Cyborg

Cyborg — CS2 Stats

76561198160345977[U:1:200080249]Steam profile ↗✓ No bans

220Tracked matches68%Win rate2022Tracked since
1,095Hours in CS
CSDB Rating3.4 LearningPositional Player
Premier CS Rating14,514Blue band · top ~31% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 19 Apr 2026 (180 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: 14,514 +12,115 13 Nov – 19 Apr · 7 days played
2,39914,514peak 14,51413 Nov19 Apr
14,546Peak Premier in tracked matches
20Days played since 2023-09-23

Premier CS Rating

  • At peak — 14,514
  • Next: Purple band at 15,000 — 486 to go
  • Reached: 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 Blue band among CSDB-tracked players (n=21,222), 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 playerBlue band medianPurple band medianvs Purple band
Headshot rate38.7%42.0%44.3%5.6% short
Shot accuracy19.8%9.6%11.9%above
Kill/death ratio1.330.981.03above
Match win rate36.2%43.8%45.2%9.0% short

This profile matches the typical Purple band player on 2 of 4 comparable metrics.

Widest gap: Match win rate. That is the metric furthest from the Purple band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGCyborgPREMIER14,514 · Blue bandcsdb.gg/stats

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Performance scores

Aim30
Positioning31
Utility25

0–100 skill scores via Leetify.

Recent form

HOT54–40–6Last 10054%Win rateWLWWTWWWLW

Last 10 vs previous 10: 0pp win rate · −0.04 avg rating · +1.9pp headshot accuracy · −26ms 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

  • 3–1–1 · 60% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 13%
  • Avg reaction 742ms

Last 10

  • 7–2–1 · 70% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 15%
  • Avg reaction 680ms

Last 20

  • 14–4–2 · 70% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 15%
  • Avg reaction 693ms

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 (+1.2 against its own average).

Aim3.0
Utility2.5
Positioning3.1
Opening Duels0.0

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

ZywOo

Plays most like ZywOo 80% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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. 679ms 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

Aim3.0
Positioning3.1
Utility2.5
Mechanics4.6
Opening Duels0.3
Win Impact10.0

Composite 3.4/10 (Learning), 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-0.04−0.01
first ⅓ avg -0.03 → last ⅓ avg -0.04
Reaction time668ms−2ms
first ⅓ avg 670ms → last ⅓ avg 668ms
Headshot accuracy13.9%−2.0%
first ⅓ avg 15.9% → last ⅓ avg 13.9%

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 · 13–10 · inferno, 17 May →
30%Best headshot accuracy · 11–13 · dust2, 5 Aug →
313msFastest reaction time · 4–13 · inferno, 15 Mar →
13–1Biggest win · anubis, 15 Mar →

Across the last 100 tracked matches.

Highlights

9Longest win streak
8–4In matches decided by ≤2 rounds
4Overtime games

Map breakdown

overpassBest map · 88% over 8infernoWeakest map · 30% over 10
MapGradePlayedRecordWin rateAvg rating
mirageA2715–1256%-0.03
dust2B189–950%-0.04
anubisA117–464%-0.03
nukeC114–736%-0.03
infernoD103–730%-0.03
ancientB105–550%-0.01
overpassS87–188%-0.03
vertigo—43–175%-0.02
thera—11–0100%-0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

89,218Lifetime kills
1.33K/D · Top 10% of Blue band
4,053Matches
36.2%Match win rate
38.7%Headshot %
19.8%Shot accuracy · Top 5% of Blue band
9,293MVPs
1,095Hours (in match)
1,732Bombs planted
451Bombs defused

Most-used weapons

AK-4719,745
AWP14,076
P2503,535
SSG 083,250
Tec-91,627

Lifetime map wins

11,291dust2
2,553inferno
726nuke
403cbble
241vertigo
178train
95lake
67office

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

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

14.1%Headshot accuracy
27.4%Accuracy (enemy spotted)
30.5%Spray accuracy
70.5%Counter-strafing
10.5°Preaim
679msReaction time
19.6%T opening success
32.5%CT opening success
0.39Enemies flashed / flash
1.6%Flash assists
7.86HE damage / grenade
2.25Flashes / 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 14.1019% — 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 0.3906 — 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 19.6281% — 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.

30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
overpass13–10-0.0416%19 Apr →
anubis10–13-0.0614%19 Apr →
dust213–10-0.0513%12 Apr →
inferno13–2-0.0717%12 Apr →
dust212–12-0.077%12 Apr →
mirage13–11-0.0520%12 Apr →
mirage13–6-0.0129%12 Apr →
anubis13–6-0.0323%12 Apr →
dust25–13-0.130%29 Mar →
nuke13–7-0.0716%29 Mar →
mirage13–8-0.0318%29 Mar →
mirage13–11-0.039%29 Mar →
mirage13–40.0211%29 Mar →
nuke9–13-0.0614%29 Mar →
dust212–12-0.0415%29 Mar →
nuke16–140.0416%28 Mar →
mirage13–8-0.0111%28 Mar →
inferno9–13-0.048%28 Mar →
overpass13–8-0.0218%28 Mar →
mirage13–50.0316%28 Mar →
dust213–5-0.039%28 Mar →
dust25–13-0.0617%23 Mar →
overpass13–2-0.0621%22 Mar →
dust22–13-0.0814%22 Mar →
mirage6–13-0.0510%22 Mar →
anubis10–3-0.100%22 Mar →
inferno9–13-0.0623%22 Mar →
anubis13–8-0.059%22 Mar →
nuke13–9-0.0010%22 Mar →
mirage10–13-0.0415%22 Mar →
ancient9–13-0.0416%22 Mar →
overpass13–4-0.0013%22 Mar →
mirage12–12-0.0610%22 Mar →
dust213–8-0.0227%22 Mar →
inferno13–11-0.069%22 Mar →
overpass9–20.0113%15 Mar →
overpass13–30.0010%15 Mar →
dust213–20.067%15 Mar →
anubis13–1-0.0117%15 Mar →
inferno4–13-0.058%15 Mar →
nuke4–13-0.0715%15 Mar →
mirage3–13-0.089%15 Mar →
nuke5–13-0.057%15 Mar →
mirage1–13-0.0610%15 Mar →
dust213–9-0.0318%15 Mar →
inferno13–100.0819%17 May →
anubis8–13-0.068%10 Nov →
ancient5–13-0.109%10 Nov →
dust213–10-0.0511%10 Nov →
vertigo13–7-0.0518%29 Oct →
thera13–11-0.0521%29 Oct →
mirage13–3-0.0217%29 Oct →
mirage6–13-0.0420%6 Aug →
inferno4–4-0.0227%6 Aug →
nuke7–130.0410%6 Aug →
dust211–13-0.0330%5 Aug →
anubis6–13-0.0818%5 Aug →
mirage13–50.0811%5 Aug →
anubis13–60.0620%4 Aug →
nuke13–60.0416%4 Aug →
vertigo13–11-0.0221%4 Aug →
mirage13–40.0728%4 Aug →
ancient8–13-0.0122%4 Aug →
dust25–13-0.0619%3 Aug →
nuke11–13-0.0318%3 Aug →
ancient12–12-0.0210%3 Aug →
mirage10–13-0.0522%3 Aug →
mirage13–80.0516%3 Aug →
dust213–8-0.053%27 Jul →
nuke10–13-0.1014%27 Jul →
dust215–15-0.0419%27 Jul →
inferno8–13-0.0728%27 Jul →
ancient16–14-0.0112%20 Jul →
inferno8–13-0.0614%20 Jul →
mirage6–13-0.0930%20 Jul →
mirage13–5-0.0615%20 Jul →
dust215–15-0.018%20 Jul →
nuke4–11-0.0913%20 Jul →
mirage2–13-0.0115%20 Jul →
dust213–6-0.0819%20 Jul →
mirage13–10-0.0222%13 Nov →
ancient11–130.005%13 Nov →
mirage13–9-0.0019%13 Nov →
mirage10–13-0.0714%13 Nov →
dust213–70.0016%12 Nov →
mirage9–13-0.1024%24 Sept →
vertigo6–130.0214%23 Sept →
overpass0–13-0.1114%23 Sept →
mirage3–13-0.0814%23 Sept →
anubis10–13-0.0116%23 Sept →
inferno6–13-0.0129%23 Sept →
vertigo8–7-0.067%23 Sept →
overpass13–10-0.0115%23 Sept →
mirage13–60.0220%23 Sept →
anubis13–8-0.0514%23 Sept →
anubis13–80.0514%23 Sept →
ancient13–5-0.0212%23 Sept →
ancient13–30.0312%23 Sept →
ancient13–30.058%23 Sept →
ancient11–10.0630%23 Sept →

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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