Ash

Ash — CS2 Stats

GB76561199234674137[U:1:1274408409]Steam profile ↗✓ No bans

1,474Tracked matches43%Win rate2022Tracked since
CSDB Rating3.6 LearningSupport
FaceitLevel 6 · 1,379 ELOTop 54.0% of ranked FACEIT players
Ladder ranks via Leetify
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CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 48 days played since 8 Jul 2025. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 8,279 -6,583 8 Jul12 Jan · 18 days played
8,27914,862peak 14,8628 Jul12 Jan
14,862Peak Premier in tracked matches
1,379Highest Faceit ELO seen on CSDB
48Days played since 2025-07-08

Faceit ELO

  • At peak — 1,379
  • Next: Level 8 at 1,531 152 to go
  • Reached: Level 7 · Level 6 · Level 5 · Level 4

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.GGAshFACEITLevel 6 · 1,379 ELOSTANDINGTop 54.0% of rankedPEAK ELO1,379csdb.gg/stats

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Performance scores

Aim36
Positioning50
Utility51

0–100 skill scores via Leetify.

Recent form

STEADY40555Last 10040%Win rateLLWLWLLWWL

Last 10 vs previous 10: −10pp win rate · +0.01 avg rating · −2.2pp headshot accuracy · −116ms reaction

Win rate −10pp 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

  • 23 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 12%
  • Avg reaction 527ms

Last 10

  • 46 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 14%
  • Avg reaction 549ms

Last 20

  • 911 · 45% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 15%
  • Avg reaction 606ms

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 (+1.3 against its own average).

Aim3.6
Utility5.1
Positioning5.0
Opening Duels3.3
Clutch1.8

Effective flashes

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 67% playstyle similarity

Most alike: utility contribution, positioning profile.

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

T-side openings. Opening success drops from 50% on CT to 31% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 621ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 67% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim3.6
Positioning5.0
Utility5.1
Mechanics3.8
Opening Duels2.7
Win Impact2.8

Composite 3.6/10 (Learning), 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 rating0.00−0.00
first ⅓ avg 0.01 → last ⅓ avg 0.00
Reaction time617ms−30ms
first ⅓ avg 648ms → last ⅓ avg 617ms
Headshot accuracy15.2%−0.5%
first ⅓ avg 15.7% → last ⅓ avg 15.2%

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

0.12Best match rating · 13–5 · mirage, 20 Jul
35%Best headshot accuracy · 4–13 · dust2, 1 Aug
438msFastest reaction time · 11–13 · inferno, 29 Jul
13–2Biggest win · ancient, 29 Jul

Across the last 100 tracked matches.

Highlights

9Longest win streak
L2Current streak
910In matches decided by ≤2 rounds
17Overtime games

Map breakdown

mirageBest map · 63% over 8infernoWeakest map · 8% over 12
MapGradePlayedRecordWin rateAvg rating
dust2B25121348%-0.00
ancientB23111248%-0.01
nukeC1661038%0.01
infernoD121118%0.00
overpassD82625%-0.00
mirageA85363%0.02
anubis41325%-0.01
cache21150%0.01
train21150%0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (8% over 12). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

655Matches
49%Win rate
1.04Avg K/D
81.3ADR
38%Headshot %

Clutches & streaks

29%1v1 clutch win
23%1v2 clutch win
7Longest win streak

Recent Faceit resultsLWLWL

MapMatchesWin rateAvg K/DAvg kills
Inferno12442%1.0016.1
Ancient11555%1.1318.1
Anubis10853%0.9615.2
Dust28551%1.1616.2
Mirage6645%1.0114.8
Nuke5758%1.0615.8
Cache2752%0.9015.0
Overpass2133%0.9415.1

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.

15.2%Headshot accuracy
31.7%Accuracy (enemy spotted)
30.0%Spray accuracy
67.2%Counter-strafing
11.9°Preaim
621msReaction time
31.1%T opening success
50.5%CT opening success
0.70Enemies flashed / flash
4.7%Flash assists
13.20HE damage / grenade
5.63Flashes / 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 31.1023% — 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.

8% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
ancient11–13-0.025%25 Aug
dust210–130.0010%23 Aug
ancient13–8-0.0013%14 Aug
nuke6–130.0114%14 Aug
nuke13–110.0518%11 Aug
inferno11–13-0.0013%29 Jul
cache6–13-0.0115%24 Jul
cache16–140.0223%17 Jul
dust213–60.029%22 Jun
inferno11–130.0218%20 Jun
overpass13–60.0213%8 Jun
anubis6–13-0.0511%2 Jun
dust216–140.0216%29 May
overpass13–16-0.0214%28 Apr
overpass10–130.0123%26 Apr
anubis13–110.0517%22 Apr
ancient13–9-0.0716%7 Apr
inferno11–130.0416%19 Mar
ancient13–9-0.0318%12 Mar
anubis9–13-0.0018%8 Mar
dust223–250.0218%27 Feb
overpass5–130.0416%27 Feb
ancient13–9-0.0120%18 Feb
dust20–13-0.0720%28 Jan
nuke9–13-0.0512%19 Jan
mirage13–90.0712%12 Jan
ancient3–13-0.0216%12 Jan
nuke5–13-0.0712%12 Jan
nuke13–30.0811%10 Jan
dust213–9-0.0510%5 Jan
dust215–15-0.0220%5 Jan
dust213–100.0015%2 Aug
ancient13–50.0719%2 Aug
ancient7–13-0.0332%2 Aug
dust24–13-0.0635%1 Aug
nuke9–13-0.0424%31 Jul
ancient7–13-0.0413%31 Jul
train13–110.0530%30 Jul
overpass7–13-0.0624%30 Jul
mirage13–70.0510%30 Jul
nuke15–15-0.0426%30 Jul
dust213–60.0617%30 Jul
dust24–13-0.0225%29 Jul
ancient13–20.0514%29 Jul
overpass7–13-0.0025%29 Jul
dust213–110.0224%29 Jul
ancient6–13-0.0421%29 Jul
nuke10–130.0720%29 Jul
dust213–8-0.0022%29 Jul
mirage8–13-0.066%28 Jul
ancient6–13-0.0313%28 Jul
inferno2–13-0.0518%28 Jul
ancient0–13-0.0613%28 Jul
overpass8–13-0.0516%27 Jul
nuke16–14-0.0221%27 Jul
dust213–50.1021%27 Jul
ancient13–3-0.0212%27 Jul
dust27–130.0224%27 Jul
train7–130.0222%26 Jul
ancient13–90.0223%26 Jul
dust213–9-0.0523%26 Jul
inferno11–13-0.0018%24 Jul
nuke13–7-0.0028%24 Jul
dust215–15-0.0210%23 Jul
dust28–130.0621%23 Jul
dust25–13-0.019%23 Jul
dust28–13-0.0424%23 Jul
inferno1–13-0.0015%23 Jul
inferno2–13-0.0619%22 Jul
nuke14–16-0.0018%22 Jul
dust213–80.0322%21 Jul
mirage16–14-0.0211%21 Jul
ancient13–100.0520%20 Jul
mirage13–40.0218%20 Jul
ancient13–9-0.0819%20 Jul
nuke13–70.1027%20 Jul
mirage13–50.129%20 Jul
overpass16–130.0410%20 Jul
dust213–60.0721%20 Jul
inferno14–160.0410%19 Jul
nuke14–16-0.039%19 Jul
inferno9–13-0.0023%16 Jul
ancient10–13-0.019%16 Jul
dust213–90.0219%15 Jul
inferno8–130.0317%14 Jul
inferno13–9-0.0016%14 Jul
ancient15–15-0.0214%14 Jul
nuke15–150.0419%13 Jul
ancient10–13-0.0220%13 Jul
ancient13–100.0817%13 Jul
nuke16–14-0.0011%12 Jul
ancient11–13-0.028%12 Jul
dust26–13-0.0927%12 Jul
dust23–13-0.079%11 Jul
mirage9–13-0.0320%11 Jul
ancient6–13-0.0417%11 Jul
anubis7–13-0.0414%9 Jul
nuke10–130.027%9 Jul
mirage10–130.018%9 Jul
inferno13–160.0414%8 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 →