BLOOD DRUNK

BLOOD DRUNK — CS2 Stats

76561198271781110[U:1:311515382]Steam profile ↗✓ No bans

234Tracked matches50%Win rate2020Tracked since
CSDB Rating4.7 DevelopingPositional Player
Premier CS Rating12,528Blue band · top ~41.5% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 11 Nov 2026 (4 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 12,528 +1,606 12 May – 11 Nov · 25 days played
10,80513,763peak 13,76312 May11 Nov
14,027Peak Premier in tracked matches
55Days played since 2025-05-12

Premier CS Rating

  • 1,235 below peak (13,763)
  • Next: Purple band at 15,000 — 2,472 to go
  • Reached: Blue band · Light Blue band

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

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CSDB.GGBLOOD DRUNKPREMIER12,528 · Blue bandcsdb.gg/stats

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Performance scores

Aim58
Positioning53
Utility43

0–100 skill scores via Leetify.

Recent form

STEADY47–48–5Last 10047%Win rateWLLTWWLTWL

Last 10 vs previous 10: 0pp win rate · −0.04 avg rating · −1.8pp headshot accuracy · −104ms reaction

Win rate 0pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 2–2–1 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 24%
  • Avg reaction 594ms

Last 10

  • 4–4–2 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 18%
  • Avg reaction 550ms

Last 20

  • 8–10–2 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 18%
  • Avg reaction 602ms

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 (+1.7 against its own average).

Aim5.8
Utility4.3
Positioning5.3
Opening Duels1.2

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 85% 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. 605ms 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
Positioning5.3
Utility4.3
Mechanics5.9
Opening Duels1.2
Win Impact5.0

Composite 4.7/10 (Developing), 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-0.00−0.01
first ⅓ avg 0.01 → last ⅓ avg -0.00
Reaction time601ms−3ms
first ⅓ avg 604ms → last ⅓ avg 601ms
Headshot accuracy20.9%+3.2%
first ⅓ avg 17.7% → last ⅓ avg 20.9%

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

0.31Best match rating · 13–6 · inferno, 31 Jan →
75%Best headshot accuracy · 1–8 · cache, 30 Apr →
406msFastest reaction time · 6–1 · inferno, 11 Jul →
13–3Biggest win · anubis, 11 Jun →

Across the last 100 tracked matches.

Highlights

5Longest win streak
11–9In matches decided by ≤2 rounds
11Overtime games

Map breakdown

infernoBest map · 70% over 23cacheWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
infernoS2316–770%0.03
nukeC229–1341%0.02
anubisB158–753%0.00
ancientC145–936%-0.01
cacheD61–517%-0.01
dust2D62–433%-0.01
overpassD62–433%-0.00
train—42–250%0.02
mirage—32–167%-0.02
vertigo—10–10%0.02

Across the last 100 tracked matches.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

20.7%Headshot accuracy
30.4%Accuracy (enemy spotted)
30.7%Spray accuracy
76.6%Counter-strafing
9.8°Preaim
605msReaction time
37.9%T opening success
32.0%CT opening success
0.43Enemies flashed / flash
3.1%Flash assists
7.14HE damage / grenade
10.23Flashes / 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 0.4259 — below the 0.5 mark we flag

    Grenade Lineups →
  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 37.8989% — below the 40% mark we flag

Spend your practice time on Cache

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.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
ancient13–60.0024%11 Nov →
cache11–13-0.0515%11 Nov →
nuke7–13-0.0714%10 Nov →
inferno15–150.0127%9 Nov →
inferno16–140.0638%8 Nov →
anubis13–9-0.0312%4 Nov →
cache2–13-0.066%21 Oct →
mirage15–15-0.0817%18 Oct →
inferno13–110.0016%14 Oct →
dust26–13-0.068%12 Oct →
nuke13–50.0412%26 Jul →
anubis13–70.0419%25 Jul →
ancient1–13-0.0910%25 Jul →
nuke13–80.0431%24 Jul →
anubis7–130.0119%21 Jul →
cache6–130.0019%20 Jul →
cache11–130.0125%20 Jul →
ancient10–13-0.0431%19 Jul →
ancient13–40.1214%19 Jul →
nuke5–130.0014%11 Jul →
inferno6–1-0.0311%11 Jul →
inferno13–70.0715%28 Jun →
cache13–100.0414%18 May →
cache1–8-0.0275%30 Apr →
overpass6–13-0.0310%28 Apr →
train9–13-0.0224%28 Apr →
ancient3–13-0.0523%28 Apr →
anubis13–9-0.0130%28 Apr →
inferno13–11-0.0226%27 Apr →
nuke13–7-0.0135%27 Apr →
ancient13–10-0.0220%17 Apr →
nuke10–130.0413%15 Apr →
inferno13–70.1223%15 Apr →
nuke9–130.0125%15 Apr →
inferno4–13-0.048%13 Apr →
dust211–130.0019%6 Apr →
ancient7–13-0.0616%6 Apr →
dust210–130.0224%26 Mar →
nuke5–130.0224%26 Mar →
nuke1–130.0410%22 Mar →
ancient2–13-0.0431%22 Mar →
overpass13–80.0328%22 Mar →
inferno16–130.039%19 Mar →
anubis13–60.0722%19 Mar →
inferno11–13-0.0032%15 Mar →
overpass13–11-0.0418%15 Mar →
inferno13–90.037%9 Mar →
ancient9–130.0422%9 Mar →
nuke10–30.0119%9 Mar →
mirage16–13-0.0123%6 Feb →
overpass11–130.0228%5 Feb →
anubis15–15-0.0230%1 Feb →
inferno13–50.0420%1 Feb →
nuke2–13-0.0523%1 Feb →
ancient16–140.0213%31 Jan →
inferno13–60.3113%31 Jan →
ancient13–11-0.0123%29 Jan →
inferno9–130.0224%29 Jan →
nuke13–60.0321%27 Jan →
ancient11–13-0.0228%27 Jan →
inferno13–50.0524%27 Jan →
nuke11–130.0535%27 Jan →
overpass9–130.0120%27 Jan →
anubis7–13-0.0314%26 Jan →
nuke13–110.0629%23 Oct →
anubis13–50.0840%17 Oct →
inferno13–40.0822%8 Oct →
train15–15-0.0117%8 Oct →
overpass5–130.0120%15 Jul →
vertigo5–130.025%15 Jul →
inferno6–13-0.0326%18 Jun →
anubis6–130.0122%18 Jun →
nuke13–110.0221%17 Jun →
anubis8–13-0.0628%16 Jun →
dust213–6-0.0613%16 Jun →
ancient6–13-0.0510%16 Jun →
inferno10–13-0.0019%11 Jun →
anubis13–30.0317%11 Jun →
dust211–130.0321%10 Jun →
nuke11–130.0512%10 Jun →
nuke13–80.0916%6 Jun →
nuke5–130.0416%6 Jun →
anubis3–13-0.0716%6 Jun →
anubis6–13-0.029%3 Jun →
dust213–9-0.0217%3 Jun →
nuke13–110.0118%3 Jun →
inferno15–150.0923%1 Jun →
nuke4–13-0.0311%1 Jun →
anubis16–140.026%29 May →
train13–60.0720%29 May →
inferno13–40.0514%29 May →
inferno13–10-0.0129%26 May →
mirage6–00.0313%18 May →
nuke7–130.0516%18 May →
inferno16–140.0120%16 May →
train13–80.0321%16 May →
nuke5–13-0.0335%15 May →
inferno13–9-0.0724%12 May →
ancient6–130.0510%12 May →
anubis13–60.0421%12 May →

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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