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Cyber_Papa

Cyber_Papa — CS2 Stats

76561198096230076[U:1:135964348]Steam profile ↗✓ No bans

1,366Tracked matches41%Win rate2020Tracked since
CSDB Rating4.4 Developing
Premier CS Rating16,434Purple band · top ~22.7% of ranked players (population est.)
CSDB Leaderboard#21615 of 38391 tracked
FaceitLevel 5Top 67.6% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGCyber_PapaFACEITLevel 5STANDINGTop 67.6% of rankedPREMIER16,434 · Purple bandcsdb.gg/stats

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Performance scores

Aim50
Positioning44
Utility64

0–100 skill scores via Leetify.

Recent form

STEADY44–51–5Last 10044%Win rateLLWWLWLLWL

Last 10 vs previous 10: +0pp win rate · +0.00 avg rating

Player DNA

Aim5.0
Aggression5.2
Utility6.4
Positioning4.4
Opening Duels2.3
Clutch3.4

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

NiKo

Plays most like NiKo 86% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

Where you differ: lower positioning profile; 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

T-side openings. Opening success drops from 47% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 660ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 70% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim5.0
Positioning4.4
Utility6.4
Mechanics4.4
Opening Duels2.3
Win Impact2.1

Composite 4.4/10 (Developing), 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 rating-0.02−0.00
first ⅓ avg -0.02 → last ⅓ avg -0.02
Reaction time668ms−65ms
first ⅓ avg 734ms → last ⅓ avg 668ms
Headshot accuracy11.6%−4.9%
first ⅓ avg 16.5% → last ⅓ avg 11.6%

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.

Highlights

0.15Best rating — mirage 13–9
13–1Biggest win — vertigo
4Longest win streak
L2Current streak
6–8In matches decided by ≤2 rounds
8Overtime games

Map breakdown

dust2Best map · 54% over 26infernoWeakest map · 24% over 21
MapGradePlayedRecordWin rateAvg rating
dust2B2614–1254%-0.00
infernoD215–1624%-0.04
ancientC156–940%-0.02
mirageB147–750%-0.00
overpassC104–640%-0.02
anubisC52–340%-0.03
nuke—32–167%-0.04
cache—32–167%-0.04
vertigo—22–0100%-0.01
train—10–10%-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (24% over 21). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,060Matches
49%Win rate
0.87Avg K/D
81.7ADR
40%Headshot %

Clutches & streaks

37%1v1 clutch win
19%1v2 clutch win
8Longest win streak

Recent Faceit resultsLWWLL

MapMatchesWin rateAvg K/DAvg kills
Dust218755%0.9715.4
Inferno13551%0.8413.8
Mirage8345%0.9915.1
Anubis7946%0.8113.9
Ancient4732%0.7713.0
Nuke2075%0.8715.6
Vertigo1030%0.7212.5
Overpass633%0.6812.7

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.

12.2%Headshot accuracy
36.4%Accuracy (enemy spotted)
34.0%Spray accuracy
69.9%Counter-strafing
9.3°Preaim
660msReaction time
31.6%T opening success
46.8%CT opening success
0.71Enemies flashed / flash
6.2%Flash assists
9.07HE damage / grenade
9.39Flashes / 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 12.1562% — below the 15% mark we flag

    Aim Training →
  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 31.553% — 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.

24% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage11–13-0.088%20 Aug →
ancient8–130.0910%20 Aug →
mirage13–5-0.0127%20 Aug →
mirage4–00.095%20 Aug →
nuke10–13-0.0325%19 Aug →
nuke13–10-0.112%9 Aug →
dust25–130.0418%23 Jul →
inferno8–13-0.0611%23 Jul →
cache13–8-0.0313%22 Jul →
dust25–13-0.0117%22 Jul →
inferno13–50.044%22 Jul →
inferno10–13-0.0414%22 Jul →
cache6–13-0.046%22 Jul →
dust213–10-0.0213%22 Jul →
dust26–13-0.038%22 Jul →
ancient13–5-0.0112%22 Jul →
dust210–13-0.067%22 Jul →
ancient11–130.015%22 Jul →
ancient13–70.0615%21 Jul →
inferno7–13-0.0113%21 Jul →
inferno7–13-0.0710%20 Jul →
dust213–4-0.0827%20 Jul →
dust29–130.0113%11 Jul →
inferno4–13-0.015%10 Jul →
ancient13–100.0513%10 Jul →
inferno8–13-0.0612%10 Jul →
dust213–70.0212%10 Jul →
anubis5–13-0.1011%10 Jul →
dust215–15-0.0314%10 Jul →
dust213–3-0.0414%10 Jul →
ancient9–13-0.0212%9 Jul →
cache13–11-0.062%9 Jul →
mirage11–13-0.087%9 Jul →
dust26–130.0512%9 Jul →
mirage6–13-0.049%9 Jul →
dust216–13-0.0210%9 Jul →
anubis13–100.0313%8 Jul →
anubis13–90.0415%6 Jul →
ancient11–13-0.098%6 Jul →
anubis2–13-0.100%6 Jul →
ancient10–13-0.0318%6 Jul →
inferno13–9-0.0913%5 Jul →
ancient13–8-0.0619%5 Jul →
inferno15–15-0.066%4 Jul →
ancient12–16-0.0713%4 Jul →
mirage5–13-0.0215%4 Jul →
anubis15–15-0.0410%4 Jul →
dust213–100.0417%4 Jul →
inferno15–150.0113%27 Jun →
inferno9–13-0.0413%27 Jun →
dust213–70.0324%27 Jun →
dust24–13-0.0813%20 Jun →
inferno13–9-0.0316%20 Jun →
dust213–110.0320%20 Jun →
inferno9–13-0.0113%20 Jun →
overpass13–70.0220%20 Jun →
dust212–120.0518%26 Feb →
ancient5–13-0.0617%4 Feb →
mirage13–10-0.0510%2 Feb →
mirage13–80.0125%22 Jan →
dust213–60.1025%25 Dec →
train11–13-0.0121%3 Dec →
inferno13–6-0.1019%20 Nov →
dust28–13-0.0626%29 Oct →
ancient10–13-0.0711%28 Oct →
inferno10–130.0221%28 Oct →
mirage13–90.1523%26 Oct →
vertigo13–9-0.0412%26 Oct →
vertigo13–10.0216%26 Oct →
inferno6–13-0.0419%25 Oct →
inferno1–13-0.0617%12 Sept →
dust213–90.0426%6 Sept →
inferno13–6-0.0114%6 Sept →
overpass6–13-0.037%5 Sept →
inferno11–13-0.0713%4 Sept →
overpass4–13-0.0812%3 Sept →
dust210–130.0216%3 Sept →
ancient13–100.0310%3 Sept →
overpass6–13-0.0548%29 Aug →
mirage9–130.0617%21 Aug →
ancient13–10-0.0411%21 Aug →
dust213–110.0025%20 Aug →
nuke16–130.0018%20 Aug →
overpass13–100.0317%13 Aug →
overpass11–13-0.0414%13 Aug →
overpass13–110.0321%13 Aug →
mirage13–11-0.0115%9 Aug →
ancient6–13-0.0615%8 Aug →
dust213–110.0121%8 Aug →
inferno2–13-0.095%7 Aug →
mirage14–16-0.0426%7 Aug →
dust23–13-0.0720%29 Jul →
mirage13–7-0.0116%29 Jul →
mirage10–13-0.009%27 Jul →
overpass9–130.0316%27 Jul →
overpass9–13-0.0319%27 Jul →
dust213–40.0213%26 Jul →
inferno8–13-0.056%26 Jul →
overpass13–7-0.0518%25 Jul →
dust213–6-0.0417%24 Jul →

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 →

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