fl4sh LFT

fl4sh LFT — CS2 Stats

UA76561199119207624[U:1:1158941896]Steam profile ↗✓ No bans

3,436Tracked matches43%Win rate2020Tracked since
CSDB Rating7.1 StrongPositional Player
FaceitLevel 10 · 2,987 ELOTop 12.4% of ranked FACEIT players
WingmanDistinguished Master Guardian
Ladder ranks via Leetify

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CSDB.GGfl4sh LFTFACEITLevel 10 · 2,987 ELOSTANDINGTop 12.4% of rankedcsdb.gg/stats

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Performance scores

Aim91
Positioning69
Utility43

0–100 skill scores via Leetify.

Recent form

STEADY52–45–3Last 10052%Win rateLLWWWWLLWT

Last 10 vs previous 10: +10pp win rate · +0.04 avg rating · +2.0pp headshot accuracy · +2ms 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

  • 3–2 · 60% win rate
  • Avg rating 0.06
  • Avg headshot accuracy 31%
  • Avg reaction 511ms

Last 10

  • 5–4–1 · 50% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 28%
  • Avg reaction 520ms

Last 20

  • 9–10–1 · 45% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 27%
  • Avg reaction 519ms

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 (+1.7 against its own average).

Aim9.1
Utility4.3
Positioning6.9
Opening Duels6.2
Clutch3.4

Sharp aimerExcellent counter-strafingStrong CT-side openerEffective 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

donk

Plays most like donk 92% playstyle similarity

Most alike: opening-duel success, aim profile.

Where you differ: lower utility contribution.

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

Strengths

Aim. Aim score of 91 — the mechanical foundation is a clear strength.

CT openings. 64% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Flashes. 0.88 enemies blinded per flash — utility that consistently lands.

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 64% on CT to 41% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim9.1
Positioning6.9
Utility4.3
Mechanics8.9
Opening Duels5.7
Win Impact2.8

Composite 7.1/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02+0.02
first ⅓ avg 0.00 → last ⅓ avg 0.02
Reaction time522ms−39ms
first ⅓ avg 560ms → last ⅓ avg 522ms
Headshot accuracy28.2%−0.7%
first ⅓ avg 28.9% → last ⅓ avg 28.2%

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

0.16Best match rating · 8–8 · inferno, 20 Oct →
63%Best headshot accuracy · 6–13 · train, 1 Apr →
336msFastest reaction time · 2–6 · vertigo, 17 Sept →
13–0Biggest win · mirage, 26 Jul →

Across the last 100 tracked matches.

Highlights

7Longest win streak
L2Current streak
13–14In matches decided by ≤2 rounds
25Overtime games

Map breakdown

nukeBest map · 70% over 10trainWeakest map · 30% over 10
MapGradePlayedRecordWin rateAvg rating
mirageA2716–1159%0.00
ancientB199–1047%-0.01
anubisB136–746%0.01
trainD103–730%0.01
nukeS107–370%0.04
dust2A95–456%0.02
infernoA74–357%0.06
overpass—42–250%-0.01
vertigo—10–10%0.05

Across the last 100 tracked matches.

Faceit stats

Combat

3,574Matches
52%Win rate
1.22Avg K/D
79.4ADR
47%Headshot %

Clutches & streaks

37%1v1 clutch win
22%1v2 clutch win
9Longest win streak

Recent Faceit resultsLLLWL

MapMatchesWin rateAvg K/DAvg kills
Ancient65853%1.2117.6
Anubis57354%1.2617.6
Mirage47251%1.1816.8
Dust224245%1.1316.5
Nuke24054%1.2417.4
Inferno14642%1.1215.7
Vertigo13459%1.3517.6
Overpass13248%1.2616.9

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.

27.3%Headshot accuracy
36.8%Accuracy (enemy spotted)
32.9%Spray accuracy
90.0%Counter-strafing
8.1°Preaim
514msReaction time
41.4%T opening success
64.3%CT opening success
0.88Enemies flashed / flash
17.0%Flash assists
5.29HE damage / grenade
12.87Flashes / match

Recommended for you

Spend your practice time on Train

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

30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
train11–130.0533%3 Dec →
train20–220.0227%20 Nov →
nuke13–40.1441%20 Nov →
train16–130.0227%13 Nov →
nuke13–40.0529%10 Nov →
mirage13–100.0533%10 Nov →
train7–13-0.0226%8 Nov →
ancient15–19-0.0115%5 Nov →
nuke13–100.0220%4 Nov →
inferno8–80.1633%20 Oct →
dust213–100.0721%20 Oct →
dust213–30.1627%19 Oct →
overpass20–22-0.0326%18 Oct →
mirage11–130.0630%4 Oct →
mirage13–11-0.0221%3 Oct →
mirage13–6-0.0225%30 Sept →
dust211–130.0128%27 Sept →
vertigo2–60.0543%17 Sept →
nuke8–13-0.0629%11 Sept →
mirage3–13-0.1114%7 Sept →
train8–130.0122%5 Sept →
nuke13–10.0725%26 Aug →
overpass9–13-0.0246%26 Aug →
overpass16–14-0.0229%26 Aug →
nuke10–13-0.0127%25 Aug →
mirage6–13-0.0624%7 Aug →
dust29–130.0240%6 Aug →
train10–13-0.0516%5 Aug →
ancient13–110.0234%2 Aug →
train8–13-0.0233%1 Aug →
inferno13–80.1021%29 Jul →
mirage13–00.0535%26 Jul →
overpass13–20.0428%19 Jul →
ancient13–40.0723%19 Jul →
ancient15–15-0.0143%18 Jul →
mirage13–30.0123%18 Jul →
ancient5–13-0.0232%5 Jul →
mirage8–130.0139%2 Jul →
ancient13–20.0233%2 Jul →
mirage13–8-0.0320%24 Jun →
inferno11–130.0718%16 Jun →
mirage13–90.0327%16 Jun →
nuke13–40.0122%16 Jun →
ancient4–13-0.0321%8 Jun →
inferno13–8-0.0123%30 May →
mirage14–160.0314%28 May →
ancient15–190.0331%13 May →
train13–30.0032%12 May →
anubis13–8-0.0133%11 May →
anubis13–9-0.0025%9 May →
nuke5–130.0420%9 May →
ancient13–90.0330%1 May →
ancient7–13-0.0317%30 Apr →
anubis13–160.0538%30 Apr →
mirage13–50.1231%30 Apr →
anubis13–110.0728%26 Apr →
ancient16–140.0228%25 Apr →
mirage16–120.0035%24 Apr →
mirage13–60.0537%22 Apr →
mirage16–12-0.0526%19 Apr →
inferno13–6-0.0224%17 Apr →
dust212–160.0422%17 Apr →
ancient15–15-0.0223%16 Apr →
dust216–12-0.0318%12 Apr →
dust213–110.0243%7 Apr →
ancient13–4-0.0131%4 Apr →
mirage14–16-0.0125%2 Apr →
anubis13–160.0133%1 Apr →
train6–130.0663%1 Apr →
nuke13–110.0422%25 Mar →
mirage16–14-0.0223%23 Mar →
mirage10–13-0.0413%20 Mar →
anubis8–130.0019%18 Mar →
mirage11–130.0125%18 Mar →
mirage14–160.0231%17 Mar →
train13–90.0320%12 Mar →
mirage13–6-0.0029%12 Mar →
mirage9–130.0127%9 Mar →
mirage13–5-0.0134%8 Mar →
inferno7–90.1040%5 Mar →
ancient11–130.0023%4 Mar →
ancient9–13-0.0020%26 Feb →
dust213–10-0.0424%25 Feb →
inferno13–11-0.0038%22 Feb →
ancient13–16-0.0419%20 Feb →
mirage16–14-0.0429%19 Feb →
anubis6–130.0629%18 Feb →
anubis3–13-0.1120%16 Feb →
nuke13–20.0844%14 Feb →
anubis19–170.0444%10 Feb →
ancient13–6-0.0729%1 Feb →
dust29–13-0.0327%18 Jan →
anubis16–14-0.0229%8 Jan →
anubis12–160.0127%8 Jan →
anubis13–30.0629%7 Jan →
ancient13–10-0.0624%6 Jan →
mirage11–13-0.0024%6 Jan →
mirage13–70.0433%1 Jan →
ancient16–14-0.0131%22 Dec →
anubis11–13-0.0632%22 Dec →

Match data via Leetify.

Recent teammates

Milestones

Faceit Level 102.5K ELO1,000 MatchesAim 90+
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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