Sheepy

Sheepy — CS2 Stats

76561198053291290[U:1:93025562]Steam profile ↗✓ No bans

2,182Tracked matches50%Win rate2020Tracked since
CSDB Rating3.7 LearningPositional Player
Premier CS Rating14,763Blue band · top ~29.7% of ranked players (population est.)
FaceitLevel 2Top 97.9% of ranked FACEIT players
WingmanGold Nova I
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 28 Sep 2026 (19 days ago). Ranks are recorded once per day this page is viewed.

+386Premier CS Rating · 14,377 → 14,763

Rating over time

Premier CS Rating: 14,763 +5,863 23 Jun – 17 Oct · 36 days played
8,44014,763peak 14,76323 Jun17 Oct
14,763Peak Premier in tracked matches
52Days played since 2026-06-23

Premier CS Rating

  • At peak — 14,763
  • +993 over 30 days · improving
  • +5,189 over 90 days
  • Next: Purple band at 15,000 — 237 to go
  • Reached: Blue band · Light Blue band
  • Blue band first seen 2026-08-28
  • Light Blue band first seen 2026-08-28

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

Share this profile

CSDB.GGSheepyFACEITLevel 2STANDINGTop 97.9% of rankedPREMIER14,763 · Blue bandcsdb.gg/stats

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Performance scores

Aim32
Positioning42
Utility39

0–100 skill scores via Leetify.

Recent form

STEADY41–55–4Last 10041%Win rateWLLLLTLWWW

Last 10 vs previous 10: −30pp win rate · +0.04 avg rating · −2.0pp headshot accuracy · −67ms reaction

Win rate down 30pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.04), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 19%
  • Avg reaction 669ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 21%
  • Avg reaction 634ms

Last 20

  • 11–7–2 · 55% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 22%
  • Avg reaction 667ms

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 (+1.5 against its own average).

Aim3.2
Utility3.9
Positioning4.2
Opening Duels1.6
Clutch1.0

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

donk

Plays most like donk 72% 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. 672ms 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

Aim3.2
Positioning4.2
Utility3.9
Mechanics5.3
Opening Duels2.1
Win Impact5.0

Composite 3.7/10 (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-0.02+0.01
first ⅓ avg -0.03 → last ⅓ avg -0.02
Reaction time673ms+36ms
first ⅓ avg 637ms → last ⅓ avg 673ms
Headshot accuracy22.3%+2.7%
first ⅓ avg 19.6% → last ⅓ avg 22.3%

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

0.29Best match rating · 4–0 · inferno, 21 Sept →
50%Best headshot accuracy · 6–13 · nuke, 5 Jul →
492msFastest reaction time · 9–13 · office, 10 Jul →
13–2Biggest win · cache, 11 Aug →

Across the last 100 tracked matches.

Highlights

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

Map breakdown

ancientBest map · 69% over 13vertigoWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
cacheC188–1044%-0.03
nukeD173–1418%-0.04
infernoC167–944%-0.00
anubisB158–753%-0.03
ancientS139–469%-0.04
vertigoD61–517%-0.04
overpassA53–260%-0.04
dust2—40–40%-0.05
mirage—32–167%-0.06
train—20–20%0.04
office—10–10%-0.01

Across the last 100 tracked matches.

Vertigo is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Vertigo lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

176Matches
47%Win rate
0.74Avg K/D
58.5ADR
46%Headshot %

Clutches & streaks

25%1v1 clutch win
17%1v2 clutch win
7Longest win streak

Recent Faceit resultsWLWLL

MapMatchesWin rateAvg K/DAvg kills
Inferno2556%0.7711.6
Ancient1839%0.6711.8
Anubis1567%0.6611.1
Overpass1560%0.8312.5
Mirage1338%0.6212.1
Nuke667%0.629.7
Dust2333%0.619.3
Train367%0.7211.7

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.

22.2%Headshot accuracy
29.8%Accuracy (enemy spotted)
27.1%Spray accuracy
74.0%Counter-strafing
14.8°Preaim
672msReaction time
34.9%T opening success
42.1%CT opening success
0.64Enemies flashed / flash
6.9%Flash assists
4.66HE damage / grenade
2.16Flashes / 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

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 14.7519° — above the 12° mark we flag

    Aim Training →
  2. Grenades & Utility

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

    Flashes per match 2.1606 — below the 4 mark we flag

    Grenade Lineups →
Spend your practice time on Vertigo

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.

Vertigo callouts & strategy →Vertigo grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache13–9-0.0018%17 Oct →
vertigo7–13-0.0324%28 Sept →
vertigo5–13-0.0220%28 Sept →
nuke9–13-0.0521%28 Sept →
vertigo10–13-0.0612%26 Sept →
vertigo12–12-0.0716%26 Sept →
dust27–13-0.0714%26 Sept →
inferno13–90.0627%21 Sept →
inferno4–00.2932%21 Sept →
cache13–90.0127%17 Sept →
ancient13–8-0.0022%17 Sept →
cache9–13-0.0828%28 Aug →
nuke4–13-0.1014%28 Aug →
ancient13–8-0.0830%28 Aug →
cache13–5-0.0313%26 Aug →
inferno13–6-0.0139%26 Aug →
nuke13–10-0.0319%25 Aug →
cache13–7-0.0421%24 Aug →
cache13–9-0.0417%18 Aug →
train12–120.0725%16 Aug →
train8–130.0120%16 Aug →
cache13–20.0033%11 Aug →
inferno8–13-0.0621%11 Aug →
nuke2–13-0.0724%7 Aug →
inferno2–13-0.0821%7 Aug →
ancient13–10-0.0429%6 Aug →
anubis7–13-0.0529%5 Aug →
inferno16–14-0.0221%5 Aug →
cache8–13-0.0522%1 Aug →
ancient6–13-0.0216%1 Aug →
anubis13–10-0.0226%31 Jul →
vertigo13–9-0.0219%30 Jul →
anubis13–110.0314%30 Jul →
ancient13–10-0.1024%30 Jul →
vertigo12–12-0.0328%29 Jul →
anubis13–100.0128%29 Jul →
cache7–13-0.0224%29 Jul →
anubis9–13-0.0616%28 Jul →
cache7–13-0.0813%27 Jul →
cache10–13-0.0114%27 Jul →
ancient11–13-0.0639%26 Jul →
anubis16–14-0.0516%26 Jul →
inferno13–90.0327%25 Jul →
anubis13–9-0.0324%25 Jul →
mirage14–16-0.0918%24 Jul →
anubis7–13-0.0317%24 Jul →
nuke6–13-0.0516%23 Jul →
anubis8–13-0.0342%23 Jul →
inferno13–7-0.0039%22 Jul →
cache7–13-0.0723%22 Jul →
nuke6–13-0.1221%21 Jul →
overpass13–8-0.034%19 Jul →
inferno13–100.0220%18 Jul →
cache13–8-0.0417%17 Jul →
cache9–13-0.0618%17 Jul →
nuke14–16-0.0719%15 Jul →
cache13–5-0.0131%14 Jul →
mirage13–11-0.0541%13 Jul →
anubis7–13-0.0714%13 Jul →
ancient13–10-0.0421%13 Jul →
ancient13–7-0.0112%12 Jul →
cache8–13-0.0326%11 Jul →
office9–13-0.0136%10 Jul →
ancient13–6-0.0023%9 Jul →
nuke6–13-0.0617%9 Jul →
inferno11–13-0.0436%9 Jul →
cache11–13-0.0126%8 Jul →
cache12–120.0131%7 Jul →
inferno7–13-0.0513%6 Jul →
nuke13–9-0.0315%6 Jul →
overpass13–8-0.0529%6 Jul →
ancient13–90.0220%5 Jul →
nuke6–13-0.0750%5 Jul →
ancient5–13-0.0629%4 Jul →
anubis13–110.0130%4 Jul →
inferno5–13-0.0213%4 Jul →
nuke10–13-0.059%4 Jul →
overpass11–13-0.0319%3 Jul →
inferno7–13-0.0629%3 Jul →
nuke2–130.0611%2 Jul →
overpass4–13-0.0614%1 Jul →
anubis13–11-0.0036%30 Jun →
ancient5–13-0.0714%29 Jun →
dust29–13-0.0319%29 Jun →
overpass13–10-0.0113%29 Jun →
inferno4–13-0.0622%27 Jun →
dust25–13-0.0914%27 Jun →
dust213–16-0.0323%27 Jun →
nuke5–13-0.0416%27 Jun →
nuke13–80.0210%26 Jun →
inferno4–13-0.0430%25 Jun →
anubis10–13-0.0714%25 Jun →
nuke3–13-0.044%25 Jun →
anubis13–110.0211%24 Jun →
ancient13–8-0.0314%24 Jun →
nuke5–13-0.0317%24 Jun →
mirage6–3-0.047%24 Jun →
inferno13–16-0.0326%23 Jun →
anubis4–13-0.0518%23 Jun →
nuke9–130.0227%23 Jun →

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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