Albon

Albon — CS2 Stats

BT76561199098681878[U:1:1138416150]Steam profile ↗✓ No bans

184Tracked matches43%Win rate2025Tracked since
284Hours in CS
CSDB Rating2.7 LearningClutch Specialist
Premier CS Rating3,362Grey band · top ~85.7% of ranked players (population est.)
WingmanSilver III
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 24 Oct 2026 (12 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: 3,362 +238 15 Mar – 24 Oct · 11 days played
2,0863,362peak 3,36215 Mar24 Oct
3,362Peak Premier in tracked matches
41Days played since 2026-03-15

Premier CS Rating

  • At peak — 3,362
  • +503 over 30 days · improving
  • Next: Light Blue band at 5,000 — 1,638 to go

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 Grey band among CSDB-tracked players (n=3,645), 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 playerGrey band medianLight Blue band medianvs Light Blue band
Headshot rate36.2%38.2%39.9%3.8% short
Shot accuracy0.2%3.6%7.0%6.7% short
Kill/death ratio0.820.830.920.10 short
Match win rate43.6%40.2%42.3%above

This profile matches the typical Light Blue band player on 1 of 4 comparable metrics.

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

Share this profile

CSDB.GGAlbonPREMIER3,362 · Grey 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

Aim25
Positioning37
Utility30

0–100 skill scores via Leetify.

Recent form

STEADY35–64–1Last 10035%Win rateWWLLWLWWLL

Last 10 vs previous 10: 0pp win rate · −0.01 avg rating · −1.4pp headshot accuracy · −22ms reaction

Win rate 0pp 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 -0.08
  • Avg headshot accuracy 14%
  • Avg reaction 566ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 9%
  • Avg reaction 686ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 10%
  • Avg reaction 697ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+1.3 against its own average).

Aim2.5
Utility3.0
Positioning3.7
Opening Duels0.0
Clutch4.0

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 72% playstyle similarity

Most alike: positioning profile, utility contribution.

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. 671ms 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

Aim2.5
Positioning3.7
Utility3.0
Mechanics4.6
Opening Duels1.1
Win Impact2.8

Composite 2.7/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.05−0.00
first ⅓ avg -0.05 → last ⅓ avg -0.05
Reaction time667ms−18ms
first ⅓ avg 685ms → last ⅓ avg 667ms
Headshot accuracy11.3%+0.9%
first ⅓ avg 10.4% → last ⅓ avg 11.3%

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

0.08Best match rating · 13–2 · ancient, 7 Apr →
33%Best headshot accuracy · 6–9 · inferno, 25 Oct →
422msFastest reaction time · 9–3 · vertigo, 25 Oct →
21–0Biggest win · anubis, 26 Oct →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W2Current streak
7–6In matches decided by ≤2 rounds
2Overtime games

Map breakdown

ancientBest map · 50% over 10infernoWeakest map · 18% over 11
MapGradePlayedRecordWin rateAvg rating
mirageB3114–1745%-0.05
nukeD164–1225%-0.08
infernoD112–918%-0.09
ancientB105–550%-0.03
cacheC94–544%-0.04
anubisD72–529%-0.07
dust2D72–529%-0.04
train—40–40%-0.04
vertigo—41–325%-0.11
overpass—11–0100%-0.08

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (18% over 11). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

11,569Lifetime kills
0.82K/D
1,085Matches
43.6%Match win rate · Top 25% of Grey band
36.2%Headshot %
0.2%Shot accuracy
3,157MVPs
284Hours (in match)
631Bombs planted
173Bombs defused

Most-used weapons

Lifetime map wins

1,747inferno
1,455nuke
1,113dust2
416vertigo
112train
64office
3italy
2assault

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

Faceit stats

Combat

13Matches
46%Win rate
0.85Avg K/D
74.8ADR
33%Headshot %

Clutches & streaks

40%1v1 clutch win
14%1v2 clutch win
2Longest win streak

Recent Faceit resultsLLLWW

MapMatchesWin rateAvg K/DAvg kills
Mirage729%0.7814.0
Nuke2100%1.0218.0
Anubis250%0.8014.0
Ancient10%0.388.0
Dust21100%1.5722.0

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.

11.6%Headshot accuracy
27.2%Accuracy (enemy spotted)
23.8%Spray accuracy
70.8%Counter-strafing
10.0°Preaim
671msReaction time
36.4%T opening success
32.4%CT opening success
0.38Enemies flashed / flash
1.8%Flash assists
8.61HE damage / grenade
6.21Flashes / 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 11.5775% — below the 15% mark we flag

    Aim Training →
  2. 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 0.3787 — below the 0.5 mark we flag

    Grenade Lineups →
  3. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 36.4231% — 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.

18% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache13–10-0.0712%26 Oct →
anubis21–0-0.056%26 Oct →
train10–13-0.0510%26 Oct →
inferno6–9-0.1033%25 Oct →
vertigo9–3-0.128%25 Oct →
anubis7–13-0.080%25 Oct →
inferno13–1-0.045%25 Oct →
mirage13–0-0.013%24 Oct →
cache6–13-0.087%24 Oct →
mirage2–13-0.0911%24 Oct →
inferno2–9-0.270%23 Oct →
dust26–3-0.030%23 Oct →
dust27–13-0.0314%23 Oct →
nuke3–9-0.075%23 Oct →
train8–13-0.0411%22 Oct →
mirage8–13-0.0516%21 Oct →
mirage13–110.0111%20 Oct →
nuke13–2-0.0627%20 Oct →
mirage13–7-0.0114%20 Oct →
cache13–6-0.0511%19 Oct →
mirage7–13-0.0724%19 Oct →
nuke7–13-0.079%19 Oct →
train6–13-0.074%19 Oct →
nuke11–13-0.090%19 Oct →
mirage13–30.0114%19 Oct →
cache0–13-0.0311%19 Oct →
ancient8–13-0.017%18 Oct →
mirage7–13-0.0819%18 Oct →
mirage6–13-0.0217%18 Oct →
dust29–13-0.0617%18 Oct →
mirage13–70.0119%18 Oct →
mirage13–11-0.0013%17 Oct →
nuke6–130.0517%15 Oct →
mirage13–7-0.056%14 Oct →
vertigo0–9-0.155%13 Oct →
inferno9–70.058%11 Oct →
ancient9–13-0.0113%8 Oct →
anubis9–13-0.0516%8 Oct →
nuke7–9-0.079%7 Oct →
nuke1–9-0.206%7 Oct →
inferno3–9-0.115%5 Oct →
nuke9–13-0.105%2 Oct →
vertigo7–9-0.0710%29 Sept →
inferno4–9-0.200%29 Sept →
mirage6–13-0.093%29 Sept →
dust213–100.0518%28 Sept →
ancient9–4-0.0618%28 Sept →
nuke4–9-0.165%26 Sept →
mirage7–13-0.0619%26 Sept →
cache10–13-0.059%26 Sept →
mirage13–8-0.0317%23 Sept →
vertigo3–9-0.1110%22 Sept →
dust28–13-0.1010%20 Sept →
nuke9–13-0.095%20 Sept →
anubis10–13-0.1114%20 Sept →
mirage8–13-0.1314%20 Sept →
nuke10–13-0.1111%20 Sept →
nuke7–13-0.136%19 Sept →
dust210–13-0.034%19 Sept →
mirage3–13-0.0615%17 Sept →
mirage5–13-0.134%15 Sept →
mirage13–8-0.063%15 Sept →
nuke13–7-0.0911%15 Sept →
inferno5–9-0.0710%14 Sept →
nuke13–11-0.040%13 Sept →
mirage1–13-0.0513%13 Sept →
inferno3–13-0.0910%13 Sept →
cache6–13-0.0118%12 Sept →
mirage13–0-0.039%12 Sept →
anubis4–13-0.1311%12 Sept →
mirage13–9-0.086%12 Sept →
mirage13–10-0.123%12 Sept →
nuke13–11-0.0310%12 Sept →
mirage6–13-0.0511%12 Sept →
ancient13–3-0.064%11 Sept →
mirage11–13-0.088%11 Sept →
ancient13–11-0.058%10 Sept →
inferno8–13-0.107%10 Sept →
mirage15–15-0.0612%10 Sept →
inferno7–90.0111%8 Sept →
mirage5–13-0.086%8 Sept →
anubis13–7-0.0213%8 Sept →
train8–9-0.0211%7 Sept →
ancient7–130.0217%7 Sept →
dust29–13-0.097%7 Sept →
nuke4–13-0.053%30 Jul →
inferno3–13-0.0714%30 Jul →
ancient13–8-0.078%30 Jul →
cache13–9-0.045%16 May →
cache13–40.0621%9 May →
cache3–13-0.120%9 May →
ancient13–20.0824%7 Apr →
mirage13–5-0.0712%7 Apr →
mirage10–13-0.0320%19 Mar →
mirage0–9-0.0714%17 Mar →
ancient5–13-0.1015%17 Mar →
anubis10–13-0.0710%17 Mar →
overpass13–11-0.087%17 Mar →
mirage13–7-0.0114%15 Mar →
ancient5–13-0.085%15 Mar →

Match data via Leetify.

Recent teammates

Milestones

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

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