.1213.1
Vertigo3161%1.5617.0

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

Inventory

$1,442Inventory value23ItemsFull inventory breakdown →
★ Karambit | Crimson Web (Field-Tested)$1,021AWP | Wildfire (Minimal Wear)$106MP9 | Latte Rush (Minimal Wear)$56StatTrak™ AK-47 | Slate (Minimal Wear)$31M4A4 | Desolate Space (Minimal Wear)$29M4A1-S | Decimator (Minimal Wear)$27

Skill profile

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

19.3%Headshot accuracy
38.1%Accuracy (enemy spotted)
44.7%Spray accuracy
76.2%Counter-strafing
11.6°Preaim
553msReaction time
18.4%T opening success
33.9%CT opening success
0.62Enemies flashed / flash
7.7%Flash assists
10.22HE damage / grenade
17.24Flashes / 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. 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 18.3884% — below the 40% mark we flag

Spend your practice time on Inferno

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

33% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke7–13-0.0215%31 Dec →
dust27–13-0.0422%6 Nov →
nuke6–13-0.0330%6 Nov →
mirage13–4-0.0119%6 Nov →
nuke13–100.0311%1 Nov →
inferno11–13-0.0014%1 Nov →
nuke12–50.0438%1 Nov →
train13–10.0914%1 Nov →
nuke9–14-0.0417%1 Nov →
train13–16-0.0621%1 Nov →
overpass13–80.0114%27 Oct →
nuke9–13-0.0023%27 Oct →
mirage13–80.0121%27 Oct →
overpass2–13-0.0225%26 Oct →
inferno13–7-0.0311%26 Oct →
train2–13-0.1024%26 Oct →
nuke7–13-0.108%25 Oct →
dust22–13-0.0315%25 Oct →
train13–100.0414%25 Oct →
nuke13–90.0616%25 Oct →
nuke16–140.0224%24 Oct →
train5–13-0.0724%24 Oct →
mirage6–13-0.0514%24 Oct →
mirage19–15-0.0424%15 Oct →
mirage13–11-0.0218%9 Oct →
overpass14–16-0.0317%9 Oct →
nuke13–5-0.0410%9 Oct →
inferno5–13-0.0718%9 Oct →
dust211–130.0237%9 Oct →
overpass13–60.0116%6 Oct →
dust213–90.0216%6 Oct →
overpass10–13-0.0510%27 Sept →
mirage1–13-0.0613%27 Sept →
train8–13-0.0112%27 Sept →
nuke13–7-0.0313%26 Sept →
nuke13–11-0.049%26 Sept →
train11–13-0.0325%12 Sept →
mirage10–13-0.0417%12 Sept →
dust213–100.0522%10 Sept →
mirage16–13-0.0414%10 Sept →
mirage5–13-0.0810%7 Sept →
inferno7–13-0.0225%7 Sept →
train9–130.0340%6 Sept →
dust214–100.0119%6 Sept →
mirage9–13-0.0522%6 Sept →
mirage13–7-0.0315%4 Sept →
dust213–7-0.0041%4 Sept →
nuke11–13-0.0025%4 Sept →
nuke7–40.0125%3 Sept →
nuke6–10.0428%3 Sept →
dust216–14-0.0312%3 Sept →
mirage7–13-0.0612%1 Sept →
train9–13-0.0626%1 Sept →
train13–40.0415%1 Sept →
overpass9–13-0.0221%31 Aug →
mirage13–60.0118%31 Aug →
nuke13–60.0428%31 Aug →
anubis13–40.0430%20 Jul →
nuke13–100.0316%14 Jun →
dust27–130.0016%14 Jun →
mirage10–130.0025%14 Jun →
nuke5–13-0.0617%13 Jun →
anubis6–13-0.0429%13 Jun →
anubis13–110.0021%26 Apr →
mirage13–30.0318%25 Apr →
train13–20.0314%17 Apr →
ancient13–6-0.0211%8 Feb →
nuke10–13-0.0321%7 Feb →
train13–70.0024%4 Feb →
mirage13–40.0821%6 Jan →
ancient7–13-0.0712%24 Apr →
inferno7–13-0.064%9 Mar →
ancient7–13-0.0224%9 Mar →
nuke9–13-0.0327%6 Mar →
nuke11–13-0.0337%4 Mar →
mirage13–90.1019%4 Mar →
ancient13–20.0324%4 Mar →
ancient13–30.0529%4 Mar →
vertigo13–30.0514%4 Mar →
vertigo14–160.0125%2 Mar →
nuke13–40.0326%2 Mar →
vertigo13–80.0725%2 Mar →
ancient13–60.0418%2 Mar →
ancient13–10-0.0211%29 Feb →
anubis6–13-0.0346%28 Feb →
nuke10–130.0119%28 Feb →
inferno16–130.0129%27 Feb →
anubis8–13-0.0415%26 Feb →
ancient5–1-0.060%26 Feb →
anubis13–40.1225%26 Feb →
ancient13–6-0.0013%26 Feb →
anubis13–70.0018%25 Feb →
anubis13–80.1027%13 Feb →
ancient13–40.0334%12 Feb →
ancient13–11-0.0226%12 Feb →
nuke14–16-0.0020%9 Feb →
mirage13–30.1418%8 Feb →
anubis5–13-0.0732%7 Feb →
mirage11–13-0.0623%6 Feb →
ancient10–13-0.0323%4 Feb →

Match data via Leetify.

Recent teammates

Milestones

Faceit Level 103K ELO Club1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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