Umbra

Umbra — CS2 Stats

UA76561198095654840[U:1:135389112]Steam profile ↗✓ No bans

386Tracked matches43%Win rate2023Tracked since
691Hours in CS
CSDB Rating4.6 DevelopingSupport
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 12,800 -1,758 18 Jun – 12 Jul · 4 days played
12,80014,558peak 14,55818 Jun12 Jul
14,558Peak Premier in tracked matches
39Days played since 2025-06-12

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

Performance scores

Aim65
Positioning46
Utility46

0–100 skill scores via Leetify.

Recent form

STEADY52–41–7Last 10052%Win rateWWWWLLLWWL

Last 10 vs previous 10: +30pp win rate · +0.04 avg rating · +2.9pp headshot accuracy · −69ms reaction

Win rate up 30pp 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 0.06
  • Avg headshot accuracy 17%
  • Avg reaction 544ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 16%
  • Avg reaction 548ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 15%
  • Avg reaction 583ms

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: Support — Utility contribution stands above the rest of this profile (+1.5 against its own average).

Aim6.5
Utility4.6
Positioning4.6
Opening Duels0.0

Strong T-side openerLimited 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: utility contribution, positioning profile.

Where you differ: lower aim profile; lower opening-duel success.

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

CT openings. Opening success drops from 34% on T to 7% on CT — first contacts on the defending side are being lost.

Reaction time. 591ms 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

Aim6.5
Positioning4.6
Utility4.6
Mechanics4.8
Opening Duels0.4
Win Impact2.6

Composite 4.6/10 (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 rating0.02+0.03
first ⅓ avg -0.01 → last ⅓ avg 0.02
Reaction time599ms−23ms
first ⅓ avg 622ms → last ⅓ avg 599ms
Headshot accuracy14.4%−0.7%
first ⅓ avg 15.1% → last ⅓ avg 14.4%

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

0.18Best match rating · 4–0 · rush_001, 21 Oct →
28%Best headshot accuracy · 13–5 · dust2, 10 Sept →
383msFastest reaction time · 9–13 · office, 6 Dec →
13–2Biggest win · overpass, 6 Dec →

Across the last 100 tracked matches.

Highlights

6Longest win streak
W4Current streak
7–4In matches decided by ≤2 rounds
3Overtime games

Map breakdown

officeBest map · 60% over 43infernoWeakest map · 25% over 8
MapGradePlayedRecordWin rateAvg rating
officeA4326–1760%0.01
dust2B137–654%-0.01
infernoD82–625%0.00
trainA74–357%0.03
overpassB63–350%0.03
ancientC52–340%0.01
agency—42–250%-0.01
mirage—42–250%0.01
nuke—31–233%-0.01
rush_001—22–0100%0.16
cache—20–20%-0.02
vertigo—10–10%0.02
grail—10–10%-0.05
italy—11–0100%-0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (25% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

40,221Lifetime kills
1.55K/D · Top 5% of tracked players
2,116Matches
53.1%Match win rate · Top 10% of tracked players
36.7%Headshot %
15.7%Shot accuracy · Top 25% of tracked players
3,893MVPs
691Hours (in match)
1,705Bombs planted
261Bombs defused

Most-used weapons

Lifetime map wins

4,453dust2
1,876office
1,870inferno
780nuke
470assault
466train
345italy
253aztec

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.

14.2%Headshot accuracy
36.9%Accuracy (enemy spotted)
42.7%Spray accuracy
71.6%Counter-strafing
10.2°Preaim
591msReaction time
33.6%T opening success
7.0%CT opening success
0.49Enemies flashed / flash
11.8%Flash assists
11.98HE damage / grenade
1.47Flashes / 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 14.2186% — 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 0.4864 — 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 33.5679% — 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.

25% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
rush_0014–00.1818%21 Oct →
rush_0014–00.1423%21 Oct →
office13–11-0.0013%21 Oct →
office9–40.0216%21 Oct →
office5–13-0.0514%1 Aug →
nuke2–13-0.0224%27 Jun →
inferno9–130.0112%27 Jun →
overpass13–40.1312%27 Jun →
office13–100.0713%18 Jun →
train3–13-0.0018%18 Jun →
inferno4–13-0.0311%18 Jun →
office13–40.1220%18 Jun →
office11–13-0.0218%15 Jun →
train13–100.0512%15 Jun →
train11–130.0516%30 May →
office4–13-0.0717%30 May →
nuke2–13-0.042%20 May →
vertigo9–130.029%20 May →
train13–80.0213%20 May →
office9–13-0.0117%20 May →
dust25–5-0.0610%20 May →
office13–60.0412%20 May →
office13–9-0.0019%13 May →
office12–12-0.0324%13 May →
inferno12–12-0.0012%9 May →
overpass2–130.0014%9 May →
overpass1–13-0.0510%9 May →
inferno13–40.1210%9 May →
office2–13-0.073%29 Apr →
cache11–130.0117%29 Apr →
cache1–13-0.0413%29 Apr →
train13–70.0117%22 Apr →
office13–30.0515%15 Apr →
office13–110.0515%15 Apr →
dust210–130.1014%11 Apr →
office10–130.0516%21 Mar →
office13–100.0715%25 Feb →
office13–70.129%18 Jan →
office13–100.0211%18 Jan →
office7–13-0.0410%11 Dec →
office13–9-0.0014%11 Dec →
office12–120.1013%7 Dec →
office9–13-0.078%6 Dec →
overpass13–20.109%6 Dec →
office13–80.0017%29 Nov →
office10–130.0411%29 Nov →
agency7–130.0014%29 Nov →
office13–9-0.0022%26 Oct →
agency12–12-0.0216%25 Oct →
train13–20.0426%25 Oct →
ancient14–160.0117%9 Oct →
ancient13–100.039%9 Oct →
office13–40.019%5 Oct →
mirage13–5-0.0013%5 Oct →
inferno13–100.0110%5 Oct →
dust213–9-0.0316%5 Oct →
dust24–13-0.0310%30 Sept →
overpass1–13-0.0527%30 Sept →
dust26–00.1221%30 Sept →
office7–13-0.0011%19 Sept →
office5–00.0721%19 Sept →
inferno12–12-0.0114%19 Sept →
train9–130.0112%19 Sept →
overpass13–80.0612%19 Sept →
office10–130.0414%11 Sept →
dust212–12-0.0527%10 Sept →
dust213–80.0118%10 Sept →
dust213–50.0128%10 Sept →
ancient13–110.0013%10 Sept →
office13–60.0218%7 Sept →
nuke13–110.0120%28 Aug →
grail4–13-0.0511%28 Aug →
office13–4-0.0620%28 Aug →
office13–5-0.0220%25 Aug →
italy13–3-0.0313%18 Aug →
office13–110.0619%18 Aug →
agency13–20.0120%18 Aug →
office13–11-0.0317%23 Jul →
office10–130.0214%23 Jul →
office12–12-0.019%12 Jul →
mirage13–160.029%12 Jul →
mirage13–100.0222%12 Jul →
inferno12–16-0.0313%12 Jul →
ancient9–130.0015%12 Jul →
dust213–7-0.0516%12 Jul →
dust29–13-0.0610%12 Jul →
dust210–13-0.0216%12 Jul →
dust29–13-0.007%10 Jul →
ancient9–13-0.0115%10 Jul →
mirage8–130.0013%10 Jul →
office13–6-0.025%10 Jul →
inferno9–13-0.0513%27 Jun →
office13–50.057%25 Jun →
office7–13-0.0717%25 Jun →
office13–5-0.0220%25 Jun →
dust213–10-0.0412%18 Jun →
office13–8-0.0111%18 Jun →
office13–6-0.0220%18 Jun →
office7–130.0416%12 Jun →
agency13–7-0.0317%12 Jun →

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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