Noller

Noller — CS2 Stats

76561199101362785[U:1:1141097057]Steam profile ↗✓ No bans

3,003Tracked matches50%Win rate2020Tracked since
2,754Hours in CS
CSDB Rating5.0 DevelopingPositional Player
Premier CS Rating16,031Purple band · top ~24.3% of ranked players (population est.)
FaceitLevel 5Top 67.6% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 23 Oct 2026 (4 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 3,003 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 16,031 -2,220 14 Apr – 23 Oct · 18 days played
13,81218,251peak 18,25114 Apr23 Oct
19,053Peak Premier in tracked matches
29Days played since 2026-04-14

Premier CS Rating

  • 2,220 below peak (18,251)
  • +1,031 over 30 days · improving
  • -551 over 90 days
  • Next: Pink band at 20,000 — 3,969 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-08-30
  • Blue band first seen 2026-08-30

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 5 among CSDB-tracked players (n=14,283), 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 5 medianLevel 6 medianvs Level 6
Headshot rate44.8%43.8%44.8%meets
Shot accuracy13.7%12.0%12.4%above
Kill/death ratio0.961.021.030.07 short
Match win rate44.6%44.7%45.2%meets

This profile matches the typical Level 6 player on 3 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Level 6 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGNollerFACEITLevel 5STANDINGTop 67.6% of rankedPREMIER16,031 · Purple 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

Aim56
Positioning47
Utility46

0–100 skill scores via Leetify.

Recent form

STEADY45–53–2Last 10045%Win rateLLLLLWWWWW

Last 10 vs previous 10: +10pp win rate · +0.02 avg rating · −2.3pp headshot accuracy · +15ms 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

  • 0–5 · 0% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 19%
  • Avg reaction 528ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 17%
  • Avg reaction 565ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 18%
  • Avg reaction 558ms

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 (+1.2 against its own average).

Aim5.6
Utility4.6
Positioning4.7
Opening Duels1.9
Clutch2.8

Limited utility dependence

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

ZywOo

Plays most like ZywOo 88% playstyle similarity

Most alike: positioning profile, utility contribution.

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. 617ms 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

Aim5.6
Positioning4.7
Utility4.6
Mechanics4.6
Opening Duels4.5
Win Impact5.0

Composite 5.0/10 (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-0.02−0.00
first ⅓ avg -0.01 → last ⅓ avg -0.02
Reaction time618ms−23ms
first ⅓ avg 641ms → last ⅓ avg 618ms
Headshot accuracy18.7%−0.2%
first ⅓ avg 18.9% → last ⅓ avg 18.7%

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 · 13–1 · inferno, 7 Oct →
37%Best headshot accuracy · 13–10 · ancient, 18 Sept →
406msFastest reaction time · 5–13 · inferno, 18 Oct →
13–1Biggest win · inferno, 7 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L5Current streak
10–12In matches decided by ≤2 rounds
12Overtime games

Map breakdown

nukeBest map · 70% over 20ancientWeakest map · 29% over 14
MapGradePlayedRecordWin rateAvg rating
infernoB2412–1250%-0.00
dust2D227–1532%-0.03
nukeS2014–670%-0.01
ancientD144–1029%-0.02
anubisD72–529%-0.02
cacheB63–350%-0.02
mirage—31–233%-0.05
overpass—31–233%-0.05
vertigo—11–0100%0.01

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (29% over 14). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

106,316Lifetime kills
0.96K/D
5,864Matches
44.6%Match win rate
44.8%Headshot % · Top 50% of Level 5 players
13.7%Shot accuracy · Top 50% of Level 5 players
11,742MVPs
2,754Hours (in match)
8,272Bombs planted
1,452Bombs defused

Most-used weapons

AK-4723,644
AUG8,487
AWP5,243
XM10143,356
MAC-103,186

Lifetime map wins

18,869inferno
13,285nuke
9,083dust2
3,252vertigo
699train
46lake
34cbble
26assault

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

Faceit stats

Combat

144Matches
52%Win rate
0.92Avg K/D
70.7ADR
43%Headshot %

Clutches & streaks

34%1v1 clutch win
21%1v2 clutch win
9Longest win streak

Recent Faceit resultsWWLLL

MapMatchesWin rateAvg K/DAvg kills
Inferno2361%1.0414.4
Ancient2143%0.9615.8
Nuke2075%0.9713.3
Dust21650%0.8612.4
Vertigo771%0.9513.1
Mirage520%0.8714.8
Anubis30%0.8713.3
Train1100%0.8214.0

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.

18.5%Headshot accuracy
34.1%Accuracy (enemy spotted)
29.9%Spray accuracy
70.8%Counter-strafing
9.5°Preaim
617msReaction time
52.3%T opening success
43.9%CT opening success
0.45Enemies flashed / flash
2.4%Flash assists
11.04HE damage / grenade
4.98Flashes / 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 0.4487 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Ancient

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

29% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke13–16-0.0116%18 Oct →
nuke8–13-0.0223%18 Oct →
inferno5–13-0.0221%18 Oct →
nuke13–16-0.0623%18 Oct →
inferno13–16-0.0013%15 Oct →
vertigo13–50.0115%15 Oct →
ancient13–110.0322%15 Oct →
inferno13–110.0513%13 Oct →
anubis13–40.009%13 Oct →
nuke13–7-0.0119%13 Oct →
mirage11–13-0.0818%13 Oct →
nuke13–10-0.0329%10 Oct →
nuke7–13-0.0619%10 Oct →
anubis6–130.0011%7 Oct →
nuke13–6-0.0321%7 Oct →
inferno13–10.0919%7 Oct →
dust24–13-0.0921%7 Oct →
dust26–13-0.0517%7 Oct →
ancient9–13-0.0516%1 Oct →
inferno13–80.0325%1 Oct →
nuke13–10-0.0119%1 Oct →
dust211–13-0.0330%1 Oct →
nuke7–13-0.049%26 Sept →
cache13–8-0.0216%26 Sept →
nuke13–5-0.0427%25 Sept →
mirage13–110.0223%25 Sept →
nuke13–10-0.0212%24 Sept →
dust23–13-0.0121%24 Sept →
dust24–13-0.0216%24 Sept →
inferno13–10-0.0016%24 Sept →
cache15–15-0.0125%24 Sept →
inferno11–13-0.0420%20 Sept →
dust213–9-0.0117%20 Sept →
dust213–8-0.0214%20 Sept →
ancient5–130.0316%20 Sept →
cache14–16-0.0613%20 Sept →
anubis7–13-0.0228%20 Sept →
ancient6–13-0.0617%20 Sept →
anubis9–13-0.0111%19 Sept →
inferno13–90.0219%19 Sept →
nuke13–8-0.0213%19 Sept →
anubis7–13-0.0111%19 Sept →
dust213–110.0316%19 Sept →
ancient13–10-0.0237%18 Sept →
inferno13–100.0014%18 Sept →
dust28–13-0.0125%18 Sept →
inferno13–7-0.0525%18 Sept →
nuke16–130.0223%17 Sept →
dust28–13-0.028%17 Sept →
dust213–70.0422%17 Sept →
ancient3–13-0.0423%9 Sept →
ancient14–16-0.0218%6 Sept →
dust211–13-0.0314%6 Sept →
mirage8–13-0.0819%6 Sept →
dust28–13-0.0311%16 Aug →
dust213–7-0.0712%16 Aug →
inferno6–130.0219%11 Aug →
inferno10–13-0.0420%8 Aug →
dust26–13-0.0520%8 Aug →
nuke13–2-0.0219%8 Aug →
dust210–13-0.0620%8 Aug →
dust214–16-0.0810%29 Jul →
ancient11–13-0.0512%29 Jul →
dust25–13-0.0422%28 Jul →
ancient13–110.006%28 Jul →
inferno10–13-0.0428%28 Jul →
nuke13–8-0.0217%28 Jul →
dust213–5-0.009%26 Jul →
inferno13–11-0.039%26 Jul →
dust213–8-0.0510%26 Jul →
inferno11–130.0235%26 Jul →
ancient7–13-0.0023%25 Jul →
inferno13–80.0121%25 Jul →
nuke13–110.0313%25 Jul →
cache6–13-0.0514%22 Jul →
inferno15–15-0.0219%22 Jul →
anubis7–13-0.0717%22 Jul →
inferno13–110.0419%22 Jul →
nuke16–140.0522%21 Jul →
ancient13–90.0111%21 Jul →
inferno7–130.0310%21 Jul →
inferno10–13-0.044%21 Jul →
overpass9–13-0.0519%4 Jun →
inferno11–13-0.0412%4 Jun →
anubis16–13-0.0122%17 May →
nuke13–10-0.0128%17 May →
overpass13–3-0.0620%17 May →
inferno13–9-0.0319%17 May →
inferno11–130.0114%4 May →
inferno13–11-0.0133%4 May →
nuke12–160.0228%4 May →
ancient4–13-0.0618%30 Apr →
overpass11–13-0.0326%30 Apr →
ancient5–13-0.0822%30 Apr →
cache13–80.0329%30 Apr →
cache13–7-0.0221%30 Apr →
dust26–13-0.0215%14 Apr →
ancient5–13-0.0118%14 Apr →
nuke13–8-0.0128%14 Apr →
dust21–5-0.0218%14 Apr →

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 →

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