GrandMaster Trash

GrandMaster Trash — CS2 Stats

76561198031992186[U:1:71726458]Steam profile ↗✓ No bans

732Tracked matches41%Win rate2020Tracked since
CSDB Rating4.2 DevelopingSupport
FaceitLevel 2 · 753 ELOTop 97.9% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 23 Sep 2026 (yesterday). Ranks are recorded once per day this page is viewed.

No change since then — still 732 tracked matches. Play, then come back: the next observation lands here.

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. 62 days played since 13 Jul 2025. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 14,889 +2,452 13 Jul29 Dec · 31 days played
12,43715,415peak 15,41513 Jul29 Dec
Faceit ELO: 753 +0 18 Sept23 Sept · 2 observations
753753peak 75318 Sept23 Sept
15,764Peak Premier in tracked matches
753Highest Faceit ELO seen on CSDB
62Days played since 2025-07-13

Faceit ELO

  • At peak — 753
  • Next: Level 4 at 901 148 to go
  • Reached: Level 3 · Level 2
  • Level 3 first seen 2026-09-18
  • Level 2 first seen 2026-09-18

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

Share this profile

CSDB.GGGrandMaster TrashFACEITLevel 2 · 753 ELOSTANDINGTop 97.9% of rankedPEAK ELO753csdb.gg/stats

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Performance scores

Aim60
Positioning38
Utility39

0–100 skill scores via Leetify.

Recent form

COLD41563Last 10041%Win rateLWLWWLLLLL

Last 10 vs previous 10: −20pp win rate · +0.01 avg rating · −4.3pp headshot accuracy · +43ms reaction

Win rate down 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 (+0.01), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 32 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 19%
  • Avg reaction 636ms

Last 10

  • 37 · 30% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 20%
  • Avg reaction 679ms

Last 20

  • 812 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 22%
  • 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: SupportUtility contribution stands above the rest of this profile (+1.2 against its own average).

Aim6.0
Utility3.9
Positioning3.8
Opening Duels1.2
Clutch1.8

Effective flashesLimited 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

device

Plays most like device 94% 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. 693ms 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

Aim6.0
Positioning3.8
Utility3.9
Mechanics7.7
Opening Duels1.2
Win Impact2.1

Composite 4.2/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.01
first ⅓ avg -0.00 → last ⅓ avg -0.02
Reaction time674ms−44ms
first ⅓ avg 718ms → last ⅓ avg 674ms
Headshot accuracy24.3%+1.3%
first ⅓ avg 23.0% → last ⅓ avg 24.3%

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

0.13Best match rating · 13–5 · inferno, 22 Oct
52%Best headshot accuracy · 5–13 · inferno, 6 Mar
484msFastest reaction time · 7–13 · nuke, 20 Sept
13–1Biggest win · dust2, 2 Nov

Across the last 100 tracked matches.

Highlights

4Longest win streak
710In matches decided by ≤2 rounds
10Overtime games

Map breakdown

trainBest map · 64% over 11mirageWeakest map · 33% over 9
MapGradePlayedRecordWin rateAvg rating
infernoC2181338%0.00
dust2B20101050%0.00
nukeC156940%0.01
overpassB115645%0.01
trainA117464%0.01
mirageD93633%-0.05
cache41325%0.02
ancient41325%-0.03
anubis2020%-0.03
rooftop1010%0.08
vertigo1010%-0.06
agency1010%-0.04

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

69Matches
49%Win rate
0.93Avg K/D
80.0ADR
43%Headshot %

Clutches & streaks

29%1v1 clutch win
38%1v2 clutch win
5Longest win streak

Recent Faceit resultsLLWLW

MapMatchesWin rateAvg K/DAvg kills
Nuke580%2.5319.8
Mirage560%0.9013.8
Ancient333%0.6712.0
Train250%0.8018.5
Dust21100%1.1721.0
Anubis1100%0.759.0

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.

23.6%Headshot accuracy
30.1%Accuracy (enemy spotted)
27.9%Spray accuracy
84.8%Counter-strafing
9.0°Preaim
693msReaction time
28.1%T opening success
39.8%CT opening success
0.73Enemies flashed / flash
3.5%Flash assists
5.85HE damage / grenade
3.05Flashes / 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

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 3.0491 — below the 4 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 28.0894% — below the 40% mark we flag

Spend your practice time on Mirage

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 9 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategyMirage grenade lineups

Recent matches

MapScoreRatingHS%Date
anubis7–13-0.0233%20 Sept
dust213–60.0315%20 Sept
nuke7–13-0.0122%20 Sept
dust213–80.068%9 Aug
mirage13–11-0.0418%9 Aug
cache7–13-0.0130%7 Aug
mirage11–13-0.0712%1 Aug
inferno14–16-0.0221%31 Jul
cache11–130.0123%31 Jul
dust25–13-0.0317%19 Jul
inferno13–7-0.0029%19 Jul
inferno0–13-0.030%19 Jul
nuke13–90.0019%12 Jul
dust29–13-0.0242%12 Jul
nuke9–13-0.0219%12 Jul
mirage13–10-0.0527%12 Jul
dust213–6-0.0321%11 Jul
mirage10–13-0.0926%17 Jun
cache13–40.0730%30 May
cache4–130.0130%4 May
overpass7–13-0.0422%3 May
nuke13–8-0.0018%3 May
dust213–11-0.0350%19 Apr
overpass13–70.0818%19 Apr
dust23–13-0.0624%15 Apr
anubis12–12-0.0341%6 Apr
inferno6–13-0.0433%4 Apr
dust216–13-0.0014%4 Apr
ancient4–13-0.0024%4 Apr
ancient11–13-0.0318%8 Mar
inferno5–13-0.0252%6 Mar
mirage13–7-0.0618%7 Feb
inferno10–13-0.0627%7 Feb
ancient13–8-0.0222%26 Jan
train13–110.0124%26 Jan
dust26–13-0.0021%7 Jan
dust213–9-0.0337%7 Jan
inferno13–8-0.0244%7 Jan
train9–13-0.0328%29 Dec
train5–13-0.0123%13 Dec
train16–19-0.0530%5 Dec
nuke13–60.0532%28 Nov
dust26–130.0229%25 Nov
nuke9–130.0333%21 Nov
inferno3–9-0.0729%13 Nov
nuke13–70.0416%11 Nov
overpass13–11-0.0015%11 Nov
inferno11–130.0118%8 Nov
overpass14–160.0614%3 Nov
nuke2–130.0026%2 Nov
dust213–10.0420%2 Nov
dust213–80.0115%30 Oct
inferno13–50.1218%30 Oct
inferno8–130.0516%29 Oct
dust210–130.0422%29 Oct
inferno8–13-0.0244%28 Oct
overpass13–6-0.0123%27 Oct
inferno11–130.0324%26 Oct
nuke16–130.0623%26 Oct
overpass9–13-0.0316%24 Oct
train13–80.0120%24 Oct
inferno13–50.1321%22 Oct
overpass13–80.0222%21 Oct
train13–110.0821%21 Oct
dust211–130.0415%19 Oct
train13–90.0428%18 Oct
dust26–130.0113%16 Oct
inferno13–40.0816%14 Oct
mirage9–13-0.0318%11 Oct
train16–120.0319%11 Oct
inferno13–50.0717%10 Oct
mirage10–130.0024%10 Oct
inferno5–9-0.149%6 Oct
rooftop5–90.0831%6 Oct
nuke7–13-0.0120%5 Oct
overpass8–13-0.0325%4 Oct
nuke14–160.0322%4 Oct
nuke8–13-0.0114%4 Oct
inferno10–130.0223%4 Oct
dust28–2-0.0410%4 Oct
overpass8–13-0.009%3 Oct
vertigo12–12-0.0629%3 Oct
train13–5-0.0436%3 Oct
dust215–150.0140%2 Oct
mirage0–13-0.0621%2 Oct
dust213–80.0234%1 Oct
nuke7–13-0.0629%1 Oct
inferno3–13-0.0613%1 Oct
nuke16–140.0421%29 Sept
mirage11–13-0.0521%20 Sept
train13–40.0435%19 Sept
nuke6–13-0.0027%19 Sept
inferno13–11-0.0013%18 Sept
train7–130.0233%17 Sept
ancient3–13-0.0517%17 Sept
overpass13–90.0825%14 Sept
agency10–13-0.0432%7 Aug
inferno16–120.0216%28 Jul
overpass9–13-0.0123%16 Jul
dust25–130.0135%13 Jul

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 →