beppu

beppu — CS2 Stats

US76561199471570877[U:1:1511305149]Steam profile ↗✓ No bans

1,385Tracked matches40%Win rate2024Tracked since
977Hours in CS22Hrs last 2 wks
CSDB Rating4.5 DevelopingPositional Player
FaceitLevel 5Top 67.6% of ranked FACEIT players
WingmanGold Nova II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Aug 2026 (47 days ago). Ranks are recorded once per day this page is viewed.

+55Tracked matches · now 1,385
−8.3ppWin rate · 48.3% → 40.0%

Rating over time

52Days played since 2026-05-18

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

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches47——
Win rate40%——
K/D0.97——
Headshot %42%——

Measured 15 Sep 2026 → 16 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 5 among CSDB-tracked players (n=13,918), 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 5 medianLevel 6 medianvs Level 6
Headshot rate48.6%43.7%44.8%above
Shot accuracy0.0%12.0%12.4%12.4% short
Kill/death ratio1.151.021.03above
Match win rate46.9%44.7%45.2%above

This profile matches the typical Level 6 player on 3 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 6 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGbeppuFACEITLevel 5STANDINGTop 67.6% 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

Aim58
Positioning52
Utility34

0–100 skill scores via Leetify.

Recent form

STEADY44–47–9Last 10044%Win rateWLWWWWLLWL

Last 10 vs previous 10: +40pp win rate · +0.02 avg rating · +1.1pp headshot accuracy · +53ms reaction

Win rate up 40pp 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

  • 4–1 · 80% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 13%
  • Avg reaction 622ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 14%
  • Avg reaction 671ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 14%
  • Avg reaction 645ms

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 (+2.6 against its own average).

Aim5.8
Utility3.4
Positioning5.2
Opening Duels2.0
Clutch0.0

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

iM

Plays most like iM 87% 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. 636ms 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

Aim5.8
Positioning5.2
Utility3.4
Mechanics4.8
Opening Duels3.0
Win Impact1.7

Composite 4.5/10 (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 rating0.00+0.00
first ⅓ avg -0.00 → last ⅓ avg 0.00
Reaction time636ms−100ms
first ⅓ avg 735ms → last ⅓ avg 636ms
Headshot accuracy15.5%−0.3%
first ⅓ avg 15.8% → last ⅓ avg 15.5%

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

0.19Best match rating · 13–5 · anubis, 14 Oct →
43%Best headshot accuracy · 9–13 · office, 2 Aug →
438msFastest reaction time · 6–9 · inferno, 27 Sept →
13–1Biggest win · overpass, 16 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
6–5In matches decided by ≤2 rounds

Map breakdown

mirageBest map · 58% over 12infernoWeakest map · 30% over 20
MapGradePlayedRecordWin rateAvg rating
dust2C229–1341%0.01
infernoD206–1430%-0.03
nukeB1910–953%-0.00
mirageA127–558%-0.00
cacheD93–633%0.01
anubis—41–325%0.04
train—42–250%0.01
ancient—42–250%-0.00
vertigo—32–167%-0.02
overpass—22–0100%0.08
office—10–10%0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (30% over 20). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

23,364Lifetime kills
1.15K/D · Top 25% of Level 5 players
1,377Matches
46.9%Match win rate · Top 50% of Level 5 players
48.6%Headshot % · Top 50% of Level 5 players
0.0%Shot accuracy
2,992MVPs
449Hours (in match)
1,461Bombs planted
326Bombs defused

Most-used weapons

Lifetime map wins

2,168inferno
2,134nuke
1,520dust2
1,178vertigo
710office
426train
44italy
2ar_shoots

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

Faceit stats

Combat

13Matches
54%Win rate
0.90Avg K/D
68.9ADR
29%Headshot %

Clutches & streaks

0%1v1 clutch win
10%1v2 clutch win
3Longest win streak

Recent Faceit resultsWWWLL

MapMatchesWin rateAvg K/DAvg kills
Ancient450%0.8814.0
Vertigo367%0.9012.7
Mirage333%0.7310.3
Anubis250%1.2414.0
Inferno1100%0.8511.0

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.

15.7%Headshot accuracy
35.9%Accuracy (enemy spotted)
39.9%Spray accuracy
71.5%Counter-strafing
10.6°Preaim
636msReaction time
41.5%T opening success
42.4%CT opening success
0.48Enemies flashed / flash
6.0%Flash assists
8.69HE damage / grenade
4.06Flashes / 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. 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 0.4775 — below the 0.5 mark we flag

    Grenade Lineups →
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 20 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
overpass13–10.0110%16 Oct →
cache11–130.0421%16 Oct →
dust213–80.0312%15 Oct →
nuke13–100.0116%15 Oct →
nuke13–60.056%15 Oct →
inferno7–4-0.0318%14 Oct →
inferno3–9-0.139%14 Oct →
nuke8–13-0.0220%14 Oct →
anubis13–50.1919%14 Oct →
dust28–130.0614%13 Oct →
train5–13-0.079%13 Oct →
nuke9–13-0.027%13 Oct →
dust29–130.0121%12 Oct →
dust213–40.1124%12 Oct →
cache0–11-0.054%12 Oct →
nuke13–60.009%12 Oct →
dust210–13-0.0413%11 Oct →
dust26–130.0610%9 Oct →
nuke8–13-0.0419%6 Oct →
cache10–13-0.0016%6 Oct →
inferno13–100.0010%6 Oct →
dust211–130.0520%5 Oct →
dust26–13-0.0420%5 Oct →
train4–70.0022%4 Oct →
nuke13–60.0736%4 Oct →
dust28–13-0.097%4 Oct →
nuke9–13-0.0331%4 Oct →
inferno3–13-0.100%30 Sept →
cache5–130.0411%28 Sept →
dust213–4-0.0115%27 Sept →
inferno8–80.0322%27 Sept →
inferno6–9-0.0919%27 Sept →
inferno13–100.0120%21 Sept →
cache12–120.0720%21 Sept →
mirage13–5-0.0313%21 Sept →
mirage13–100.0219%21 Sept →
nuke6–9-0.0915%21 Sept →
cache13–10.0024%20 Sept →
nuke10–13-0.039%20 Sept →
dust29–00.0413%20 Sept →
inferno7–13-0.046%18 Sept →
mirage13–11-0.029%17 Sept →
dust212–12-0.0118%17 Sept →
inferno8–80.0616%17 Sept →
ancient13–11-0.088%16 Sept →
anubis9–130.0419%16 Sept →
mirage10–130.0112%16 Sept →
ancient13–60.119%15 Sept →
mirage13–6-0.0012%14 Sept →
dust213–7-0.055%14 Sept →
dust213–80.0216%13 Sept →
inferno13–11-0.039%13 Sept →
inferno12–120.0822%13 Sept →
anubis3–13-0.0414%10 Sept →
mirage13–4-0.0421%10 Sept →
train13–110.0623%29 Aug →
dust20–9-0.0528%19 Aug →
nuke13–40.118%19 Aug →
mirage11–13-0.0514%19 Aug →
nuke13–110.0615%13 Aug →
inferno3–9-0.218%13 Aug →
dust213–50.0614%12 Aug →
train13–70.056%12 Aug →
vertigo13–7-0.0811%12 Aug →
vertigo6–130.0713%10 Aug →
nuke13–40.1316%8 Aug →
office9–130.0343%2 Aug →
inferno7–130.0417%2 Aug →
mirage6–13-0.0529%30 Jul →
vertigo13–9-0.0617%30 Jul →
mirage13–20.1217%27 Jul →
inferno6–9-0.0215%25 Jul →
anubis3–13-0.0023%24 Jul →
mirage13–11-0.0014%24 Jul →
nuke13–60.108%20 Jul →
nuke2–9-0.0311%15 Jul →
ancient12–12-0.0313%11 Jul →
dust28–13-0.0425%6 Jul →
dust26–13-0.0226%6 Jul →
overpass13–20.1410%2 Jul →
ancient5–13-0.028%1 Jul →
nuke2–10-0.0918%22 Jun →
inferno13–40.0625%22 Jun →
dust211–130.0221%14 Jun →
mirage3–13-0.0440%10 Jun →
cache13–100.039%9 Jun →
inferno8–80.0113%9 Jun →
inferno11–13-0.0211%8 Jun →
dust213–10.099%8 Jun →
dust213–80.0229%7 Jun →
nuke13–20.0219%7 Jun →
inferno7–13-0.0720%4 Jun →
cache13–50.0312%3 Jun →
inferno5–9-0.0910%1 Jun →
dust212–12-0.0212%28 May →
inferno13–20.016%28 May →
nuke13–2-0.0018%26 May →
nuke0–11-0.220%25 May →
mirage12–120.067%25 May →
cache6–13-0.0511%18 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.