Alberto Stone

Alberto Stone — CS2 Stats

76561197960289849[U:1:24121]Steam profile ↗✓ No bans

659Tracked matches67%Win rate2020Tracked since
618Hours in CS6Hrs last 2 wks
CSDB Rating4.8 DevelopingSupport
FaceitLevel 5 · 1,124 ELOTop 67.6% of ranked FACEIT players
WingmanMaster Guardian Elite
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 17 Sep 2026 (45 days ago). Ranks are recorded once per day this page is viewed.

0Faceit ELO · 1,124 → 1,124
+29Tracked matches · now 659
+6.0ppWin rate · 60.7% → 66.7%

Rating over time

Premier CS Rating: 12,619 +141 16 Mar – 24 Mar · 3 days played
12,32112,619peak 12,61916 Mar24 Mar
Faceit ELO: 1,124 +0 3 Sept – 17 Sept · 2 observations
1,1241,124peak 1,1243 Sept17 Sept
12,619Peak Premier in tracked matches
1,124Highest Faceit ELO seen on CSDB
46Days played since 2026-03-16

Faceit ELO

  • At peak — 1,124
  • Next: Level 6 at 1,201 — 77 to go
  • Reached: Level 5 · Level 4 · Level 3 · Level 2
  • Level 5 first seen 2026-09-03
  • Level 4 first seen 2026-09-03

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.

How this compares with the same rank

Median values for Level 5 among CSDB-tracked players (n=14,283), 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 5 medianLevel 6 medianvs Level 6
Headshot rate58.4%43.8%44.8%above
Shot accuracy7.6%12.0%12.4%4.8% short
Kill/death ratio0.841.021.030.19 short
Match win rate46.6%44.7%45.2%above

This profile matches the typical Level 6 player on 2 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 6 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGAlberto StoneFACEITLevel 5 · 1,124 ELOSTANDINGTop 67.6% of rankedPEAK ELO1,124csdb.gg/stats

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Performance scores

Aim59
Positioning51
Utility54

0–100 skill scores via Leetify.

Recent form

HOT52–46–2Last 10052%Win rateWLWWLWWWWW

Last 10 vs previous 10: +20pp win rate · +0.01 avg rating · −1.6pp headshot accuracy · −8ms reaction

Win rate up 20pp 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

  • 3–2 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 19%
  • Avg reaction 578ms

Last 10

  • 8–2 · 80% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 23%
  • Avg reaction 574ms

Last 20

  • 14–6 · 70% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 24%
  • Avg reaction 578ms

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 (+1.9 against its own average).

Aim5.9
Utility5.4
Positioning5.1
Opening Duels0.6
Clutch3.0

Limited utility dependence

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 77% 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. 569ms 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

Aim5.9
Positioning5.1
Utility5.4
Mechanics4.7
Opening Duels0.7
Win Impact10.0

Composite 4.8/10 (Developing), 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-0.01+0.02
first ⅓ avg -0.03 → last ⅓ avg -0.01
Reaction time584ms−92ms
first ⅓ avg 676ms → last ⅓ avg 584ms
Headshot accuracy25.3%+2.0%
first ⅓ avg 23.3% → last ⅓ avg 25.3%

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

0.13Best match rating · 13–2 · anubis, 19 Jul →
48%Best headshot accuracy · 13–5 · anubis, 21 Jul →
406msFastest reaction time · 10–13 · inferno, 22 Sept →
13–2Biggest win · cache, 18 Oct →

Across the last 100 tracked matches.

Highlights

9Longest win streak
10–10In matches decided by ≤2 rounds
14Overtime games

Map breakdown

anubisBest map · 80% over 20cacheWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
dust2C3013–1743%-0.02
ancientA2012–860%-0.01
anubisS2016–480%-0.02
infernoB136–746%-0.02
cacheD61–517%-0.00
mirageD61–517%-0.04
nukeA53–260%0.02

Across the last 100 tracked matches.

Lifetime stats

15,891Lifetime kills
0.84K/D
972Matches
46.6%Match win rate · Top 50% of Level 5 players
58.4%Headshot % · Top 10% of Level 5 players
7.6%Shot accuracy
2,602MVPs
379Hours (in match)
1,618Bombs planted
211Bombs defused

Most-used weapons

Lifetime map wins

2,704dust2
1,536inferno
423nuke
325cbble
77train
44vertigo
25lake
13office

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

Faceit stats

Combat

202Matches
52%Win rate
0.82Avg K/D
60.4ADR
56%Headshot %

Clutches & streaks

35%1v1 clutch win
19%1v2 clutch win
8Longest win streak

Recent Faceit resultsLWWLW

MapMatchesWin rateAvg K/DAvg kills
Dust23754%0.7711.3
Ancient3364%0.8813.8
Anubis2879%0.9112.4
Inferno2737%0.8912.0
Mirage1436%0.7011.9
Cache50%0.7614.6
Nuke250%1.2620.0

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.

25.6%Headshot accuracy
29.0%Accuracy (enemy spotted)
27.6%Spray accuracy
71.2%Counter-strafing
10.0°Preaim
569msReaction time
30.5%T opening success
35.2%CT opening success
0.55Enemies flashed / flash
7.8%Flash assists
9.10HE damage / grenade
3.76Flashes / 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

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 3.7598 — below the 4 mark we flag

    Grenade Lineups →
  2. 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 30.4631% — below the 40% mark we flag

Spend your practice time on Cache

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

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
ancient13–110.0624%29 Oct →
anubis11–13-0.0614%29 Oct →
inferno13–80.1128%29 Oct →
anubis13–3-0.0413%19 Oct →
ancient8–13-0.0218%19 Oct →
dust213–11-0.0015%19 Oct →
ancient19–17-0.0135%18 Oct →
cache13–20.0935%18 Oct →
dust213–11-0.0130%17 Oct →
inferno13–10-0.0022%17 Oct →
dust213–40.0926%17 Oct →
anubis16–130.0220%17 Oct →
ancient13–90.0224%17 Oct →
anubis13–7-0.0324%16 Oct →
inferno4–13-0.0820%16 Oct →
dust25–130.0024%16 Oct →
anubis16–14-0.0427%15 Oct →
inferno6–13-0.0513%24 Sept →
anubis13–50.0937%24 Sept →
nuke13–16-0.0333%24 Sept →
inferno10–13-0.0735%22 Sept →
dust211–13-0.0918%22 Sept →
mirage18–220.0128%21 Sept →
ancient13–11-0.0511%21 Sept →
dust213–90.0223%21 Sept →
ancient13–7-0.0126%20 Sept →
ancient7–13-0.0730%20 Sept →
dust213–50.0532%20 Sept →
anubis16–130.0135%18 Sept →
dust213–11-0.0338%14 Sept →
dust213–8-0.0817%10 Sept →
cache10–13-0.0228%9 Sept →
ancient13–6-0.0033%9 Sept →
dust210–13-0.0732%9 Sept →
dust25–13-0.0622%8 Sept →
ancient13–10-0.0127%8 Sept →
anubis13–11-0.0345%6 Sept →
anubis13–9-0.0328%6 Sept →
anubis13–70.0527%31 Aug →
ancient10–130.0725%31 Aug →
cache4–13-0.0645%31 Aug →
nuke13–100.0527%30 Aug →
anubis13–11-0.0524%30 Aug →
ancient13–40.0317%30 Aug →
inferno13–80.0725%30 Jul →
nuke8–130.0227%30 Jul →
ancient12–120.0238%30 Jul →
inferno13–100.0034%29 Jul →
nuke6–2-0.0328%29 Jul →
nuke10–00.0820%29 Jul →
inferno4–13-0.0814%28 Jul →
inferno9–1-0.0117%28 Jul →
dust27–13-0.0321%28 Jul →
ancient3–11-0.0524%27 Jul →
dust212–12-0.0810%26 Jul →
mirage2–13-0.0828%26 Jul →
dust213–40.0128%26 Jul →
ancient14–16-0.0538%23 Jul →
anubis13–8-0.0317%23 Jul →
inferno11–13-0.0329%22 Jul →
cache6–130.0338%22 Jul →
anubis8–13-0.0331%22 Jul →
anubis13–50.0348%21 Jul →
dust29–130.0230%19 Jul →
anubis13–20.1338%19 Jul →
dust28–13-0.0529%19 Jul →
dust22–13-0.0833%19 Jul →
dust211–130.0121%18 Jul →
anubis5–13-0.1035%10 Jun →
mirage8–13-0.0631%10 Jun →
anubis16–13-0.0318%8 Jun →
ancient16–130.0018%8 Jun →
dust213–100.0122%7 Jun →
inferno8–13-0.0619%7 Jun →
dust210–13-0.0721%28 May →
dust213–9-0.0224%28 May →
anubis16–14-0.0618%27 May →
dust29–13-0.0719%27 May →
ancient10–13-0.0535%25 May →
ancient6–13-0.1219%6 May →
mirage5–13-0.0718%5 May →
cache9–13-0.0618%5 May →
cache20–220.0130%4 May →
dust25–130.0421%4 May →
dust213–20.0721%30 Apr →
ancient13–9-0.0023%27 Apr →
ancient13–7-0.0329%27 Apr →
inferno11–13-0.0431%26 Apr →
anubis13–6-0.0714%26 Apr →
dust211–13-0.0526%26 Apr →
dust216–19-0.0326%25 Apr →
mirage11–13-0.0227%20 Apr →
dust213–90.0124%20 Apr →
dust211–13-0.0821%20 Apr →
mirage13–7-0.0022%24 Mar →
dust216–13-0.0418%23 Mar →
ancient13–90.0335%22 Mar →
dust28–130.0021%22 Mar →
inferno16–13-0.0324%16 Mar →
anubis9–13-0.0422%16 Mar →

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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