D Azoff

D Azoff — CS2 Stats

76561199035900632[U:1:1075634904]Steam profile ↗✓ No bans

2,619Tracked matches48%Win rate2020Tracked since
CSDB Rating5.2 DevelopingSupport
Premier CS Rating14,249Blue band · top ~32.4% of ranked players (population est.)
FaceitLevel 6 · 1,293 ELOTop 54.0% of ranked FACEIT players
WingmanMaster Guardian I
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 29 Oct 2026 (7 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: 14,249 -2,148 31 Aug – 29 Oct · 24 days played
13,44917,505peak 17,50531 Aug29 Oct
Faceit ELO: 1,293 +0 31 Aug – 25 Sept · 4 observations
1,2931,293peak 1,29331 Aug25 Sept
18,399Peak Premier in tracked matches
1,293Highest Faceit ELO seen on CSDB
23Days played since 2026-08-31

Faceit ELO

  • At peak — 1,293
  • 0 over 30 days · steady
  • Next: Level 7 at 1,351 — 58 to go
  • Reached: Level 6 · Level 5 · Level 4 · Level 3
  • Level 6 first seen 2026-08-31
  • Level 5 first seen 2026-08-31

Premier CS Rating

  • 3,256 below peak (17,505)
  • -814 over 30 days · declining
  • Next: Purple band at 15,000 — 751 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-08-31
  • Blue band first seen 2026-08-31

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.GGD AzoffFACEITLevel 6 · 1,293 ELOSTANDINGTop 54.0% of rankedPREMIER14,249 · Blue band30 DAYS0 ELOPEAK ELO1,293csdb.gg/stats

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Performance scores

Aim63
Positioning58
Utility68

0–100 skill scores via Leetify.

Recent form

COLD43–55–2Last 10043%Win rateLWLLLLWLLL

Last 10 vs previous 10: −60pp win rate · −0.04 avg rating · −8.5pp headshot accuracy · +30ms reaction

Win rate down 60pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 9%
  • Avg reaction 537ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 10%
  • Avg reaction 571ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 14%
  • Avg reaction 556ms

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: Support — Utility contribution stands above the rest of this profile (+2.4 against its own average).

Aim6.3
Utility6.8
Positioning5.8
Opening Duels1.8
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

iM

Plays most like iM 72% 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

Reaction time. 563ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% 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

Aim6.3
Positioning5.8
Utility6.8
Mechanics4.3
Opening Duels3.4
Win Impact4.4

Composite 5.2/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.00
first ⅓ avg -0.00 → last ⅓ avg -0.01
Reaction time558ms+15ms
first ⅓ avg 542ms → last ⅓ avg 558ms
Headshot accuracy14.3%+1.6%
first ⅓ avg 12.7% → last ⅓ avg 14.3%

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

0.20Best match rating · 13–1 · nuke, 1 Oct →
38%Best headshot accuracy · 2–13 · dust2, 15 Oct →
359msFastest reaction time · 10–13 · mirage, 22 Oct →
13–1Biggest win · nuke, 1 Oct →

Across the last 100 tracked matches.

Highlights

6Longest win streak
6–5In matches decided by ≤2 rounds
8Overtime games

Map breakdown

cacheBest map · 63% over 8infernoWeakest map · 29% over 14
MapGradePlayedRecordWin rateAvg rating
nukeA2112–957%0.01
mirageC156–940%0.00
infernoD144–1029%-0.03
ancientC145–936%-0.03
anubisD144–1029%-0.01
dust2A127–558%-0.02
cacheA85–363%0.00
vertigo—20–20%-0.02

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 14). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

369Matches
49%Win rate
0.93Avg K/D
75.3ADR
35%Headshot %

Clutches & streaks

36%1v1 clutch win
17%1v2 clutch win
9Longest win streak

Recent Faceit resultsWWWWL

MapMatchesWin rateAvg K/DAvg kills
Nuke7556%1.0114.7
Ancient6055%1.0214.7
Anubis5949%0.9314.0
Dust23850%0.9014.1
Mirage3842%0.8313.3
Inferno3631%0.9213.6
Train1861%1.1412.9
Cache1567%0.8912.2

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.

13.0%Headshot accuracy
38.2%Accuracy (enemy spotted)
38.9%Spray accuracy
69.4%Counter-strafing
10.2°Preaim
563msReaction time
48.1%T opening success
38.8%CT opening success
0.57Enemies flashed / flash
9.7%Flash assists
11.91HE damage / grenade
8.47Flashes / 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. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 12.9724% — below the 15% mark we flag

    Aim Training →
  2. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 38.7873% — 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.

29% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno2–13-0.1011%29 Oct →
ancient13–6-0.059%29 Oct →
mirage4–13-0.048%29 Oct →
ancient7–13-0.0111%29 Oct →
nuke9–130.068%29 Oct →
ancient5–13-0.0411%24 Oct →
nuke13–70.0216%24 Oct →
anubis13–16-0.029%24 Oct →
inferno11–13-0.004%23 Oct →
ancient8–13-0.088%23 Oct →
dust213–60.0323%23 Oct →
nuke16–14-0.0312%23 Oct →
dust213–70.0117%23 Oct →
anubis13–6-0.057%23 Oct →
vertigo7–130.0019%23 Oct →
nuke13–60.0612%23 Oct →
mirage13–7-0.0033%23 Oct →
anubis13–40.088%23 Oct →
anubis10–130.0116%23 Oct →
cache13–20.0733%23 Oct →
cache10–130.025%22 Oct →
mirage10–130.0110%22 Oct →
nuke13–110.0018%16 Oct →
ancient13–5-0.0019%16 Oct →
nuke13–110.0314%16 Oct →
anubis5–130.0113%16 Oct →
vertigo8–13-0.049%16 Oct →
nuke12–120.018%16 Oct →
mirage9–13-0.0117%16 Oct →
nuke13–70.0510%15 Oct →
dust22–13-0.1138%15 Oct →
cache5–13-0.0120%15 Oct →
mirage5–13-0.0616%15 Oct →
nuke13–10-0.0412%15 Oct →
inferno13–16-0.0212%14 Oct →
dust211–130.0210%14 Oct →
anubis7–130.0515%14 Oct →
mirage2–13-0.0213%14 Oct →
mirage9–13-0.089%14 Oct →
inferno13–9-0.0519%13 Oct →
dust213–70.0316%13 Oct →
dust213–80.0111%13 Oct →
nuke8–130.006%13 Oct →
nuke9–130.039%12 Oct →
mirage8–130.0611%12 Oct →
nuke7–00.014%12 Oct →
nuke11–130.018%12 Oct →
ancient8–13-0.0611%9 Oct →
nuke9–13-0.0515%9 Oct →
ancient11–13-0.025%9 Oct →
cache9–13-0.007%9 Oct →
anubis13–10-0.0618%8 Oct →
inferno13–100.019%8 Oct →
mirage13–70.1117%8 Oct →
ancient16–14-0.047%8 Oct →
dust213–60.008%7 Oct →
inferno13–7-0.0727%5 Oct →
anubis13–16-0.084%4 Oct →
dust213–8-0.0512%4 Oct →
inferno9–13-0.029%3 Oct →
dust213–11-0.0210%3 Oct →
mirage13–80.0113%3 Oct →
dust215–15-0.082%2 Oct →
nuke2–13-0.0911%2 Oct →
inferno7–13-0.048%2 Oct →
cache13–80.000%1 Oct →
inferno3–13-0.0424%1 Oct →
nuke13–10.2020%1 Oct →
mirage10–130.0915%1 Oct →
ancient16–14-0.0310%27 Sept →
anubis10–13-0.008%27 Sept →
nuke13–70.0213%25 Sept →
dust24–13-0.037%25 Sept →
inferno9–130.055%24 Sept →
mirage13–2-0.0120%24 Sept →
inferno9–13-0.0419%24 Sept →
anubis6–13-0.0310%24 Sept →
mirage13–60.0313%24 Sept →
nuke13–9-0.059%24 Sept →
cache13–80.0217%23 Sept →
anubis4–13-0.0817%23 Sept →
cache16–13-0.0513%23 Sept →
ancient5–13-0.015%23 Sept →
inferno5–13-0.073%22 Sept →
anubis11–13-0.0014%22 Sept →
ancient6–2-0.1113%22 Sept →
mirage3–13-0.0913%18 Sept →
dust21–13-0.0811%18 Sept →
nuke13–100.0211%18 Sept →
inferno4–13-0.0926%18 Sept →
ancient4–130.028%18 Sept →
nuke10–130.0619%18 Sept →
anubis8–13-0.069%18 Sept →
ancient10–13-0.0218%18 Sept →
ancient7–130.0117%18 Sept →
inferno13–30.1318%18 Sept →
anubis13–100.0713%18 Sept →
cache13–10-0.0211%18 Sept →
nuke7–13-0.0215%18 Sept →
mirage13–60.053%18 Sept →

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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