green gangsta

green gangsta — CS2 Stats

GB76561198051937479[U:1:91671751]Steam profile ↗✓ No bans

643Tracked matches64%Win rate2020Tracked since
2,137Hours in CS
CSDB Rating6.3 SolidPositional Player
Premier CS Rating21,270Top 50% of 212,133 CSDB-tracked playersPink band · top ~7.1% of ranked players (population est.)
CSDB Leaderboard#66227 of 259000 tracked
FaceitLevel 8Top 31.2% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 2 Sep 2026 (59 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 643 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 21,270 +1,747 23 Aug – 2 Sept · 7 days played
19,52321,270peak 21,27023 Aug2 Sept
21,270Peak Premier in tracked matches
30Days played since 2025-03-06

Premier CS Rating

  • At peak — 21,270
  • Next: Red band at 25,000 — 3,730 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band
  • Pink band first seen 2026-09-01
  • Purple band first seen 2026-09-01

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 8 among CSDB-tracked players (n=15,525), 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 8 medianLevel 9 medianvs Level 9
Headshot rate54.9%46.8%48.2%above
Shot accuracy21.1%13.0%13.2%above
Kill/death ratio1.251.061.07above
Match win rate48.1%46.3%46.9%above

Across every metric we can compare, this profile already matches the typical Level 9 player. Rank still comes from winning matches — this is a performance comparison, not a prediction.

Share this profile

CSDB.GGgreen gangstaFACEITLevel 8STANDINGTop 31.2% of rankedPREMIER21,270 · 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

Aim67
Positioning64
Utility17

0–100 skill scores via Leetify.

Recent form

STEADY66–31–3Last 10066%Win rateLLWWLWLWWW

Last 10 vs previous 10: 0pp win rate · +0.00 avg rating · +4.3pp headshot accuracy · +113ms 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

  • 2–3 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 22%
  • Avg reaction 703ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 23%
  • Avg reaction 656ms

Last 20

  • 12–6–2 · 60% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 21%
  • Avg reaction 599ms

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).

Aim6.7
Utility1.7
Positioning6.4
Opening Duels6.0

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

s1mple

Plays most like s1mple 83% playstyle similarity

Most alike: positioning profile, aim profile.

Where you differ: lower opening-duel success; 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. 591ms 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

Aim6.7
Positioning6.4
Utility1.7
Mechanics7.6
Opening Duels5.4
Win Impact9.8

Composite 6.3/10 (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 0.03 → last ⅓ avg 0.01
Reaction time595ms+39ms
first ⅓ avg 557ms → last ⅓ avg 595ms
Headshot accuracy20.8%+1.0%
first ⅓ avg 19.8% → last ⅓ avg 20.8%

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

0.14Best match rating · 13–5 · dust2, 25 Mar →
45%Best headshot accuracy · 13–5 · inferno, 6 Mar →
391msFastest reaction time · 13–10 · ancient, 23 Mar →
13–1Biggest win · ancient, 31 Aug →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L2Current streak
15–4In matches decided by ≤2 rounds
3Overtime games

Map breakdown

infernoBest map · 86% over 7ancientWeakest map · 50% over 14
MapGradePlayedRecordWin rateAvg rating
nukeS1612–475%0.02
ancientB147–750%-0.01
trainS108–280%0.02
overpassS108–280%0.02
dust2A106–460%0.03
infernoS76–186%0.04
vertigoA74–357%0.02
mirageS65–183%0.00
anubisS64–267%-0.02
basaltA53–260%0.03
cache—32–167%0.05
edin—31–233%0.02
alpine—10–10%-0.01
jura—10–10%0.00
italy—10–10%0.05

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (50% over 14). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

120,098Lifetime kills
1.25K/D · Top 25% of Level 8 players
3,532Matches
48.1%Match win rate · Top 50% of Level 8 players
54.9%Headshot % · Top 25% of Level 8 players
21.1%Shot accuracy · Top 5% of Level 8 players
10,168MVPs
2,137Hours (in match)
4,739Bombs planted
1,462Bombs defused

Most-used weapons

AK-4754,523
AWP6,903
P2502,031
SG 5531,600
Knife1,494

Lifetime map wins

5,390inferno
4,779dust2
4,054nuke
2,255cbble
1,892train
350vertigo
41lake
37militia

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

Faceit stats

Combat

474Matches
56%Win rate
1.32Avg K/D
—ADR
41%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
8Longest win streak

Recent Faceit resultsWLLWW

MapMatchesWin rateAvg K/DAvg kills
Overpass540%0.9216.4
Ancient3100%1.3025.0
Inferno367%1.0520.7
Anubis2100%0.9216.0
Mirage1100%1.3320.0
Nuke1100%0.7213.0

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.

20.3%Headshot accuracy
32.4%Accuracy (enemy spotted)
36.5%Spray accuracy
84.1%Counter-strafing
11.4°Preaim
591msReaction time
51.0%T opening success
52.4%CT opening success
0.47Enemies flashed / flash
5.0%Flash assists
4.91HE damage / grenade
4.82Flashes / 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 0.4657 — below the 0.5 mark we flag

    Grenade Lineups →

Recent matches

MapScoreRatingHS%Date
alpine4–13-0.0121%29 Apr →
cache4–13-0.0314%29 Apr →
cache13–50.0621%29 Apr →
cache13–80.1123%29 Apr →
jura4–130.0030%14 Sept →
nuke13–110.0215%9 Sept →
ancient2–13-0.0324%9 Sept →
train13–80.0627%31 Aug →
ancient13–1-0.0919%31 Aug →
overpass13–10.1337%31 Aug →
ancient16–130.0012%27 Aug →
ancient11–130.0423%25 Aug →
overpass13–100.014%25 Aug →
inferno13–110.0418%23 Aug →
nuke6–13-0.0229%23 Aug →
italy12–120.058%23 Aug →
mirage13–8-0.0126%23 Aug →
mirage15–150.0427%23 Aug →
overpass13–80.0522%23 Aug →
ancient12–3-0.0120%23 Aug →
ancient10–13-0.0219%21 Aug →
inferno13–6-0.0019%21 Aug →
train13–70.0310%21 Aug →
ancient13–40.0228%21 Aug →
inferno12–16-0.0020%13 Aug →
nuke13–70.0524%13 Aug →
nuke13–90.0625%13 Aug →
overpass13–30.0516%3 Aug →
dust27–13-0.0613%3 Aug →
nuke5–13-0.0424%17 Jul →
train13–11-0.0415%21 Apr →
overpass13–11-0.0333%21 Apr →
vertigo13–6-0.0218%20 Apr →
inferno13–50.0429%20 Apr →
nuke13–110.0124%9 Apr →
ancient4–13-0.0233%9 Apr →
nuke13–10.1014%7 Apr →
dust213–110.0013%7 Apr →
train9–13-0.017%7 Apr →
dust21–13-0.0823%3 Apr →
basalt13–60.075%3 Apr →
vertigo4–130.0514%3 Apr →
overpass6–13-0.070%3 Apr →
anubis5–13-0.0920%3 Apr →
overpass13–11-0.0518%31 Mar →
ancient13–11-0.0313%31 Mar →
vertigo13–20.039%31 Mar →
anubis9–13-0.0413%25 Mar →
nuke11–130.0313%25 Mar →
dust213–50.1411%25 Mar →
mirage13–50.039%25 Mar →
anubis13–11-0.0410%24 Mar →
mirage13–3-0.1015%24 Mar →
basalt10–13-0.010%24 Mar →
edin5–13-0.0113%24 Mar →
inferno13–50.1025%23 Mar →
ancient13–100.1025%23 Mar →
dust213–110.0020%23 Mar →
overpass12–120.0129%23 Mar →
vertigo13–90.0212%23 Mar →
train13–50.0210%23 Mar →
nuke13–90.0538%23 Mar →
basalt9–130.0511%20 Mar →
nuke13–5-0.049%20 Mar →
train13–10.1017%20 Mar →
ancient13–70.017%20 Mar →
edin4–00.120%20 Mar →
nuke13–60.0517%19 Mar →
dust213–10.0422%19 Mar →
edin11–13-0.0424%19 Mar →
basalt13–100.0119%18 Mar →
nuke7–13-0.0418%18 Mar →
train13–6-0.0226%18 Mar →
vertigo8–13-0.0217%18 Mar →
nuke13–60.0824%17 Mar →
anubis13–110.0217%17 Mar →
overpass13–40.0816%17 Mar →
train6–130.0120%16 Mar →
ancient10–130.0428%16 Mar →
nuke13–100.0911%16 Mar →
anubis13–7-0.0311%13 Mar →
dust28–130.0628%13 Mar →
mirage13–110.018%13 Mar →
dust213–10.0825%12 Mar →
nuke13–4-0.0214%12 Mar →
inferno13–110.0416%12 Mar →
ancient6–13-0.0324%12 Mar →
dust211–13-0.0223%10 Mar →
anubis13–90.048%9 Mar →
nuke5–00.020%9 Mar →
vertigo13–80.0719%9 Mar →
mirage13–20.0529%9 Mar →
ancient8–13-0.0413%9 Mar →
train13–90.0614%9 Mar →
basalt13–60.0512%9 Mar →
overpass13–110.0027%6 Mar →
train13–110.0124%6 Mar →
vertigo7–13-0.0133%6 Mar →
dust213–10.1323%6 Mar →
inferno13–50.1045%6 Mar →

Match data via Leetify.

Recent teammates

Milestones

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

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