mustard tiger

mustard tiger — CS2 Stats

76561198165388660[U:1:205122932]Steam profile ↗✓ No bans

1,375Tracked matches50%Win rate2020Tracked since
CSDB Rating5.6 SolidPositional Player
Premier CS Rating17,565Purple band · top ~18.2% of ranked players (population est.)
FaceitLevel 9Top 20.7% of ranked FACEIT players
WingmanGold Nova II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 4 Oct 2026 (32 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 1,375 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 17,565 +1,829 9 Apr – 4 Oct · 15 days played
15,73620,000peak 20,0009 Apr4 Oct
20,102Peak Premier in tracked matches
37Days played since 2025-03-28

Premier CS Rating

  • 2,435 below peak (20,000)
  • 0 over 30 days · steady
  • Next: Pink band at 20,000 — 2,435 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-09-02
  • Blue band first seen 2026-09-02

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

Share this profile

CSDB.GGmustard tigerFACEITLevel 9STANDINGTop 20.7% of rankedPREMIER17,565 · Purple bandcsdb.gg/stats

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Performance scores

Aim70
Positioning49
Utility37

0–100 skill scores via Leetify.

Recent form

STEADY51–44–5Last 10051%Win rateLWLLLWWLWL

Last 10 vs previous 10: 0pp win rate · −0.02 avg rating · −3.2pp headshot accuracy · +11ms 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

  • 1–4 · 20% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 15%
  • Avg reaction 644ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 17%
  • Avg reaction 637ms

Last 20

  • 8–10–2 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 19%
  • Avg reaction 631ms

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 (+1.9 against its own average).

Aim7.0
Utility3.7
Positioning4.9
Opening Duels3.3
Clutch0.0

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

m0NESY

Plays most like m0NESY 95% playstyle similarity

Most alike: aim profile, positioning profile.

Where you differ: lower utility contribution; lower opening-duel success.

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 50% on CT to 30% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 641ms 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

Aim7.0
Positioning4.9
Utility3.7
Mechanics7.9
Opening Duels2.5
Win Impact5.0

Composite 5.6/10 (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 time656ms+25ms
first ⅓ avg 631ms → last ⅓ avg 656ms
Headshot accuracy16.4%−2.0%
first ⅓ avg 18.4% → last ⅓ avg 16.4%

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

0.15Best match rating · 13–3 · dust2, 22 May →
63%Best headshot accuracy · 2–13 · overpass, 10 Oct →
453msFastest reaction time · 11–13 · inferno, 9 Apr →
13–1Biggest win · overpass, 18 Apr →

Across the last 100 tracked matches.

Highlights

7Longest win streak
8–8In matches decided by ≤2 rounds
7Overtime games

Map breakdown

anubisBest map · 86% over 7mirageWeakest map · 33% over 21
MapGradePlayedRecordWin rateAvg rating
mirageD217–1433%-0.01
dust2B179–853%0.00
ancientA169–756%-0.03
nukeB147–750%-0.02
infernoA95–456%-0.01
anubisS76–186%-0.00
trainS75–271%-0.03
overpassD62–433%-0.03
cache—21–150%0.04
vertigo—10–10%-0.05

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (33% over 21). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,107Matches
52%Win rate
0.95Avg K/D
68.2ADR
39%Headshot %

Clutches & streaks

19%1v1 clutch win
7%1v2 clutch win
12Longest win streak

Recent Faceit resultsWLLWL

MapMatchesWin rateAvg K/DAvg kills
Mirage4743%0.9414.6
Ancient4052%0.8912.9
Nuke2259%0.8512.8
Anubis1164%0.8011.7
Dust2757%0.8512.3
Overpass560%0.8612.0
Train475%1.2213.8
Inferno30%0.8917.7

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.

17.7%Headshot accuracy
34.0%Accuracy (enemy spotted)
37.9%Spray accuracy
85.6%Counter-strafing
9.3°Preaim
641msReaction time
30.0%T opening success
50.2%CT opening success
0.49Enemies flashed / flash
1.3%Flash assists
6.58HE damage / grenade
5.97Flashes / 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 0.4896 — 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 30.0108% — 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 21 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient13–16-0.0713%19 Jun →
dust213–4-0.0625%19 Jun →
mirage12–160.0419%12 Jun →
nuke9–13-0.038%12 Jun →
overpass7–130.018%12 Jun →
nuke13–11-0.0226%23 May →
dust213–70.0128%23 May →
mirage11–130.0719%23 May →
inferno13–100.0623%23 May →
nuke9–13-0.014%22 May →
dust213–30.1523%22 May →
nuke8–13-0.058%22 May →
mirage11–13-0.0312%22 May →
nuke13–5-0.0313%22 May →
dust213–50.1220%22 May →
cache13–40.1024%22 May →
cache12–12-0.0126%30 Apr →
ancient6–130.0626%30 Apr →
dust215–15-0.0330%2 Apr →
anubis7–13-0.0622%2 Apr →
mirage3–13-0.0916%2 Apr →
dust27–13-0.098%22 Mar →
ancient16–14-0.0711%21 Mar →
mirage13–5-0.0424%21 Mar →
overpass13–60.0414%21 Mar →
dust213–20.016%21 Mar →
mirage11–13-0.0518%5 Mar →
ancient13–2-0.009%4 Mar →
ancient3–0-0.020%4 Mar →
overpass4–13-0.0631%28 Feb →
dust210–13-0.048%27 Feb →
train7–13-0.054%27 Feb →
mirage5–130.0215%14 Feb →
dust24–13-0.0322%1 Jan →
inferno5–13-0.0223%1 Jan →
inferno13–90.0428%31 Dec →
train13–60.0110%31 Dec →
overpass10–13-0.0420%31 Dec →
mirage13–50.0138%31 Dec →
ancient13–5-0.047%31 Dec →
mirage1–90.0125%31 Dec →
dust213–110.0327%31 Dec →
mirage6–13-0.0425%31 Dec →
vertigo8–8-0.0514%31 Dec →
dust213–40.0129%24 Oct →
overpass2–13-0.1163%10 Oct →
ancient4–13-0.0613%10 Oct →
nuke9–130.0322%7 Oct →
mirage13–7-0.0325%29 Sept →
ancient7–13-0.1035%14 Jul →
mirage10–13-0.0610%13 Jul →
nuke10–13-0.0815%13 Jul →
train13–9-0.0813%13 Jul →
dust210–120.0233%12 Jul →
ancient13–30.0023%27 Jun →
inferno13–7-0.0220%27 Jun →
mirage4–13-0.0315%14 Jun →
ancient9–13-0.0327%14 Jun →
mirage4–13-0.0318%7 Jun →
anubis8–1-0.0833%7 Jun →
dust213–6-0.0817%7 Jun →
mirage11–13-0.0119%7 Jun →
train2–3-0.060%7 Jun →
mirage13–50.0517%6 Jun →
nuke13–20.0715%6 Jun →
mirage3–13-0.0821%6 Jun →
mirage13–3-0.029%24 May →
ancient13–90.0319%24 May →
dust29–13-0.0214%24 May →
mirage14–16-0.0317%23 May →
anubis13–50.0132%23 May →
dust213–6-0.0236%23 May →
train16–140.0010%3 May →
mirage13–90.0310%3 May →
anubis8–00.0120%3 May →
ancient2–0-0.080%1 May →
nuke13–4-0.0413%1 May →
nuke10–13-0.057%1 May →
dust212–120.0226%1 May →
nuke10–13-0.0524%19 Apr →
anubis13–3-0.0211%19 Apr →
train14–16-0.0832%18 Apr →
ancient13–10-0.0525%18 Apr →
inferno13–5-0.029%18 Apr →
inferno13–11-0.0223%18 Apr →
inferno6–13-0.1013%18 Apr →
overpass13–10.0110%18 Apr →
inferno8–13-0.0110%11 Apr →
ancient3–13-0.0210%11 Apr →
anubis13–30.1318%11 Apr →
nuke13–60.0022%11 Apr →
train13–30.0744%11 Apr →
anubis13–4-0.0126%10 Apr →
ancient9–13-0.0015%10 Apr →
inferno11–130.0222%9 Apr →
mirage13–110.0122%9 Apr →
nuke13–9-0.0318%30 Mar →
nuke13–9-0.0312%28 Mar →
ancient13–70.0014%28 Mar →
dust212–120.0121%28 Mar →

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 →

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