adr1an

adr1an — CS2 Stats

SE76561198054699661[U:1:94433933]Steam profile ↗✓ No bans

719Tracked matches47%Win rate2020Tracked since
9,781Hours in CS7Hrs last 2 wks
CSDB Rating6.8 SolidPositional Player
Premier CS Rating23,253Top 25% of 212,133 CSDB-tracked playersPink band · top ~4.9% of ranked players (population est.)
CSDB Leaderboard#40628 of 258985 tracked
FaceitLevel 9Top 20.7% of ranked FACEIT players
WingmanSupreme Master First Class
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 10 Oct 2026 (21 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: 23,253 -203 2 Nov – 10 Oct · 17 days played
19,25824,171peak 24,1712 Nov10 Oct
24,171Peak Premier in tracked matches
39Days played since 2025-11-02

Premier CS Rating

  • 918 below peak (24,171)
  • +678 over 30 days · improving
  • -366 over 90 days
  • Next: Red band at 25,000 — 1,747 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band

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 Level 9 among CSDB-tracked players (n=15,132), 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 playerLevel 9 medianLevel 10 medianvs Level 10
Headshot rate44.0%48.2%50.9%6.9% short
Shot accuracy21.8%13.2%13.7%above
Kill/death ratio0.741.071.090.34 short
Match win rate47.8%46.9%48.4%meets

This profile matches the typical Level 10 player on 2 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Level 10 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGadr1anFACEITLevel 9STANDINGTop 20.7% of rankedPREMIER23,253 · Pink bandcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim77
Positioning70
Utility60

0–100 skill scores via Leetify.

Recent form

STEADY48–50–2Last 10048%Win rateWWWLWWLLLL

Last 10 vs previous 10: −10pp win rate · −0.02 avg rating · −3.4pp headshot accuracy · −8ms 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

  • 4–1 · 80% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 14%
  • Avg reaction 472ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 14%
  • Avg reaction 496ms

Last 20

  • 11–9 · 55% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 16%
  • Avg reaction 500ms

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 (+2.5 against its own average).

Aim7.7
Utility6.0
Positioning7.0
Opening Duels5.0
Clutch0.0

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

Twistzz

Plays most like Twistzz 91% playstyle similarity

Most alike: positioning profile, utility contribution.

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 →

CSDB Rating breakdown

Aim7.7
Positioning7.0
Utility6.0
Mechanics6.6
Opening Duels6.3
Win Impact3.9

Composite 6.8/10 (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 rating0.01−0.01
first ⅓ avg 0.02 → last ⅓ avg 0.01
Reaction time505ms−62ms
first ⅓ avg 567ms → last ⅓ avg 505ms
Headshot accuracy15.8%+2.5%
first ⅓ avg 13.3% → last ⅓ avg 15.8%

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

0.12Best match rating · 13–6 · cache, 9 Oct →
33%Best headshot accuracy · 3–13 · nuke, 24 Sept →
367msFastest reaction time · 13–9 · inferno, 25 Oct →
13–2Biggest win · anubis, 25 Jun →

Across the last 100 tracked matches.

Highlights

5Longest win streak
W3Current streak
7–12In matches decided by ≤2 rounds
7Overtime games

Map breakdown

infernoBest map · 70% over 20mirageWeakest map · 33% over 24
MapGradePlayedRecordWin rateAvg rating
mirageD248–1633%0.00
infernoS2014–670%0.03
nukeB168–850%0.03
cacheA106–460%0.02
ancientB105–550%-0.00
overpassC94–544%0.01
anubis—42–250%-0.00
train—31–233%0.03
dust2—30–30%-0.03
vertigo—10–10%-0.09

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (33% over 24). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Lifetime stats

315,851Lifetime kills
0.74K/D
8,851Matches
47.8%Match win rate · Top 50% of Level 9 players
44.0%Headshot %
21.8%Shot accuracy · Top 5% of Level 9 players
21,340MVPs
5,928Hours (in match)
13,956Bombs planted
2,994Bombs defused

Most-used weapons

AK-47132,732
AWP44,520
P25011,304
SG 5534,932
Knife3,891

Lifetime map wins

18,643inferno
11,801dust2
7,418train
7,100nuke
3,187cbble
826vertigo
286lake
138safehouse

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

Faceit stats

Combat

1,840Matches
51%Win rate
1.12Avg K/D
68.2ADR
31%Headshot %

Clutches & streaks

17%1v1 clutch win
20%1v2 clutch win
9Longest win streak

Recent Faceit resultsWLLLL

MapMatchesWin rateAvg K/DAvg kills
Inferno540%0.9614.8
Dust2333%0.7912.3
Ancient3100%0.9714.0
Overpass30%0.7311.3
Mirage250%0.9013.5
Nuke1100%0.274.0
Anubis10%0.7112.0

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.

15.9%Headshot accuracy
38.1%Accuracy (enemy spotted)
36.8%Spray accuracy
79.8%Counter-strafing
10.2°Preaim
509msReaction time
58.6%T opening success
52.1%CT opening success
0.64Enemies flashed / flash
4.3%Flash assists
9.14HE damage / grenade
11.99Flashes / match

Recommended for you

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.

33% win rate across 24 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache13–90.0924%27 Oct →
inferno13–80.0313%27 Oct →
mirage13–80.0010%27 Oct →
overpass5–13-0.047%27 Oct →
inferno13–90.0217%25 Oct →
cache13–90.054%25 Oct →
mirage10–13-0.029%25 Oct →
mirage11–130.0114%17 Oct →
mirage7–13-0.0624%13 Oct →
inferno8–13-0.0319%13 Oct →
nuke13–90.0411%13 Oct →
overpass13–40.0019%10 Oct →
cache11–130.0217%10 Oct →
inferno13–60.0215%10 Oct →
anubis7–13-0.0217%10 Oct →
cache13–60.1211%9 Oct →
nuke13–70.0626%9 Oct →
anubis5–13-0.0224%9 Oct →
cache16–19-0.0118%4 Oct →
inferno22–200.0115%4 Oct →
inferno11–130.0014%3 Oct →
vertigo7–13-0.094%2 Oct →
nuke3–13-0.0433%24 Sept →
inferno13–70.0819%24 Sept →
nuke13–90.0619%13 Sept →
train9–13-0.0114%13 Sept →
ancient4–13-0.057%13 Sept →
mirage8–13-0.0312%13 Sept →
inferno13–70.0721%12 Sept →
mirage6–13-0.0224%12 Sept →
mirage3–13-0.046%6 Sept →
cache13–11-0.0110%6 Sept →
train13–100.0225%6 Sept →
ancient13–70.0212%30 Aug →
train11–130.0722%15 Aug →
inferno10–130.0021%15 Aug →
mirage8–130.0016%15 Aug →
inferno13–100.0715%25 Jul →
cache5–13-0.0013%25 Jul →
mirage13–30.0833%25 Jul →
nuke11–130.0914%25 Jul →
inferno13–50.0221%19 Jul →
nuke13–30.027%19 Jul →
mirage13–110.0619%19 Jul →
cache13–50.0033%19 Jul →
ancient13–6-0.0118%18 Jul →
nuke9–130.019%18 Jul →
cache13–9-0.059%18 Jul →
mirage13–60.019%18 Jul →
nuke13–30.0633%18 Jul →
mirage4–130.0216%18 Jul →
cache12–12-0.0020%7 Jul →
anubis13–20.0013%25 Jun →
nuke13–8-0.0220%25 Jun →
mirage13–50.0313%22 Jun →
ancient5–13-0.055%22 Jun →
overpass11–130.0213%21 Jun →
nuke13–100.0915%21 Jun →
inferno7–13-0.0128%21 Jun →
mirage13–90.0414%20 Jun →
nuke11–130.039%20 Jun →
ancient7–130.0322%20 Jun →
dust26–13-0.035%16 Jun →
mirage13–9-0.0320%16 Jun →
overpass11–13-0.0314%15 Jun →
dust27–13-0.0232%9 Jun →
ancient2–13-0.0711%9 Jun →
mirage7–13-0.0418%9 Jun →
anubis13–110.0411%8 Jun →
ancient7–13-0.0614%8 Jun →
mirage11–13-0.027%8 Jun →
mirage4–13-0.034%4 Jun →
inferno16–130.0110%4 Jun →
overpass13–10-0.0414%1 Jun →
inferno11–13-0.0011%1 Jun →
ancient13–40.0810%31 May →
inferno13–100.0813%31 May →
nuke7–13-0.0314%31 May →
mirage14–160.0618%27 May →
mirage10–130.089%17 May →
nuke13–160.0114%17 May →
inferno15–150.016%17 May →
overpass13–70.1019%17 May →
nuke10–130.009%16 May →
mirage13–90.0417%16 May →
inferno13–110.0516%16 May →
ancient13–80.0216%16 May →
mirage10–13-0.0610%16 May →
dust29–13-0.0516%16 May →
inferno13–11-0.0519%7 Mar →
ancient13–90.0514%1 Mar →
mirage8–130.0111%1 Mar →
mirage11–13-0.0017%16 Nov →
nuke13–30.0514%16 Nov →
overpass10–130.0024%10 Nov →
nuke9–130.018%10 Nov →
overpass2–13-0.0510%10 Nov →
overpass13–60.1017%3 Nov →
inferno13–100.0811%3 Nov →
inferno16–140.0414%2 Nov →

Match data via Leetify.

Recent teammates

Milestones

500 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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