UNIX

UNIX — CS2 Stats

DK76561199030559468[U:1:1070293740]Steam profile ↗✓ No bans

1,835Tracked matches57%Win rate2020Tracked since
CSDB Rating5.1 DevelopingSupport
FaceitLevel 10 · 2,431 ELOTop 12.4% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGUNIXFACEITLevel 10 · 2,431 ELOSTANDINGTop 12.4% of rankedcsdb.gg/stats

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Performance scores

Aim55
Positioning54
Utility59

0–100 skill scores via Leetify.

Recent form

HOT49–51Last 10049%Win rateWWLWLLWWWW

Last 10 vs previous 10: +20pp win rate · +0.03 avg rating · +6.0pp headshot accuracy · −11ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 23%
  • Avg reaction 533ms

Last 10

  • 7–3 · 70% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 25%
  • Avg reaction 565ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 22%
  • Avg reaction 570ms

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 (+1.3 against its own average).

Aim5.5
Utility5.9
Positioning5.4
Opening Duels4.5
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

m0NESY

Plays most like m0NESY 79% playstyle similarity

Most alike: utility contribution, positioning profile.

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

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

T-side openings. Opening success drops from 52% on CT to 36% on T — the same duels are being taken with worse setups on the attacking side.

Counter-strafing. Only 63% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim5.5
Positioning5.4
Utility5.9
Mechanics2.9
Opening Duels3.5
Win Impact7.2

Composite 5.1/10 (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-0.00−0.01
first ⅓ avg 0.01 → last ⅓ avg -0.00
Reaction time553ms+6ms
first ⅓ avg 547ms → last ⅓ avg 553ms
Headshot accuracy20.6%+2.8%
first ⅓ avg 17.8% → last ⅓ avg 20.6%

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

0.15Best match rating · 13–6 · inferno, 18 Jul →
37%Best headshot accuracy · 13–9 · nuke, 12 Feb →
359msFastest reaction time · 7–13 · inferno, 16 May →
13–2Biggest win · inferno, 11 Feb →

Across the last 100 tracked matches.

Highlights

9Longest win streak
W2Current streak
11–12In matches decided by ≤2 rounds
10Overtime games

Map breakdown

nukeBest map · 70% over 20dust2Weakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
infernoB2714–1352%0.01
ancientC2410–1442%0.00
nukeS2014–670%-0.00
mirageD124–833%0.02
overpassA74–357%0.04
dust2D51–420%-0.00
anubis—31–233%0.01
cache—10–10%-0.03
train—11–0100%0.04

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

2,412Matches
51%Win rate
1.10Avg K/D
84.2ADR
41%Headshot %

Clutches & streaks

34%1v1 clutch win
19%1v2 clutch win
11Longest win streak

Recent Faceit resultsWLWWW

MapMatchesWin rateAvg K/DAvg kills
Inferno36657%1.1717.6
Ancient31653%1.1517.5
Nuke18756%1.1417.1
Mirage18240%1.0817.0
Dust28348%1.0616.3
Anubis5542%1.0715.6
Vertigo5357%1.2117.8
Overpass5042%1.0916.7

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.

20.8%Headshot accuracy
28.3%Accuracy (enemy spotted)
32.4%Spray accuracy
63.1%Counter-strafing
8.6°Preaim
545msReaction time
36.0%T opening success
51.9%CT opening success
0.56Enemies flashed / flash
4.4%Flash assists
9.25HE damage / grenade
10.32Flashes / 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 35.9604% — below the 40% mark we flag

Spend your practice time on Dust 2

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno13–10-0.0329%8 Nov →
nuke13–30.0523%4 Nov →
nuke3–13-0.088%10 Aug →
inferno19–17-0.0230%22 Jul →
nuke2–13-0.0427%22 Jul →
dust214–16-0.0420%19 Jul →
ancient13–9-0.0026%19 Jul →
mirage13–50.1031%18 Jul →
inferno13–60.1533%18 Jul →
ancient13–60.0420%18 Jul →
nuke13–60.0115%17 Jul →
ancient13–5-0.0315%17 Jul →
anubis13–70.024%17 Jul →
mirage13–100.0519%17 Jul →
inferno13–40.0119%13 Jul →
inferno10–13-0.059%8 Jul →
dust211–13-0.0433%8 Jul →
cache11–13-0.0320%7 Jul →
inferno11–130.0123%7 Jul →
nuke7–13-0.0931%5 Jul →
mirage17–190.0321%5 Jul →
dust28–13-0.0223%4 Jul →
nuke13–7-0.008%4 Jul →
overpass7–13-0.0123%3 Jul →
inferno13–70.0919%28 Jun →
ancient13–50.0320%28 Jun →
ancient16–13-0.0115%28 Jun →
inferno6–13-0.0219%27 Jun →
inferno13–6-0.0113%27 Jun →
dust23–13-0.0325%27 Jun →
mirage11–13-0.0421%20 Jun →
inferno6–13-0.0414%20 Jun →
inferno13–11-0.0127%16 May →
inferno7–13-0.0211%16 May →
nuke13–80.0330%16 May →
mirage10–130.0114%10 May →
inferno13–90.0335%10 May →
overpass5–130.0011%9 May →
nuke13–110.0224%9 May →
inferno5–13-0.0623%8 May →
inferno13–11-0.046%8 May →
ancient16–140.0117%3 May →
ancient13–110.0414%3 May →
ancient5–130.0224%25 Apr →
overpass13–100.0317%9 Mar →
inferno2–13-0.0216%9 Mar →
ancient10–13-0.039%9 Mar →
ancient13–16-0.0319%22 Feb →
inferno9–13-0.0310%15 Feb →
nuke13–90.0337%12 Feb →
ancient11–13-0.0523%12 Feb →
overpass13–50.0417%12 Feb →
mirage11–130.0721%11 Feb →
inferno13–20.1317%11 Feb →
nuke10–13-0.0028%11 Feb →
ancient9–13-0.0122%10 Feb →
nuke13–90.0024%10 Feb →
mirage7–13-0.0221%8 Feb →
nuke13–50.0419%8 Feb →
ancient5–13-0.028%8 Feb →
ancient11–13-0.0211%8 Feb →
ancient9–130.0924%8 Feb →
anubis6–130.0317%8 Feb →
nuke13–70.0522%6 Feb →
mirage6–130.0321%6 Feb →
overpass13–110.1120%4 Feb →
dust213–70.1217%4 Feb →
nuke13–110.0121%4 Feb →
ancient5–13-0.036%2 Feb →
nuke16–140.0320%1 Feb →
anubis13–16-0.0215%24 Jan →
mirage13–9-0.0313%15 Jan →
ancient13–30.0722%15 Jan →
inferno13–90.0116%14 Jan →
inferno11–130.0323%11 Jan →
inferno9–13-0.0120%10 Jan →
inferno13–110.0220%10 Jan →
nuke11–13-0.0426%5 Jan →
nuke2–7-0.0811%4 Jan →
mirage12–160.0025%4 Jan →
nuke13–60.0326%4 Jan →
ancient6–13-0.0218%4 Jan →
overpass13–90.0821%3 Jan →
nuke13–10-0.027%3 Jan →
inferno9–130.015%3 Jan →
ancient13–16-0.0426%3 Jan →
inferno13–110.0122%2 Jan →
ancient13–70.0819%2 Jan →
mirage13–100.0617%2 Jan →
inferno2–13-0.0415%2 Jan →
mirage5–13-0.0518%2 Jan →
overpass10–130.0212%2 Jan →
ancient9–130.0117%1 Jan →
inferno8–130.0019%1 Jan →
train13–60.0423%31 Dec →
ancient3–13-0.097%31 Dec →
ancient11–130.029%22 Dec →
nuke13–7-0.0228%22 Dec →
ancient13–80.0822%22 Dec →
inferno13–70.0622%22 Dec →

Match data via Leetify.

Recent teammates

Milestones

Faceit Level 102K ELO1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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