Fabi6523

Fabi6523 — CS2 Stats

DE76561198113345530[U:1:153079802]Steam profile ↗✓ No bans

1,501Tracked matches36%Win rate2020Tracked since
4,507Hours in CS4Hrs last 2 wks
CSDB Rating6.1 SolidPositional Player
Premier CS Rating22,201Top 50% of 213,211 CSDB-tracked playersPink band · top ~6.1% of ranked players (population est.)
CSDB Leaderboard#53856 of 259901 tracked
WingmanLegendary Eagle
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 27 Oct 2026 (8 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 22,201 -1,087 26 Jul – 27 Oct · 33 days played
21,41925,379peak 25,37926 Jul27 Oct
25,488Peak Premier in tracked matches
39Days played since 2026-07-26

Premier CS Rating

  • 3,178 below peak (25,379)
  • -1,536 over 30 days · declining
  • -982 over 90 days
  • Next: Red band at 25,000 — 2,799 to go
  • Reached: Red band · Pink band · Purple band · Blue band
  • Pink band first seen 2026-09-03
  • Purple band first seen 2026-09-03

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 Pink band among CSDB-tracked players (n=38,294), 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 playerPink band medianRed band medianvs Red band
Headshot rate41.9%46.9%49.3%7.4% short
Shot accuracy14.7%13.0%13.4%above
Kill/death ratio1.261.081.12above
Match win rate48.8%46.7%48.5%meets

This profile matches the typical Red band player on 3 of 4 comparable metrics.

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

Share this profile

CSDB.GGFabi6523PREMIER22,201 · Pink bandcsdb.gg/stats

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Performance scores

Aim85
Positioning64
Utility42

0–100 skill scores via Leetify.

Recent form

COLD46–49–5Last 10046%Win rateLLLLTWLLLL

Last 10 vs previous 10: −50pp win rate · +0.01 avg rating · −0.5pp headshot accuracy · −4ms reaction

Win rate down 50pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.01), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 0–4–1 · 0% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 19%
  • Avg reaction 484ms

Last 10

  • 1–8–1 · 10% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 19%
  • Avg reaction 479ms

Last 20

  • 7–12–1 · 35% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 20%
  • Avg reaction 481ms

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 (+1.8 against its own average).

Aim8.5
Utility4.2
Positioning6.4
Opening Duels4.7
Clutch3.0

Sharp aimer

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 96% playstyle similarity

Most alike: positioning profile, aim 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.

CT openings. Opening success drops from 58% on T to 41% on CT — first contacts on the defending side are being lost.

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

Aim8.5
Positioning6.4
Utility4.2
Mechanics6.6
Opening Duels4.9
Win Impact0.2

Composite 6.1/10 (Solid), 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 rating0.01−0.00
first ⅓ avg 0.01 → last ⅓ avg 0.01
Reaction time505ms−2ms
first ⅓ avg 507ms → last ⅓ avg 505ms
Headshot accuracy21.7%−0.5%
first ⅓ avg 22.2% → last ⅓ avg 21.7%

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

0.31Best match rating · 9–3 · inferno, 21 Oct →
57%Best headshot accuracy · 2–9 · inferno, 22 Aug →
250msFastest reaction time · 2–9 · inferno, 22 Aug →
13–2Biggest win · nuke, 16 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L4Current streak
5–6In matches decided by ≤2 rounds
9Overtime games

Map breakdown

cacheBest map · 64% over 14anubisWeakest map · 33% over 12
MapGradePlayedRecordWin rateAvg rating
infernoC3314–1942%0.02
cacheA149–564%0.04
dust2B126–650%-0.02
anubisD124–833%0.01
mirageC114–736%0.01
ancientA116–555%0.01
nuke—32–167%0.01
overpass—21–150%0.04
vertigo—10–10%-0.15
eldorado—10–10%-0.07

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (33% over 12). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

128,564Lifetime kills
1.26K/D · Top 25% of Pink band
6,595Matches
48.8%Match win rate · Top 50% of Pink band
41.9%Headshot %
14.7%Shot accuracy · Top 50% of Pink band
18,742MVPs
2,490Hours (in match)
9,810Bombs planted
1,964Bombs defused

Most-used weapons

AK-4735,799
AWP17,520
P2503,559
SSG 083,194
P902,260

Lifetime map wins

11,864dust2
11,517inferno
2,479cbble
1,597nuke
536train
404vertigo
324safehouse
209office

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

Faceit stats

Combat

541Matches
53%Win rate
1.49Avg K/D
88.7ADR
45%Headshot %

Clutches & streaks

35%1v1 clutch win
25%1v2 clutch win
11Longest win streak

Recent Faceit resultsLWLLW

MapMatchesWin rateAvg K/DAvg kills
Inferno757%1.5018.0
Ancient683%1.5012.8
Anubis450%1.8215.5
Mirage475%1.3819.0
Dust2250%1.1015.0
Nuke10%1.0016.0
Cache1100%1.6221.0

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.

20.5%Headshot accuracy
35.1%Accuracy (enemy spotted)
40.3%Spray accuracy
79.9%Counter-strafing
8.5°Preaim
495msReaction time
58.0%T opening success
41.5%CT opening success
0.41Enemies flashed / flash
3.2%Flash assists
8.01HE damage / grenade
6.17Flashes / 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. 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 0.41 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Anubis

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 12 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno9–130.0122%27 Oct →
dust26–130.0017%27 Oct →
inferno10–13-0.0127%23 Oct →
dust29–13-0.0213%23 Oct →
inferno12–120.0519%22 Oct →
inferno9–30.3135%21 Oct →
mirage5–130.028%20 Oct →
anubis1–80.0419%19 Oct →
dust26–13-0.0325%19 Oct →
mirage4–13-0.0410%18 Oct →
anubis13–10-0.0423%18 Oct →
cache7–130.0020%18 Oct →
dust213–60.0223%18 Oct →
mirage13–90.0823%18 Oct →
inferno1–9-0.1719%17 Oct →
inferno13–100.0316%15 Oct →
mirage13–110.1232%11 Oct →
ancient13–80.1318%11 Oct →
inferno8–130.0110%27 Sept →
anubis13–160.0317%25 Sept →
inferno11–13-0.0125%25 Sept →
inferno9–130.0021%24 Sept →
ancient9–13-0.0320%13 Sept →
anubis2–130.0226%13 Sept →
dust216–12-0.0323%13 Sept →
dust29–13-0.0722%13 Sept →
inferno3–9-0.0733%10 Sept →
anubis8–13-0.0222%7 Sept →
cache7–130.0328%6 Sept →
anubis7–3-0.0150%6 Sept →
ancient13–100.0519%6 Sept →
ancient13–70.0222%6 Sept →
mirage15–15-0.0412%5 Sept →
dust213–4-0.0422%5 Sept →
inferno4–9-0.1110%5 Sept →
vertigo0–9-0.1511%5 Sept →
inferno9–60.1018%5 Sept →
dust213–11-0.0419%4 Sept →
ancient14–16-0.0013%30 Aug →
cache13–40.0714%30 Aug →
dust213–110.0719%30 Aug →
inferno13–90.0919%30 Aug →
inferno4–13-0.0420%29 Aug →
cache13–110.0629%29 Aug →
inferno13–60.0629%29 Aug →
inferno13–40.0815%28 Aug →
inferno1–13-0.105%26 Aug →
mirage14–16-0.0117%25 Aug →
inferno16–120.0627%22 Aug →
inferno4–130.0030%22 Aug →
overpass5–9-0.0115%22 Aug →
overpass9–40.0913%22 Aug →
inferno2–9-0.1557%22 Aug →
inferno7–90.049%22 Aug →
inferno3–9-0.0235%22 Aug →
inferno8–80.0412%22 Aug →
inferno9–40.1518%22 Aug →
inferno9–40.2022%22 Aug →
mirage13–10-0.0329%22 Aug →
inferno9–50.1326%22 Aug →
eldorado4–9-0.0730%21 Aug →
anubis9–130.0114%20 Aug →
mirage13–40.0732%20 Aug →
nuke13–2-0.0424%16 Aug →
anubis10–13-0.0211%16 Aug →
dust213–100.0217%16 Aug →
ancient3–13-0.0818%15 Aug →
nuke13–100.0314%15 Aug →
cache13–90.0225%15 Aug →
anubis13–20.0925%15 Aug →
ancient13–8-0.0038%15 Aug →
cache13–100.0628%15 Aug →
anubis9–13-0.0317%15 Aug →
cache12–12-0.0813%11 Aug →
dust28–13-0.0624%11 Aug →
inferno13–100.0324%10 Aug →
mirage3–13-0.0316%10 Aug →
cache15–150.0422%9 Aug →
mirage9–130.0030%9 Aug →
inferno16–14-0.0220%9 Aug →
inferno3–130.0131%9 Aug →
ancient6–13-0.0630%9 Aug →
ancient5–13-0.0025%9 Aug →
cache10–13-0.0017%7 Aug →
cache13–40.1423%7 Aug →
ancient13–50.0218%7 Aug →
anubis11–130.0121%7 Aug →
anubis13–100.0723%6 Aug →
cache16–130.0221%6 Aug →
ancient13–60.0420%6 Aug →
inferno13–60.0328%6 Aug →
inferno11–130.0428%3 Aug →
inferno13–9-0.006%3 Aug →
mirage2–13-0.0615%3 Aug →
cache13–50.0628%2 Aug →
dust22–13-0.0514%31 Jul →
inferno2–13-0.0325%31 Jul →
cache13–20.1018%31 Jul →
nuke8–130.0331%28 Jul →
cache13–80.0316%26 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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.