Big Ash

Big Ash — CS2 Stats

76561199016314440[U:1:1056048712]Steam profile ↗✓ No bans

1,709Tracked matches54%Win rate2024Tracked since
CSDB Rating6.0 SolidSupport
CSDB Leaderboard#77911 of 226133 tracked
FaceitLevel 8Top 31.2% 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. 47 days played since 7 Dec 2025. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 19,882 -3,281 7 Dec28 Mar · 38 days played
17,86823,832peak 23,8327 Dec28 Mar
23,832Peak Premier in tracked matches
47Days played since 2025-12-07

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

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CSDB.GGBig AshFACEITLevel 8STANDINGTop 31.2% of rankedcsdb.gg/stats

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Performance scores

Aim71
Positioning50
Utility59

0–100 skill scores via Leetify.

Recent form

STEADY45514Last 10045%Win rateTTLLLWWWWW

Last 10 vs previous 10: +10pp win rate · −0.01 avg rating · +9.3pp headshot accuracy · −28ms 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

  • 032 · 0% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 33%
  • Avg reaction 572ms

Last 10

  • 532 · 50% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 28%
  • Avg reaction 600ms

Last 20

  • 992 · 45% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 24%
  • Avg reaction 614ms

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 (+1.1 against its own average).

Aim7.1
Utility5.9
Positioning5.0
Opening Duels3.4

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

NiKo

Plays most like NiKo 88% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; 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 48% on CT to 28% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 634ms 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

Aim7.1
Positioning5.0
Utility5.9
Mechanics7.3
Opening Duels2.3
Win Impact6.2

Composite 6.0/10 (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 rating0.01+0.03
first ⅓ avg -0.02 → last ⅓ avg 0.01
Reaction time636ms−6ms
first ⅓ avg 642ms → last ⅓ avg 636ms
Headshot accuracy22.0%+4.9%
first ⅓ avg 17.2% → last ⅓ avg 22.0%

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

0.22Best match rating · 13–4 · ancient, 25 Jan
43%Best headshot accuracy · 4–13 · inferno, 29 Dec
391msFastest reaction time · 6–13 · mirage, 19 Dec
13–1Biggest win · inferno, 24 Jan

Across the last 100 tracked matches.

Highlights

8Longest win streak
67In matches decided by ≤2 rounds
5Overtime games

Map breakdown

dust2Best map · 54% over 13mirageWeakest map · 38% over 13
MapGradePlayedRecordWin rateAvg rating
infernoB24121250%-0.01
ancientB1991047%0.00
dust2B137654%-0.01
mirageC135838%-0.03
anubisC104640%-0.02
trainC73443%-0.02
nukeB63350%-0.03
overpass31233%-0.04
vertigo31233%0.01
cache2020%0.02

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (38% over 13). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

22.4%Headshot accuracy
32.4%Accuracy (enemy spotted)
32.8%Spray accuracy
83.0%Counter-strafing
8.5°Preaim
634msReaction time
28.3%T opening success
48.1%CT opening success
0.64Enemies flashed / flash
5.2%Flash assists
9.71HE damage / grenade
7.16Flashes / 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 28.3495% — 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.

38% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategyMirage grenade lineups

Recent matches

MapScoreRatingHS%Date
cache15–15-0.0229%28 Aug
inferno15–150.0337%23 Jul
ancient1–13-0.0334%23 Jul
cache11–130.0643%1 May
ancient11–13-0.0123%28 Mar
inferno13–9-0.0024%19 Mar
ancient13–90.0224%19 Mar
inferno13–7-0.0426%15 Mar
anubis13–5-0.0725%12 Mar
anubis13–50.0718%26 Feb
anubis8–130.0625%21 Feb
dust28–130.0336%21 Feb
ancient13–90.0220%21 Feb
anubis8–13-0.0114%27 Jan
inferno4–13-0.0024%26 Jan
anubis2–13-0.1011%26 Jan
overpass13–8-0.0321%26 Jan
dust213–6-0.0014%25 Jan
ancient13–40.2217%25 Jan
mirage4–13-0.078%25 Jan
inferno13–10.1125%24 Jan
mirage16–140.0423%24 Jan
anubis4–13-0.0738%24 Jan
mirage13–6-0.0524%23 Jan
mirage2–130.0112%23 Jan
anubis6–130.0213%23 Jan
anubis16–12-0.067%23 Jan
nuke13–80.0118%23 Jan
anubis13–40.0120%20 Jan
train11–130.0321%17 Jan
ancient13–100.0515%17 Jan
inferno6–13-0.0123%16 Jan
ancient13–11-0.0017%15 Jan
nuke5–13-0.119%14 Jan
train7–130.0123%14 Jan
inferno2–13-0.0615%11 Jan
ancient13–100.1025%11 Jan
ancient11–130.0221%10 Jan
train13–11-0.0324%10 Jan
inferno8–13-0.0617%7 Jan
mirage3–12-0.0510%6 Jan
dust213–11-0.0215%5 Jan
mirage11–13-0.0221%4 Jan
nuke6–13-0.0318%4 Jan
dust28–13-0.0118%3 Jan
train13–7-0.0213%2 Jan
ancient13–90.0116%2 Jan
inferno13–50.0319%2 Jan
inferno13–70.0123%1 Jan
inferno13–8-0.0220%1 Jan
inferno13–50.0620%1 Jan
nuke13–8-0.0319%1 Jan
dust213–40.0636%30 Dec
inferno4–13-0.0243%29 Dec
inferno3–13-0.0518%28 Dec
dust213–8-0.0613%28 Dec
mirage13–110.0215%28 Dec
dust29–13-0.0624%27 Dec
inferno4–13-0.0710%27 Dec
inferno13–60.0425%27 Dec
dust213–110.0422%27 Dec
inferno2–13-0.0310%24 Dec
overpass4–13-0.0420%24 Dec
inferno11–130.0114%23 Dec
nuke13–9-0.0428%23 Dec
mirage6–13-0.0525%19 Dec
overpass8–13-0.0519%18 Dec
inferno8–13-0.0120%17 Dec
dust213–50.0213%17 Dec
vertigo9–13-0.058%17 Dec
vertigo12–120.0527%17 Dec
dust210–13-0.0115%17 Dec
mirage1–6-0.130%16 Dec
ancient10–13-0.0524%16 Dec
vertigo13–60.0413%16 Dec
anubis12–12-0.0114%16 Dec
train13–9-0.0417%15 Dec
train1–5-0.0129%15 Dec
inferno4–13-0.0322%15 Dec
ancient13–10-0.0024%14 Dec
mirage16–12-0.0333%14 Dec
mirage8–13-0.055%13 Dec
ancient4–13-0.0118%13 Dec
ancient10–13-0.086%13 Dec
inferno13–100.0032%12 Dec
ancient5–13-0.0625%12 Dec
mirage6–130.0124%12 Dec
ancient9–13-0.0815%11 Dec
inferno13–6-0.095%11 Dec
mirage13–10-0.029%11 Dec
inferno12–7-0.0221%11 Dec
dust213–60.0121%11 Dec
nuke8–130.0114%10 Dec
ancient10–13-0.0213%10 Dec
train9–13-0.0627%9 Dec
dust21–13-0.129%9 Dec
dust29–130.0216%9 Dec
inferno13–90.0418%8 Dec
ancient13–10.0218%8 Dec
ancient11–13-0.0116%7 Dec

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 →