Gu1dotoN

Gu1dotoN — CS2 Stats

76561197960283276[U:1:17548]Steam profile ↗✓ No bans

1,289Tracked matches45%Win rate2020Tracked since
2,843Hours in CS0Hrs last 2 wks
CSDB Rating5.7 SolidSupport
FaceitLevel 9Top 20.7% of ranked FACEIT players
WingmanLegendary Eagle Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 27 Sep 2026 (4 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 1,289 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 25,450 +571 5 May – 1 Jul · 12 days played
24,87926,183peak 26,1835 May1 Jul
26,183Peak Premier in tracked matches
41Days played since 2026-05-05

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

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches1——
Win rate100%——
K/D1.27——
Headshot %71%——

Measured 2 Sep 2026 → 1 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Level 9 among CSDB-tracked players (n=14,327), 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 rate48.6%48.2%50.9%2.3% short
Shot accuracy14.8%13.3%13.8%above
Kill/death ratio1.331.071.09above
Match win rate45.9%46.9%48.4%2.5% short

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

Widest gap: Match win rate. 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.GGGu1dotoNFACEITLevel 9STANDINGTop 20.7% of rankedcsdb.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

Aim72
Positioning60
Utility60

0–100 skill scores via Leetify.

Recent form

STEADY51–44–5Last 10051%Win rateLWWLLWWLWW

Last 10 vs previous 10: +20pp win rate · +0.03 avg rating · +0.6pp headshot accuracy · −45ms 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

  • 2–3 · 40% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 16%
  • Avg reaction 550ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 18%
  • Avg reaction 525ms

Last 20

  • 10–8–2 · 50% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 18%
  • Avg reaction 547ms

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 (+1.1 against its own average).

Aim7.2
Utility6.0
Positioning6.0
Opening Duels3.3
Clutch4.4

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

NiKo

Plays most like NiKo 86% 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 →

CSDB Rating breakdown

Aim7.2
Positioning6.0
Utility6.0
Mechanics5.9
Opening Duels2.4
Win Impact3.3

Composite 5.7/10 (Solid), 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 0.02 → last ⅓ avg 0.02
Reaction time543ms−53ms
first ⅓ avg 596ms → last ⅓ avg 543ms
Headshot accuracy20.1%+3.4%
first ⅓ avg 16.7% → last ⅓ avg 20.1%

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

0.39Best match rating · 9–3 · inferno, 12 Aug →
47%Best headshot accuracy · 3–13 · nuke, 18 Jun →
375msFastest reaction time · 13–10 · anubis, 19 Jun →
13–1Biggest win · anubis, 29 May →

Across the last 100 tracked matches.

Highlights

9Longest win streak
8–8In matches decided by ≤2 rounds
5Overtime games

Map breakdown

nukeBest map · 65% over 17infernoWeakest map · 37% over 19
MapGradePlayedRecordWin rateAvg rating
infernoC197–1237%0.03
anubisA1810–856%0.01
nukeS1711–665%0.05
ancientA138–562%0.00
mirageA116–555%-0.01
cacheC73–443%0.02
overpassA74–357%0.00
train—30–30%0.02
poseidon—20–20%-0.00
dust2—21–150%-0.02
debris—11–0100%0.12

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (37% over 19). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

132,765Lifetime kills
1.33K/D · Top 25% of Level 9 players
4,991Matches
45.9%Match win rate
48.6%Headshot % · Top 50% of Level 9 players
14.8%Shot accuracy · Top 50% of Level 9 players
16,205MVPs
2,616Hours (in match)
7,242Bombs planted
2,344Bombs defused

Most-used weapons

Lifetime map wins

10,344inferno
5,022dust2
3,692nuke
1,995train
1,338vertigo
1,246cbble
141office
78safehouse

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

Faceit stats

Combat

852Matches
52%Win rate
1.26Avg K/D
80.7ADR
42%Headshot %

Clutches & streaks

42%1v1 clutch win
25%1v2 clutch win
12Longest win streak

Recent Faceit resultsWWWLL

MapMatchesWin rateAvg K/DAvg kills
Anubis6253%1.2915.7
Ancient4953%1.2717.4
Inferno3543%1.3017.4
Mirage2941%1.1815.8
Nuke1560%1.3215.7
Cache1050%0.9515.6
Dust21040%1.5518.7
Train425%1.5918.8

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.

17.0%Headshot accuracy
33.1%Accuracy (enemy spotted)
41.6%Spray accuracy
76.7%Counter-strafing
9.7°Preaim
542msReaction time
33.9%T opening success
45.3%CT opening success
0.56Enemies flashed / flash
5.2%Flash assists
9.19HE damage / grenade
13.47Flashes / 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. 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 33.8533% — 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.

37% win rate across 19 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno8–13-0.0517%28 Aug →
cache13–60.0517%28 Aug →
anubis16–140.0413%27 Aug →
mirage8–13-0.0320%24 Aug →
inferno5–13-0.0213%21 Aug →
inferno9–60.0317%21 Aug →
mirage13–90.0115%20 Aug →
nuke3–90.0123%19 Aug →
mirage13–110.0431%17 Aug →
inferno9–30.3918%12 Aug →
train12–120.0414%12 Aug →
anubis13–110.0223%11 Aug →
ancient2–13-0.0311%11 Aug →
cache0–13-0.0218%7 Aug →
nuke16–13-0.0213%7 Aug →
cache13–11-0.0418%6 Aug →
inferno4–13-0.0010%5 Aug →
debris9–00.1238%5 Aug →
nuke8–80.0714%5 Aug →
cache14–160.0421%5 Aug →
ancient9–1-0.0230%5 Aug →
inferno11–130.0819%3 Aug →
inferno7–130.0126%31 Jul →
anubis4–13-0.0219%28 Jul →
ancient11–13-0.0221%28 Jul →
inferno2–9-0.1030%28 Jul →
poseidon8–8-0.0116%28 Jul →
ancient6–130.0120%27 Jul →
poseidon4–9-0.0046%22 Jul →
nuke9–10.1829%21 Jul →
inferno13–8-0.0717%21 Jul →
nuke13–50.0516%17 Jul →
anubis7–13-0.0413%15 Jul →
inferno9–130.0410%15 Jul →
inferno9–60.0132%15 Jul →
mirage5–13-0.0720%15 Jul →
dust213–100.0013%15 Jul →
overpass9–40.0224%13 Jul →
nuke13–11-0.0113%10 Jul →
mirage13–9-0.0413%10 Jul →
anubis14–160.0114%7 Jul →
anubis13–70.0118%1 Jul →
overpass13–60.0720%1 Jul →
inferno11–13-0.016%1 Jul →
anubis13–9-0.0218%1 Jul →
overpass9–13-0.034%30 Jun →
anubis8–130.0722%30 Jun →
inferno7–13-0.0029%30 Jun →
anubis10–13-0.0410%30 Jun →
mirage13–20.0716%24 Jun →
nuke9–00.0927%21 Jun →
nuke9–30.0619%21 Jun →
overpass13–60.0821%20 Jun →
cache13–90.0719%20 Jun →
inferno4–130.0126%20 Jun →
nuke13–80.0725%20 Jun →
dust23–13-0.0538%20 Jun →
ancient13–90.0221%20 Jun →
inferno13–70.0410%20 Jun →
ancient13–60.0515%20 Jun →
anubis13–8-0.0315%19 Jun →
inferno13–20.0427%19 Jun →
mirage13–100.1121%19 Jun →
nuke13–80.0718%19 Jun →
ancient13–7-0.0113%19 Jun →
anubis13–100.0220%19 Jun →
nuke9–13-0.0013%19 Jun →
inferno7–13-0.0117%19 Jun →
train9–130.0121%18 Jun →
train10–130.0218%18 Jun →
nuke3–13-0.0847%18 Jun →
anubis13–10.0829%29 May →
anubis12–120.0117%29 May →
anubis9–13-0.0617%26 May →
inferno7–90.0420%22 May →
nuke13–60.0517%22 May →
inferno13–80.1012%22 May →
nuke13–10.1613%22 May →
nuke6–13-0.0122%20 May →
ancient13–40.0216%20 May →
mirage13–90.0112%20 May →
overpass9–70.017%20 May →
overpass15–15-0.077%19 May →
mirage10–13-0.0218%19 May →
anubis13–80.0017%19 May →
ancient10–13-0.0413%15 May →
mirage7–13-0.0711%15 May →
nuke13–110.0520%15 May →
anubis13–30.119%15 May →
nuke5–80.1132%13 May →
overpass6–13-0.053%13 May →
ancient13–110.0115%13 May →
anubis13–7-0.038%13 May →
cache11–130.0311%10 May →
cache1–130.0519%9 May →
ancient13–100.0215%6 May →
anubis11–130.0719%6 May →
mirage8–13-0.0715%5 May →
ancient13–90.0517%5 May →
ancient9–130.0016%5 May →

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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.