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76561198146479130[U:1:186213402]Steam profile ↗✓ No bans

1,317Tracked matches43%Win rate2020Tracked since
2,736Hours in CS3Hrs last 2 wks
CSDB Rating5.3 DevelopingPositional Player
Premier CS Rating19,598Top 50% of 215,558 CSDB-tracked playersPurple band · top ~10.1% of ranked players (population est.)
CSDB Leaderboard#92635 of 261673 tracked
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 11 Nov 2026 (4 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 1,317 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 19,598 +738 2 Jul – 11 Nov · 4 days played
18,86019,598peak 19,5982 Jul11 Nov
19,598Peak Premier in tracked matches
35Days played since 2026-07-02

Premier CS Rating

  • At peak — 19,598
  • Next: Pink band at 20,000 — 402 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-11-11
  • Blue band first seen 2026-11-11

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 Purple band among CSDB-tracked players (n=42,517), 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 playerPurple band medianPink band medianvs Pink band
Headshot rate45.4%44.4%46.9%1.5% short
Shot accuracy9.6%11.8%13.0%3.4% short
Kill/death ratio1.011.031.080.07 short
Match win rate43.9%45.3%46.7%2.8% short

This profile sits below the typical Pink band player on every metric we can compare.

Widest gap: Shot accuracy. That is the metric furthest from the Pink band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGArchPREMIER19,598 · Purple bandcsdb.gg/stats

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Performance scores

Aim68
Positioning53
Utility43

0–100 skill scores via Leetify.

Recent form

STEADY51–46–3Last 10051%Win rateLWWLLWWLLL

Last 10 vs previous 10: 0pp win rate · −0.01 avg rating · +8.7pp headshot accuracy · +23ms 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 -0.04
  • Avg headshot accuracy 28%
  • Avg reaction 578ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 25%
  • Avg reaction 623ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 21%
  • Avg reaction 611ms

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 (+1.4 against its own average).

Aim6.8
Utility4.3
Positioning5.3
Opening Duels3.6
Clutch2.6

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

m0NESY

Plays most like m0NESY 90% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower aim profile; 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

Reaction time. 624ms 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

Aim6.8
Positioning5.3
Utility4.3
Mechanics6.4
Opening Duels2.7
Win Impact2.8

Composite 5.3/10 (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-0.02−0.02
first ⅓ avg 0.00 → last ⅓ avg -0.02
Reaction time613ms−22ms
first ⅓ avg 636ms → last ⅓ avg 613ms
Headshot accuracy19.5%+1.6%
first ⅓ avg 17.9% → last ⅓ avg 19.5%

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

0.10Best match rating · 13–5 · inferno, 18 Jul →
67%Best headshot accuracy · 10–13 · mirage, 15 Oct →
359msFastest reaction time · 6–9 · inferno, 17 Jul →
13–0Biggest win · inferno, 7 Jul →

Across the last 100 tracked matches.

Highlights

6Longest win streak
3–14In matches decided by ≤2 rounds
1Overtime games

Map breakdown

anubisBest map · 90% over 10infernoWeakest map · 38% over 16
MapGradePlayedRecordWin rateAvg rating
ancientB199–1047%-0.01
dust2A169–756%0.01
infernoC166–1038%-0.02
nukeB136–746%-0.02
mirageA127–558%-0.00
anubisS109–190%-0.01
trainA53–260%-0.00
cache—41–325%-0.02
overpass—21–150%-0.01
shelter—20–20%-0.05
fachwerk—10–10%0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 16). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

74,840Lifetime kills
1.01K/D
4,064Matches
43.9%Match win rate
45.4%Headshot % · Top 50% of Purple band
9.6%Shot accuracy
6,502MVPs
1,500Hours (in match)
3,896Bombs planted
979Bombs defused

Most-used weapons

Lifetime map wins

11,079dust2
2,763inferno
2,454nuke
1,396vertigo
453train
305aztec
252office
153bank

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

Faceit stats

Combat

86Matches
49%Win rate
1.09Avg K/D
73.9ADR
45%Headshot %

Clutches & streaks

33%1v1 clutch win
26%1v2 clutch win
9Longest win streak

Recent Faceit resultsLWWLL

MapMatchesWin rateAvg K/DAvg kills
Mirage1540%1.5513.1
Nuke1354%0.7913.1
Inferno1283%0.8713.7
Anubis1145%1.0115.6
Dust21040%1.1215.8
Overpass757%1.2217.9
Ancient540%1.4214.4
Cache20%0.6810.5

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.

19.9%Headshot accuracy
34.3%Accuracy (enemy spotted)
44.1%Spray accuracy
78.9%Counter-strafing
11.4°Preaim
624msReaction time
38.2%T opening success
43.7%CT opening success
0.51Enemies flashed / flash
9.1%Flash assists
12.29HE damage / grenade
4.17Flashes / 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. 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 38.1724% — below the 40% mark we flag

Spend your practice time on Inferno

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

38% win rate across 16 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke9–13-0.0722%10 Nov →
ancient13–2-0.0221%10 Nov →
dust213–5-0.0118%5 Nov →
mirage10–13-0.0667%15 Oct →
mirage11–13-0.0214%26 Sept →
dust213–6-0.0218%26 Sept →
dust213–100.0229%26 Sept →
inferno9–13-0.0134%21 Aug →
inferno7–13-0.0512%21 Aug →
dust29–13-0.0414%21 Aug →
cache11–130.0313%17 Aug →
inferno3–13-0.0625%14 Aug →
dust213–5-0.0217%14 Aug →
dust213–70.0417%14 Aug →
ancient9–13-0.0323%10 Aug →
dust211–130.014%10 Aug →
nuke13–6-0.067%6 Aug →
ancient13–40.0531%6 Aug →
anubis8–13-0.066%6 Aug →
mirage9–13-0.0520%6 Aug →
nuke13–10-0.0414%5 Aug →
anubis13–100.089%5 Aug →
mirage8–13-0.049%5 Aug →
nuke11–130.0115%4 Aug →
inferno10–13-0.0540%4 Aug →
dust213–100.0317%3 Aug →
nuke13–60.0217%3 Aug →
ancient13–90.0025%3 Aug →
overpass10–13-0.0113%1 Aug →
mirage10–13-0.0526%1 Aug →
inferno13–10-0.0113%1 Aug →
cache10–13-0.0420%31 Jul →
anubis13–8-0.0315%31 Jul →
mirage13–110.0117%30 Jul →
ancient11–13-0.0311%30 Jul →
nuke13–100.0438%29 Jul →
dust211–130.0127%28 Jul →
mirage13–7-0.0225%28 Jul →
ancient7–13-0.0322%28 Jul →
anubis13–30.0321%28 Jul →
inferno4–13-0.116%28 Jul →
anubis13–8-0.0311%27 Jul →
inferno13–60.0928%27 Jul →
train12–120.0421%23 Jul →
anubis13–4-0.0715%23 Jul →
nuke13–40.0836%23 Jul →
nuke11–13-0.0618%22 Jul →
train5–13-0.0535%22 Jul →
ancient8–13-0.0311%21 Jul →
ancient11–13-0.0115%21 Jul →
dust27–13-0.0318%21 Jul →
inferno12–5-0.0627%20 Jul →
dust210–130.0324%20 Jul →
ancient13–2-0.0110%20 Jul →
train13–4-0.069%19 Jul →
cache8–13-0.0718%19 Jul →
dust213–30.0513%19 Jul →
mirage13–90.0319%19 Jul →
ancient9–130.0419%19 Jul →
inferno13–7-0.0123%18 Jul →
dust213–90.0622%18 Jul →
inferno13–50.1029%18 Jul →
nuke10–13-0.0616%17 Jul →
train13–50.0310%17 Jul →
ancient2–13-0.0115%17 Jul →
anubis13–8-0.0418%17 Jul →
inferno6–9-0.1113%17 Jul →
inferno7–9-0.0213%17 Jul →
overpass13–4-0.0113%15 Jul →
mirage13–40.0616%15 Jul →
inferno12–120.0323%15 Jul →
ancient8–13-0.039%15 Jul →
nuke13–50.0522%14 Jul →
inferno7–13-0.0424%14 Jul →
nuke5–13-0.078%14 Jul →
anubis13–60.0513%14 Jul →
dust211–13-0.0118%14 Jul →
ancient11–13-0.0513%13 Jul →
train13–50.0516%13 Jul →
inferno8–13-0.0315%13 Jul →
shelter11–13-0.0628%10 Jul →
nuke14–16-0.0221%10 Jul →
ancient13–10.1028%10 Jul →
cache13–90.0211%10 Jul →
shelter11–13-0.0524%9 Jul →
fachwerk12–120.0125%9 Jul →
anubis13–10-0.0417%8 Jul →
ancient6–13-0.0419%8 Jul →
ancient13–80.1021%8 Jul →
inferno13–00.018%7 Jul →
ancient13–9-0.0525%7 Jul →
nuke4–13-0.0517%7 Jul →
mirage13–110.0411%5 Jul →
dust29–130.0315%5 Jul →
dust213–40.0327%5 Jul →
mirage8–30.0525%5 Jul →
mirage13–90.0316%5 Jul →
ancient13–11-0.0516%3 Jul →
ancient13–10-0.0013%3 Jul →
anubis13–70.0523%2 Jul →

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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