AZAD

AZAD — CS2 Stats

FI76561198087038367[U:1:126772639]Steam profile ↗✓ No bans

1,898Tracked matches53%Win rate2020Tracked since
CSDB Rating7.0 StrongPositional Player
FaceitLevel 6Top 54.0% of ranked FACEIT players
WingmanLegendary Eagle Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 1 Sep 2026 (65 days ago). Ranks are recorded once per day this page is viewed.

+63Tracked matches · now 1,898
+13.3ppWin rate · 40.0% → 53.3%

Rating over time

Premier CS Rating: 18,095 -4,158 18 Jan – 1 Sept · 5 days played
18,09522,253peak 22,25318 Jan1 Sept
23,356Peak Premier in tracked matches
32Days played since 2026-01-18

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

Share this profile

CSDB.GGAZADFACEITLevel 6STANDINGTop 54.0% of rankedcsdb.gg/stats

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Performance scores

Aim73
Positioning68
Utility66

0–100 skill scores via Leetify.

Recent form

STEADY54–45–1Last 10054%Win rateWWWLLLLLWW

Last 10 vs previous 10: −10pp win rate · +0.01 avg rating · −6.5pp headshot accuracy · +1ms 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 0.02
  • Avg headshot accuracy 12%
  • Avg reaction 572ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 16%
  • Avg reaction 584ms

Last 20

  • 11–9 · 55% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 19%
  • Avg reaction 583ms

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 (+1.3 against its own average).

Aim7.3
Utility6.6
Positioning6.8
Opening Duels5.4
Clutch3.2

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 84% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: 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

Reaction time. 578ms 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

Aim7.3
Positioning6.8
Utility6.6
Mechanics7.7
Opening Duels6.7
Win Impact6.1

Composite 7.0/10 (Strong), 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 rating0.02+0.01
first ⅓ avg 0.00 → last ⅓ avg 0.02
Reaction time586ms−63ms
first ⅓ avg 649ms → last ⅓ avg 586ms
Headshot accuracy18.8%−1.2%
first ⅓ avg 19.9% → last ⅓ avg 18.8%

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

0.14Best match rating · 13–10 · ancient, 30 Mar →
41%Best headshot accuracy · 13–3 · mirage, 27 Sept →
422msFastest reaction time · 13–3 · mirage, 30 Mar →
13–2Biggest win · mirage, 17 Oct →

Across the last 100 tracked matches.

Highlights

6Longest win streak
W3Current streak
9–10In matches decided by ≤2 rounds
13Overtime games

Map breakdown

ancientBest map · 71% over 24infernoWeakest map · 17% over 12
MapGradePlayedRecordWin rateAvg rating
nukeB2815–1354%0.02
ancientS2417–771%0.01
mirageA1912–763%0.01
infernoD122–1017%-0.03
cacheB63–350%0.00
dust2—31–233%0.03
vertigo—21–150%0.04
anubis—21–150%0.01
train—21–150%0.01
overpass—21–150%0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (17% over 12). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

231Matches
54%Win rate
1.08Avg K/D
78.2ADR
44%Headshot %

Clutches & streaks

36%1v1 clutch win
29%1v2 clutch win
7Longest win streak

Recent Faceit resultsLWLWW

MapMatchesWin rateAvg K/DAvg kills
Nuke1457%1.4416.9
Ancient1362%0.8812.6
Mirage1164%1.1313.6
Cache633%0.9214.7
Inferno520%0.9716.4
Vertigo425%0.9118.5
Overpass1100%0.9416.0
Anubis1100%1.0523.0

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.

18.3%Headshot accuracy
37.0%Accuracy (enemy spotted)
39.6%Spray accuracy
84.5%Counter-strafing
11.9°Preaim
578msReaction time
55.0%T opening success
58.3%CT opening success
0.61Enemies flashed / flash
8.6%Flash assists
10.36HE damage / grenade
11.10Flashes / match

Recommended for you

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.

17% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage13–80.008%3 Nov →
cache13–10-0.0515%3 Nov →
nuke13–60.1312%3 Nov →
ancient9–130.0314%2 Nov →
mirage13–16-0.0113%2 Nov →
cache6–13-0.0514%1 Nov →
nuke7–130.0126%1 Nov →
inferno10–130.0220%1 Nov →
nuke13–70.1110%1 Nov →
ancient13–50.0526%24 Oct →
cache14–16-0.0419%18 Oct →
ancient5–13-0.069%18 Oct →
nuke13–60.0211%17 Oct →
cache13–50.0539%17 Oct →
ancient6–13-0.0622%17 Oct →
mirage13–20.0825%17 Oct →
mirage13–70.0621%17 Oct →
ancient13–30.0221%16 Oct →
cache6–13-0.0435%16 Oct →
mirage13–50.0721%16 Oct →
dust213–50.0922%16 Oct →
inferno11–130.0115%16 Oct →
nuke13–7-0.0222%16 Oct →
ancient7–13-0.0321%16 Oct →
nuke10–130.0417%16 Oct →
inferno13–90.0414%16 Oct →
ancient13–70.0322%15 Oct →
nuke8–13-0.0516%15 Oct →
mirage13–30.0221%13 Oct →
mirage14–160.0413%13 Oct →
vertigo8–130.0114%13 Oct →
ancient16–14-0.0023%13 Oct →
nuke13–90.0120%11 Oct →
ancient13–9-0.0523%7 Oct →
ancient16–120.0424%7 Oct →
vertigo16–140.0713%4 Oct →
inferno13–16-0.0521%4 Oct →
nuke13–60.0213%4 Oct →
ancient16–140.0425%4 Oct →
anubis16–140.0219%2 Oct →
nuke13–110.0832%1 Oct →
ancient13–90.0631%1 Oct →
nuke13–20.039%30 Sept →
ancient10–13-0.0317%30 Sept →
nuke10–13-0.0115%30 Sept →
ancient13–6-0.0516%30 Sept →
cache13–40.1435%29 Sept →
mirage11–60.0136%29 Sept →
nuke13–90.0524%29 Sept →
nuke5–13-0.0232%29 Sept →
nuke12–12-0.0018%27 Sept →
dust20–2-0.000%27 Sept →
train13–80.0022%27 Sept →
ancient13–20.0121%27 Sept →
mirage13–30.0641%27 Sept →
nuke13–7-0.0322%27 Sept →
ancient13–100.1425%30 Mar →
mirage13–30.0029%30 Mar →
nuke6–130.0324%29 Mar →
inferno12–16-0.0433%29 Mar →
nuke9–130.0227%10 Mar →
overpass11–130.0427%10 Mar →
inferno5–13-0.084%4 Mar →
nuke13–9-0.0128%17 Feb →
inferno6–13-0.094%17 Feb →
ancient13–30.0930%17 Feb →
inferno5–13-0.0615%15 Feb →
nuke11–130.0524%12 Feb →
ancient9–130.0133%12 Feb →
ancient13–9-0.0127%9 Feb →
inferno5–13-0.0616%28 Jan →
mirage13–11-0.0333%28 Jan →
nuke13–90.0021%26 Jan →
ancient13–80.0519%26 Jan →
mirage6–13-0.0429%25 Jan →
anubis10–130.0014%25 Jan →
overpass13–50.0513%25 Jan →
inferno13–110.0118%25 Jan →
mirage6–13-0.0620%25 Jan →
mirage8–130.0230%25 Jan →
nuke5–13-0.0122%25 Jan →
dust24–13-0.0018%25 Jan →
nuke13–100.0323%25 Jan →
ancient16–140.0217%25 Jan →
mirage5–13-0.0718%25 Jan →
nuke14–16-0.0226%24 Jan →
mirage13–11-0.0214%22 Jan →
inferno7–13-0.0215%19 Jan →
train14–160.0232%19 Jan →
ancient7–13-0.078%19 Jan →
nuke9–100.009%19 Jan →
ancient13–80.0111%19 Jan →
nuke13–20.0430%19 Jan →
mirage13–7-0.0316%19 Jan →
nuke5–13-0.0314%18 Jan →
mirage13–80.029%18 Jan →
inferno10–13-0.036%18 Jan →
mirage11–130.0115%18 Jan →
ancient13–60.0930%18 Jan →
nuke13–100.0628%18 Jan →

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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