Totallynoob

Totallynoob — CS2 Stats

NO76561198152092421[U:1:191826693]Steam profile ↗✓ No bans

337Tracked matches40%Win rate2020Tracked since
885Hours in CS
CSDB Rating3.4 LearningPositional Player
FaceitLevel 3Top 90.6% of ranked FACEIT players
Ladder ranks via Leetify
Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 56 days played since 4 Feb 2024. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 8,737 -1,375 4 Feb – 9 Jan · 37 days played
8,38810,745peak 10,7454 Feb9 Jan
10,745Peak Premier in tracked matches
56Days played since 2024-02-04

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 3 among CSDB-tracked players (n=9,584), 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 3 medianLevel 4 medianvs Level 4
Headshot rate36.2%41.9%42.7%6.5% short
Shot accuracy18.0%12.2%11.3%above
Kill/death ratio0.760.980.990.23 short
Match win rate36.8%43.3%43.9%7.1% short

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

Widest gap: Kill/death ratio. That is the metric furthest from the Level 4 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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CSDB.GGTotallynoobFACEITLevel 3STANDINGTop 90.6% of rankedcsdb.gg/stats

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Performance scores

Aim47
Positioning35
Utility10

0–100 skill scores via Leetify.

Recent form

COLD36–56–8Last 10036%Win rateLLLLTWTWWL

Last 10 vs previous 10: 0pp win rate · +0.02 avg rating · −0.2pp headshot accuracy · −31ms reaction

Win rate 0pp 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

  • 0–4–1 · 0% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 15%
  • Avg reaction 656ms

Last 10

  • 3–5–2 · 30% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 17%
  • Avg reaction 642ms

Last 20

  • 6–10–4 · 30% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 17%
  • Avg reaction 657ms

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 (+1.7 against its own average).

Aim4.7
Utility1.0
Positioning3.5
Opening Duels1.0

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

iM

Plays most like iM 88% playstyle similarity

Most alike: positioning profile, opening-duel success.

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.

Reaction time. 673ms 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

Aim4.7
Positioning3.5
Utility1.0
Mechanics6.5
Opening Duels0.2
Win Impact1.7

Composite 3.4/10 (Learning), 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-0.04+0.01
first ⅓ avg -0.05 → last ⅓ avg -0.04
Reaction time677ms+20ms
first ⅓ avg 657ms → last ⅓ avg 677ms
Headshot accuracy18.1%−1.9%
first ⅓ avg 20.0% → last ⅓ avg 18.1%

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

0.09Best match rating · 13–5 · vertigo, 23 Mar →
44%Best headshot accuracy · 13–8 · mirage, 3 May →
422msFastest reaction time · 4–13 · mirage, 5 Apr →
13–1Biggest win · anubis, 5 Apr →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L4Current streak
3–11In matches decided by ≤2 rounds
7Overtime games

Map breakdown

mirageBest map · 58% over 26ancientWeakest map · 0% over 11
MapGradePlayedRecordWin rateAvg rating
mirageA2615–1158%-0.03
vertigoD186–1233%-0.04
dust2C135–838%-0.05
ancientD110–110%-0.04
anubisA116–555%-0.07
nukeD81–713%-0.06
train—42–250%-0.03
office—41–325%-0.04
cache—10–10%-0.01
overpass—10–10%-0.09
italy—10–10%-0.11
thera—10–10%-0.04
inferno—10–10%0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (0% over 11). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

32,761Lifetime kills
0.76K/D
2,375Matches
36.8%Match win rate
36.2%Headshot %
18.0%Shot accuracy · Top 25% of Level 3 players
3,221MVPs
885Hours (in match)
931Bombs planted
340Bombs defused

Most-used weapons

Lifetime map wins

2,326dust2
807inferno
735nuke
569office
519lake
380train
370vertigo
286safehouse

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

Faceit stats

Combat

17Matches
35%Win rate
0.62Avg K/D
—ADR
37%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
2Longest win streak

Recent Faceit resultsLLLLW

MapMatchesWin rateAvg K/DAvg kills
Dust210%0.294.0
Mirage1100%0.7710.0

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.

17.6%Headshot accuracy
30.3%Accuracy (enemy spotted)
29.8%Spray accuracy
79.2%Counter-strafing
10.2°Preaim
673msReaction time
23.8%T opening success
31.5%CT opening success
0.48Enemies flashed / flash
4.8%Flash assists
10.44HE damage / grenade
5.77Flashes / 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 0.4788 — below the 0.5 mark we flag

    Grenade Lineups →
  2. 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 23.7815% — below the 40% mark we flag

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.

0% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient5–13-0.0615%17 Aug →
cache11–13-0.0120%3 May →
overpass5–13-0.0918%5 Apr →
mirage11–13-0.069%5 Apr →
mirage12–12-0.0114%23 Mar →
vertigo13–50.0929%23 Mar →
ancient12–12-0.049%16 Mar →
mirage13–110.0218%6 Feb →
mirage13–8-0.027%6 Feb →
train8–13-0.0532%6 Feb →
train13–6-0.0117%1 Feb →
mirage13–40.0215%1 Feb →
ancient5–13-0.0219%1 Feb →
ancient12–12-0.0712%16 Jan →
office4–13-0.0529%16 Jan →
mirage13–6-0.0118%9 Jan →
anubis10–13-0.0716%4 Jan →
italy12–12-0.1111%4 Jan →
dust28–13-0.1225%4 Jan →
ancient6–13-0.0213%21 Dec →
dust20–9-0.0623%21 Dec →
train13–9-0.0324%3 Dec →
anubis13–8-0.0517%3 Dec →
train11–13-0.0320%26 Nov →
dust212–120.0012%24 Nov →
vertigo11–13-0.0827%2 Nov →
vertigo13–16-0.0228%31 Oct →
mirage13–80.0422%26 Oct →
dust213–7-0.0410%26 Oct →
vertigo11–13-0.076%26 Oct →
nuke2–13-0.1011%15 Oct →
dust29–13-0.0723%15 Oct →
dust27–13-0.0829%14 Oct →
vertigo13–50.0822%29 Sept →
anubis2–13-0.1113%7 Sept →
thera4–13-0.0430%7 Sept →
office12–12-0.0623%7 Sept →
dust213–90.0123%7 Sept →
ancient10–13-0.0221%7 Sept →
mirage4–13-0.1014%2 Sept →
vertigo13–9-0.0711%2 Sept →
vertigo11–13-0.057%19 Aug →
anubis4–13-0.075%11 Jul →
ancient7–13-0.0123%24 May →
mirage16–14-0.0425%22 May →
dust213–7-0.026%21 May →
mirage13–4-0.0527%4 May →
dust25–13-0.1137%3 May →
mirage13–8-0.0544%3 May →
dust213–8-0.0136%2 May →
vertigo13–7-0.0022%2 May →
dust28–13-0.0514%30 Apr →
anubis13–10-0.088%30 Apr →
dust22–13-0.0714%26 Apr →
mirage7–13-0.0319%22 Apr →
vertigo13–40.0113%18 Apr →
nuke9–13-0.0810%17 Apr →
mirage8–13-0.0519%16 Apr →
nuke14–16-0.0624%16 Apr →
vertigo7–13-0.0421%15 Apr →
nuke13–110.0228%14 Apr →
vertigo2–13-0.0817%13 Apr →
vertigo13–5-0.0333%13 Apr →
vertigo9–13-0.0921%9 Apr →
mirage13–10-0.0213%8 Apr →
mirage13–6-0.0026%6 Apr →
vertigo8–13-0.1011%6 Apr →
mirage11–13-0.0721%6 Apr →
mirage9–13-0.0815%6 Apr →
ancient7–13-0.0331%6 Apr →
anubis13–1-0.0616%5 Apr →
mirage13–9-0.0918%5 Apr →
nuke4–13-0.0320%5 Apr →
ancient9–13-0.0416%5 Apr →
vertigo8–13-0.119%5 Apr →
mirage13–7-0.0533%5 Apr →
mirage0–13-0.100%5 Apr →
mirage4–130.0125%5 Apr →
ancient9–13-0.113%3 Apr →
nuke8–13-0.0921%3 Apr →
mirage1–13-0.0720%3 Apr →
anubis13–4-0.117%2 Apr →
mirage13–40.0136%31 Mar →
vertigo15–15-0.0717%16 Mar →
anubis8–13-0.057%11 Mar →
nuke5–13-0.0538%10 Mar →
vertigo17–19-0.1018%10 Mar →
nuke13–16-0.0813%18 Feb →
ancient5–13-0.0135%14 Feb →
anubis13–8-0.0328%13 Feb →
mirage13–9-0.0525%13 Feb →
office7–13-0.0625%13 Feb →
anubis9–13-0.0918%12 Feb →
inferno10–110.0217%7 Feb →
mirage15–150.0519%5 Feb →
office13–3-0.0130%5 Feb →
dust213–6-0.0220%5 Feb →
mirage13–90.0624%4 Feb →
anubis13–3-0.0317%4 Feb →
vertigo11–130.0316%4 Feb →

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 →