1Skilled1

1Skilled1 — CS2 Stats

NO76561199006641272[U:1:1046375544]Steam profile ↗✓ No bans

2,065Tracked matches65%Win rate2021Tracked since
4,663Hours in CS8Hrs last 2 wks
CSDB Rating6.8 SolidSupport
Premier CS Rating20,499Top 50% of 213,211 CSDB-tracked playersPink band · top ~8% of ranked players (population est.)
CSDB Leaderboard#76796 of 259864 tracked
FaceitLevel 4Top 81.0% of ranked FACEIT players
WingmanSilver Elite Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 14 Oct 2026 (21 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 20,499 +1,761 29 Jul – 14 Oct · 15 days played
17,73320,499peak 20,49929 Jul14 Oct
20,499Peak Premier in tracked matches
37Days played since 2026-07-29

Premier CS Rating

  • At peak — 20,499
  • +1,270 over 30 days · improving
  • +1,761 over 90 days
  • Next: Red band at 25,000 — 4,501 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-09-21
  • Blue band first seen 2026-09-21

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

How this compares with the same rank

Median values for Level 4 among CSDB-tracked players (n=14,630), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerLevel 4 medianLevel 5 medianvs Level 5
Headshot rate38.9%42.7%43.8%4.8% short
Shot accuracy10.1%11.2%12.0%1.9% short
Kill/death ratio0.980.991.020.03 short
Match win rate43.8%43.9%44.7%meets

This profile matches the typical Level 5 player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 5 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GG1Skilled1FACEITLevel 4STANDINGTop 81.0% of rankedPREMIER20,499 · Pink bandcsdb.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

Aim68
Positioning57
Utility66

0–100 skill scores via Leetify.

Recent form

STEADY51–42–7Last 10051%Win rateLLWTWTWLWW

Last 10 vs previous 10: +10pp win rate · −0.01 avg rating · +0.9pp headshot accuracy · +35ms 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

  • 2–2–1 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 25%
  • Avg reaction 686ms

Last 10

  • 5–3–2 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 22%
  • Avg reaction 655ms

Last 20

  • 9–7–4 · 45% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 21%
  • Avg reaction 637ms

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 (+2.3 against its own average).

Aim6.8
Utility6.6
Positioning5.7
Opening Duels3.2
Clutch1.6

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

Twistzz

Plays most like Twistzz 84% 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

Reaction time. 611ms 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

Aim6.8
Positioning5.7
Utility6.6
Mechanics6.7
Opening Duels4.6
Win Impact10.0

Composite 6.8/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01+0.01
first ⅓ avg -0.00 → last ⅓ avg 0.01
Reaction time602ms−53ms
first ⅓ avg 655ms → last ⅓ avg 602ms
Headshot accuracy20.1%+0.3%
first ⅓ avg 19.8% → last ⅓ avg 20.1%

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

0.16Best match rating · 13–6 · dust2, 23 Sept →
41%Best headshot accuracy · 12–12 · inferno, 19 Sept →
414msFastest reaction time · 3–13 · mirage, 10 Sept →
13–2Biggest win · mirage, 15 Oct →

Across the last 100 tracked matches.

Highlights

7Longest win streak
L2Current streak
6–5In matches decided by ≤2 rounds
2Overtime games

Map breakdown

ancientBest map · 58% over 12infernoWeakest map · 45% over 11
MapGradePlayedRecordWin rateAvg rating
dust2B2814–1450%0.01
mirageB178–947%0.01
cacheA148–657%-0.01
ancientA127–558%0.01
infernoB115–645%0.00
trainA74–357%0.02
anubisB63–350%-0.00
nuke—31–233%0.02
overpass—21–150%-0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (45% over 11). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

142,867Lifetime kills
0.98K/D
8,184Matches
43.8%Match win rate
38.9%Headshot %
10.1%Shot accuracy
23,790MVPs
2,485Hours (in match)
6,372Bombs planted
1,278Bombs defused

Most-used weapons

AK-4741,741
AWP28,552
Molotov6,984
Knife5,764
MP93,744

Lifetime map wins

13,803inferno
7,163dust2
6,649vertigo
3,393nuke
2,236train
515cbble
92lake
78office

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

60Matches
48%Win rate
1.08Avg K/D
84.4ADR
45%Headshot %

Clutches & streaks

28%1v1 clutch win
7%1v2 clutch win
6Longest win streak

Recent Faceit resultsWLWLL

MapMatchesWin rateAvg K/DAvg kills
Mirage1457%1.3215.6
Dust21164%1.0714.4
Ancient1060%1.3615.4
Inferno714%0.9414.6
Anubis250%1.0617.5
Train250%0.9414.0
Nuke20%0.6412.5
Cache250%1.1616.0

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.

19.9%Headshot accuracy
33.9%Accuracy (enemy spotted)
31.1%Spray accuracy
80.4%Counter-strafing
8.9°Preaim
611msReaction time
50.2%T opening success
47.0%CT opening success
0.53Enemies flashed / flash
10.1%Flash assists
12.37HE damage / grenade
10.43Flashes / match

Recommended for you

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.

45% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno9–13-0.0329%30 Oct →
cache8–130.0324%30 Oct →
dust213–50.0934%30 Oct →
mirage12–120.0331%30 Oct →
cache13–60.008%23 Oct →
cache12–12-0.0118%22 Oct →
dust213–5-0.0320%18 Oct →
dust23–13-0.0225%18 Oct →
ancient13–90.0510%17 Oct →
mirage13–2-0.0120%15 Oct →
dust211–13-0.0222%14 Oct →
dust212–120.0322%14 Oct →
overpass13–7-0.0613%14 Oct →
ancient8–13-0.0112%14 Oct →
cache16–14-0.0820%14 Oct →
inferno13–20.0423%14 Oct →
train1–13-0.0126%13 Oct →
inferno12–120.1420%13 Oct →
dust210–130.0725%13 Oct →
ancient13–80.0729%12 Oct →
ancient13–110.0423%11 Oct →
anubis13–9-0.0218%11 Oct →
dust213–10-0.0416%11 Oct →
dust213–50.0513%11 Oct →
mirage13–100.0011%11 Oct →
nuke13–30.0515%6 Oct →
cache7–13-0.0615%6 Oct →
inferno8–13-0.0323%6 Oct →
dust213–3-0.0217%6 Oct →
cache13–90.0517%4 Oct →
anubis11–13-0.0613%4 Oct →
inferno0–8-0.0125%4 Oct →
ancient13–60.1029%1 Oct →
mirage13–60.1218%27 Sept →
anubis7–13-0.0120%26 Sept →
anubis13–40.0727%26 Sept →
dust213–60.1629%23 Sept →
anubis2–13-0.1014%23 Sept →
mirage6–130.0116%23 Sept →
dust23–13-0.0511%22 Sept →
dust213–7-0.0018%22 Sept →
mirage10–130.0129%22 Sept →
train13–80.0718%20 Sept →
overpass10–130.0115%19 Sept →
ancient13–7-0.0126%19 Sept →
mirage11–130.0430%19 Sept →
inferno12–120.0341%19 Sept →
train13–4-0.0230%15 Sept →
dust28–13-0.0020%15 Sept →
ancient11–130.0232%15 Sept →
train13–40.0224%15 Sept →
dust213–110.0121%13 Sept →
inferno13–9-0.0627%13 Sept →
mirage10–13-0.0111%10 Sept →
train9–130.0626%10 Sept →
dust213–30.098%10 Sept →
mirage3–13-0.0414%10 Sept →
mirage11–130.0217%8 Sept →
cache13–70.0520%8 Sept →
inferno13–90.0421%7 Sept →
cache13–90.0221%7 Sept →
dust22–13-0.0427%7 Sept →
dust213–60.0222%6 Sept →
mirage10–13-0.0314%6 Sept →
dust28–130.0123%6 Sept →
ancient7–13-0.1114%4 Sept →
dust213–11-0.0321%4 Sept →
mirage13–80.0017%4 Sept →
cache12–12-0.0124%4 Sept →
mirage13–110.0212%4 Sept →
dust29–13-0.1011%4 Sept →
dust213–60.0115%30 Aug →
nuke9–13-0.0529%30 Aug →
mirage13–90.0219%30 Aug →
inferno13–10-0.0411%23 Aug →
mirage13–80.0236%22 Aug →
ancient10–13-0.0322%22 Aug →
anubis13–50.1017%22 Aug →
dust23–13-0.0620%16 Aug →
ancient13–11-0.0126%15 Aug →
inferno0–13-0.0533%15 Aug →
cache5–13-0.0010%5 Aug →
nuke6–130.0517%3 Aug →
dust213–30.0521%3 Aug →
dust29–130.0516%3 Aug →
ancient13–90.0938%2 Aug →
mirage9–13-0.0316%2 Aug →
ancient12–16-0.0712%2 Aug →
train8–13-0.0110%1 Aug →
dust25–130.0732%1 Aug →
mirage13–6-0.0115%1 Aug →
cache13–8-0.0524%1 Aug →
cache13–8-0.0816%1 Aug →
dust213–7-0.0114%1 Aug →
cache13–80.0318%30 Jul →
train13–100.0130%30 Jul →
dust212–12-0.0315%30 Jul →
cache5–13-0.0613%30 Jul →
inferno13–100.0019%29 Jul →
dust23–130.0427%29 Jul →

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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