Sepi

Sepi — CS2 Stats

PE76561198052284227[U:1:92018499]Steam profile ↗✓ No bans

4,355Tracked matches50%Win rate2020Tracked since
CSDB Rating6.5 SolidPositional Player
FaceitLevel 5Top 67.6% of ranked FACEIT players
WingmanMaster Guardian II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 23 Sep 2026 (45 days ago). Ranks are recorded once per day this page is viewed.

+104Tracked matches · now 4,355
+6.5ppWin rate · 43.5% → 50.0%

Rating over time

30Days played since 2026-08-28

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.

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CSDB.GGSepiFACEITLevel 5STANDINGTop 67.6% of rankedcsdb.gg/stats

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Performance scores

Aim66
Positioning66
Utility64

0–100 skill scores via Leetify.

Recent form

COLD40–45–15Last 10040%Win rateWLLLLLTTTL

Last 10 vs previous 10: −60pp win rate · −0.04 avg rating · −5.8pp headshot accuracy · +72ms reaction

Win rate down 60pp 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

  • 1–4 · 20% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 648ms

Last 10

  • 1–6–3 · 10% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 13%
  • Avg reaction 602ms

Last 20

  • 8–9–3 · 40% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 16%
  • Avg reaction 566ms

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 (+1.8 against its own average).

Aim6.6
Utility6.4
Positioning6.6
Opening Duels6.0
Clutch0.0

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

device

Plays most like device 82% playstyle similarity

Most alike: positioning profile, utility contribution.

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

Strengths

T openings. 71% T opening-duel success — entries that actually open the round.

Areas to improve

CT openings. Opening success drops from 71% on T to 49% on CT — first contacts on the defending side are being lost.

Reaction time. 560ms 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

Aim6.6
Positioning6.6
Utility6.4
Mechanics6.8
Opening Duels7.3
Win Impact5.0

Composite 6.5/10 (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 rating0.01+0.02
first ⅓ avg -0.01 → last ⅓ avg 0.01
Reaction time564ms−20ms
first ⅓ avg 584ms → last ⅓ avg 564ms
Headshot accuracy14.8%−0.5%
first ⅓ avg 15.4% → last ⅓ avg 14.8%

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

0.17Best match rating · 5–0 · dust2, 3 Nov →
36%Best headshot accuracy · 5–0 · dust2, 3 Nov →
422msFastest reaction time · 13–11 · ancient, 30 Sept →
13–0Biggest win · mirage, 21 Oct →

Across the last 100 tracked matches.

Highlights

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

Map breakdown

infernoBest map · 62% over 13trainWeakest map · 0% over 5
MapGradePlayedRecordWin rateAvg rating
nukeA2011–955%0.03
dust2B199–1047%-0.01
mirageD134–931%-0.03
infernoA138–562%-0.01
cacheD123–925%-0.02
ancientD103–730%0.02
anubisD82–625%-0.01
trainD50–50%-0.02

Across the last 100 tracked matches.

Faceit stats

Combat

101Matches
49%Win rate
1.05Avg K/D
67.8ADR
44%Headshot %

Clutches & streaks

0%1v1 clutch win
0%1v2 clutch win
6Longest win streak

Recent Faceit resultsLLWLL

MapMatchesWin rateAvg K/DAvg kills
Vertigo1354%1.0115.2
Mirage650%0.7814.5
Nuke560%1.1216.4
Anubis40%1.0320.0
Ancient475%2.1714.8
Overpass3100%1.5913.7
Office1100%1.0013.0
Inferno1100%1.4320.0

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.

13.8%Headshot accuracy
31.6%Accuracy (enemy spotted)
33.9%Spray accuracy
80.5%Counter-strafing
8.2°Preaim
560msReaction time
71.1%T opening success
48.6%CT opening success
0.57Enemies flashed / flash
5.4%Flash assists
9.85HE damage / grenade
14.21Flashes / 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 13.7934% — below the 15% mark we flag

    Aim Training →
Spend your practice time on Train

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

0% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
nuke13–30.127%7 Nov →
mirage0–13-0.1022%7 Nov →
dust27–13-0.0315%7 Nov →
ancient4–130.008%7 Nov →
train8–13-0.0215%7 Nov →
cache8–13-0.0815%7 Nov →
inferno12–12-0.0115%6 Nov →
nuke8–8-0.089%6 Nov →
mirage12–12-0.015%4 Nov →
inferno11–130.0117%4 Nov →
nuke13–7-0.0417%4 Nov →
anubis9–130.0312%4 Nov →
mirage4–00.0133%4 Nov →
dust25–00.1736%3 Nov →
cache13–10-0.0016%3 Nov →
mirage3–13-0.117%3 Nov →
inferno13–11-0.0118%3 Nov →
nuke13–20.107%2 Nov →
dust213–70.0023%2 Nov →
nuke8–130.0916%29 Oct →
inferno10–13-0.0310%29 Oct →
anubis13–10-0.0015%29 Oct →
dust213–5-0.007%28 Oct →
train12–120.0215%28 Oct →
nuke13–7-0.0315%28 Oct →
anubis10–13-0.0511%28 Oct →
inferno13–90.0811%28 Oct →
mirage11–13-0.0411%28 Oct →
dust213–90.0419%27 Oct →
ancient12–12-0.0013%27 Oct →
cache7–13-0.0212%27 Oct →
nuke13–10.1523%27 Oct →
anubis13–30.0714%27 Oct →
dust212–12-0.0711%26 Oct →
inferno13–7-0.0111%26 Oct →
nuke13–110.0517%24 Oct →
anubis6–13-0.024%24 Oct →
nuke2–13-0.0814%24 Oct →
dust213–60.0319%23 Oct →
nuke13–80.0119%22 Oct →
cache12–12-0.1011%22 Oct →
ancient12–120.0414%22 Oct →
dust213–5-0.0721%22 Oct →
inferno13–90.0021%21 Oct →
mirage13–90.0126%21 Oct →
mirage13–00.1317%21 Oct →
inferno13–4-0.0110%21 Oct →
nuke13–40.1119%21 Oct →
nuke12–120.0424%21 Oct →
dust213–0-0.0226%20 Oct →
cache11–130.0218%20 Oct →
ancient12–12-0.0110%17 Oct →
nuke11–130.0416%17 Oct →
dust213–90.0211%17 Oct →
mirage11–13-0.0216%17 Oct →
inferno13–3-0.0118%17 Oct →
nuke8–13-0.0415%16 Oct →
cache7–13-0.0113%16 Oct →
nuke12–120.0118%14 Oct →
ancient4–13-0.0212%14 Oct →
mirage13–11-0.069%14 Oct →
anubis9–13-0.039%13 Oct →
cache6–1-0.015%13 Oct →
dust28–13-0.0518%13 Oct →
inferno3–13-0.126%13 Oct →
nuke6–13-0.0518%13 Oct →
mirage6–13-0.0618%13 Oct →
train8–13-0.059%13 Oct →
cache11–13-0.0012%12 Oct →
dust212–12-0.0112%12 Oct →
nuke13–110.0317%10 Oct →
mirage12–12-0.0517%10 Oct →
cache13–60.019%10 Oct →
ancient13–110.0120%9 Oct →
dust29–13-0.0713%9 Oct →
nuke12–12-0.0216%9 Oct →
ancient3–130.0113%9 Oct →
anubis3–13-0.0322%9 Oct →
train11–130.0112%8 Oct →
cache6–13-0.0718%8 Oct →
dust23–13-0.0233%8 Oct →
inferno13–4-0.0626%7 Oct →
train5–13-0.0518%7 Oct →
dust24–13-0.109%7 Oct →
dust25–130.009%7 Oct →
nuke13–100.1317%6 Oct →
cache4–130.0016%6 Oct →
inferno4–130.0715%3 Oct →
mirage0–13-0.070%3 Oct →
dust213–10-0.016%3 Oct →
ancient13–80.0717%2 Oct →
nuke13–40.0118%2 Oct →
anubis6–13-0.0426%1 Oct →
mirage8–13-0.077%1 Oct →
dust23–13-0.0525%1 Oct →
cache10–13-0.0212%1 Oct →
ancient13–110.0611%30 Sept →
dust212–120.0113%28 Sept →
ancient9–130.0122%28 Sept →
inferno13–8-0.0217%27 Sept →

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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