nms

nms — CS2 Stats

76561198005137939[U:1:44872211]Steam profile ↗✓ No bans

167Tracked matches64%Win rate2020Tracked since
583Hours in CS
CSDB Rating5.7 SolidPositional Player
FaceitLevel 4Top 81.0% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 19 Sep 2026 (25 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 167 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 19,786 +9,913 10 Nov – 21 Jan · 4 days played
9,87319,786peak 19,78610 Nov21 Jan
19,786Peak Premier in tracked matches
34Days played since 2022-08-25

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

Compare periods

Last 30 days vs previous 30

No matches recorded between 19 Sep 2026 and 14 Oct 2026.

Measured 19 Sep 2026 → 14 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Level 4 among CSDB-tracked players (n=14,247), 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 rate40.8%42.7%43.7%2.9% short
Shot accuracy19.5%11.3%12.0%above
Kill/death ratio1.140.991.02above
Match win rate42.1%43.9%44.7%2.6% short

This profile matches the typical Level 5 player on 2 of 4 comparable metrics.

Widest gap: Headshot rate. 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.GGnmsFACEITLevel 4STANDINGTop 81.0% of rankedcsdb.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

Aim70
Positioning58
Utility36

0–100 skill scores via Leetify.

Recent form

HOT49–48–3Last 10049%Win rateWWWWLWLWLW

Last 10 vs previous 10: +20pp win rate · −0.02 avg rating · +4.9pp headshot accuracy · −35ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (−0.02), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 4–1 · 80% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 23%
  • Avg reaction 494ms

Last 10

  • 7–3 · 70% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 21%
  • Avg reaction 513ms

Last 20

  • 12–7–1 · 60% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 18%
  • Avg reaction 530ms

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 (+1.1 against its own average).

Aim7.0
Utility3.6
Positioning5.8
Opening Duels4.8

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

jL

Plays most like jL 89% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower aim profile; lower utility contribution.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 49% on CT to 24% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim7.0
Positioning5.8
Utility3.6
Mechanics4.5
Opening Duels2.4
Win Impact9.8

Composite 5.7/10 (Solid), 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-0.01+0.00
first ⅓ avg -0.01 → last ⅓ avg -0.01
Reaction time517ms−79ms
first ⅓ avg 596ms → last ⅓ avg 517ms
Headshot accuracy17.4%+4.1%
first ⅓ avg 13.2% → last ⅓ avg 17.4%

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

0.09Best match rating · 16–11 · overpass, 11 Nov →
30%Best headshot accuracy · 13–6 · inferno, 26 Nov →
406msFastest reaction time · 5–13 · mirage, 12 Sept →
16–3Biggest win · overpass, 15 Apr →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W4Current streak
12–11In matches decided by ≤2 rounds
76Overtime games

Map breakdown

overpassBest map · 81% over 16anubisWeakest map · 33% over 6
MapGradePlayedRecordWin rateAvg rating
infernoB2513–1252%0.00
overpassS1613–381%0.02
nukeC146–843%-0.01
mirageC125–742%-0.01
dust2C114–736%-0.03
anubisD62–433%-0.02
ancientC52–340%-0.04
cacheC52–340%-0.02
train—22–0100%0.03
cbble—10–10%-0.05
office—10–10%0.00
vertigo—10–10%0.01
tuscan—10–10%-0.03

Across the last 100 tracked matches.

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

Lifetime stats

32,159Lifetime kills
1.14K/D · Top 25% of Level 4 players
1,317Matches
42.1%Match win rate
40.8%Headshot %
19.5%Shot accuracy · Top 5% of Level 4 players
2,712MVPs
583Hours (in match)
2,030Bombs planted
418Bombs defused

Most-used weapons

Lifetime map wins

2,464inferno
1,545dust2
775cbble
580train
449nuke
134vertigo
25lake
14aztec

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

Faceit stats

Combat

158Matches
52%Win rate
1.16Avg K/D
—ADR
31%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
6Longest win streak

Recent Faceit resultsLLLLL

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
35.7%Accuracy (enemy spotted)
33.1%Spray accuracy
70.2%Counter-strafing
8.6°Preaim
518msReaction time
24.4%T opening success
49.2%CT opening success
0.51Enemies flashed / flash
4.1%Flash assists
6.83HE damage / grenade
10.02Flashes / 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 24.3609% — below the 40% mark we flag

Spend your practice time on Anubis

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.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient13–11-0.0118%13 Sept →
anubis13–6-0.0027%13 Sept →
inferno13–2-0.0621%12 Sept →
nuke13–6-0.0725%12 Sept →
anubis10–130.0426%12 Sept →
inferno13–90.0514%12 Sept →
dust23–13-0.0518%12 Sept →
cache13–8-0.0017%12 Sept →
mirage5–13-0.0721%12 Sept →
dust213–7-0.0619%12 Sept →
ancient11–13-0.0517%12 Sept →
overpass8–13-0.0320%12 Sept →
nuke9–13-0.0414%12 Sept →
inferno13–50.0614%21 Jan →
anubis7–13-0.118%21 Jan →
overpass13–11-0.0218%21 Jan →
inferno13–60.0715%5 Jan →
overpass13–110.0712%5 Jan →
inferno13–60.0130%26 Nov →
nuke15–15-0.039%26 Nov →
anubis13–110.0123%26 Nov →
inferno15–150.0020%10 Nov →
nuke11–130.0217%10 Nov →
nuke13–30.0819%10 Nov →
overpass16–100.0215%1 Sept →
inferno14–16-0.0311%15 Apr →
overpass16–70.0215%15 Apr →
nuke10–16-0.0216%15 Apr →
overpass16–30.0010%15 Apr →
ancient16–130.029%15 Apr →
dust28–160.0117%15 Apr →
cache10–16-0.0212%15 Apr →
dust215–15-0.0124%14 Apr →
inferno20–220.0215%14 Apr →
cbble14–16-0.058%14 Apr →
nuke9–16-0.069%6 Apr →
mirage12–16-0.0313%6 Apr →
overpass16–19-0.0410%6 Apr →
inferno17–190.0213%6 Apr →
nuke16–140.027%4 Apr →
dust216–9-0.0313%28 Mar →
inferno16–90.0611%25 Mar →
overpass16–9-0.0213%25 Mar →
mirage12–160.0123%25 Mar →
cache16–110.0613%25 Mar →
inferno7–16-0.045%25 Mar →
inferno13–160.0513%23 Mar →
mirage10–16-0.0112%23 Mar →
nuke9–16-0.0125%19 Mar →
overpass16–90.089%19 Mar →
inferno14–160.0219%17 Mar →
office2–160.0013%17 Mar →
dust214–16-0.0710%17 Mar →
ancient17–19-0.037%17 Mar →
inferno14–16-0.0215%17 Mar →
overpass14–16-0.0314%16 Mar →
mirage16–6-0.0113%6 Mar →
inferno9–16-0.0217%6 Mar →
mirage16–13-0.0119%5 Mar →
anubis6–16-0.0710%5 Mar →
overpass16–14-0.0114%4 Mar →
inferno16–14-0.0218%4 Mar →
mirage16–130.0110%4 Mar →
ancient3–16-0.1118%4 Mar →
anubis15–190.0225%24 Feb →
overpass16–80.0716%24 Feb →
nuke10–16-0.0813%24 Feb →
vertigo11–160.017%24 Feb →
inferno22–200.0221%24 Feb →
mirage10–16-0.0210%17 Feb →
overpass16–100.0011%17 Feb →
inferno16–10-0.036%17 Feb →
inferno16–11-0.0214%15 Jan →
overpass16–70.0516%15 Jan →
cache7–16-0.1010%15 Jan →
mirage9–16-0.086%15 Jan →
dust210–16-0.018%15 Jan →
train16–110.019%13 Jan →
nuke9–160.0217%13 Jan →
inferno11–160.058%13 Jan →
overpass16–12-0.0017%13 Jan →
cache5–16-0.0418%11 Jan →
inferno16–14-0.0315%22 Dec →
mirage16–110.0513%16 Dec →
dust24–16-0.0617%11 Nov →
tuscan5–16-0.0315%11 Nov →
overpass16–110.0913%11 Nov →
dust216–10-0.0411%21 Oct →
nuke16–14-0.0520%29 Sept →
inferno16–13-0.0812%29 Sept →
inferno10–16-0.0525%16 Sept →
nuke9–10.0616%16 Sept →
inferno16–70.079%16 Sept →
dust210–20.0017%16 Sept →
inferno15–19-0.058%3 Sept →
dust27–16-0.0517%3 Sept →
mirage9–16-0.0218%3 Sept →
mirage16–140.059%1 Sept →
nuke16–70.0511%1 Sept →
train16–140.0513%25 Aug →

Match data via Leetify.

Recent teammates

Milestones

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

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.