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Bloo

Bloo — CS2 Stats

MC76561198107637362[U:1:147371634]Steam profile ↗✓ No bans

185Tracked matches47%Win rate2024Tracked since
CSDB Rating4.5 DevelopingPositional Player
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 16 Sep 2026 (59 days ago). Ranks are recorded once per day this page is viewed.

+33Tracked matches · now 185
+3.3ppWin rate · 43.3% → 46.7%

Rating over time

61Days played since 2026-04-26

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

Performance scores

Aim46
Positioning64
Utility45

0–100 skill scores via Leetify.

Recent form

STEADY42–55–3Last 10042%Win rateLWWLLLWLWL

Last 10 vs previous 10: 0pp win rate · −0.02 avg rating · −0.3pp headshot accuracy · −65ms 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

  • 2–3 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 10%
  • Avg reaction 481ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 10%
  • Avg reaction 492ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 10%
  • Avg reaction 525ms

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 against its own average).

Aim4.6
Utility4.5
Positioning6.4
Opening Duels5.3

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

jL

Plays most like jL 79% 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

Areas to improve

Counter-strafing. Only 60% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim4.6
Positioning6.4
Utility4.5
Mechanics2.3
Opening Duels4.2
Win Impact3.9

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 rating0.02+0.00
first ⅓ avg 0.02 → last ⅓ avg 0.02
Reaction time542ms−31ms
first ⅓ avg 572ms → last ⅓ avg 542ms
Headshot accuracy9.5%−3.1%
first ⅓ avg 12.6% → last ⅓ avg 9.5%

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

0.29Best match rating · 13–2 · office, 10 Sept →
22%Best headshot accuracy · 5–13 · dust2, 22 Jul →
383msFastest reaction time · 6–13 · office, 9 Oct →
13–1Biggest win · office, 12 Jun →

Across the last 100 tracked matches.

Highlights

6Longest win streak
8–1In matches decided by ≤2 rounds

Map breakdown

ancientBest map · 83% over 6infernoWeakest map · 37% over 19
MapGradePlayedRecordWin rateAvg rating
officeC5320–3338%0.03
infernoC197–1237%-0.00
vertigoA116–555%0.02
ancientS65–183%0.04
dust2—41–325%-0.02
mirage—22–0100%-0.01
train—10–10%-0.14
cache—10–10%-0.10
alpine—11–0100%-0.07
nuke—10–10%-0.02
italy—10–10%-0.12

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (37% over 19). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Skill profile

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

9.4%Headshot accuracy
34.5%Accuracy (enemy spotted)
37.4%Spray accuracy
60.3%Counter-strafing
10.5°Preaim
539msReaction time
46.5%T opening success
47.2%CT opening success
0.50Enemies flashed / flash
1.1%Flash assists
13.26HE damage / grenade
1.88Flashes / 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 9.4171% — below the 15% 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 1.8767 — below the 4 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.

37% win rate across 19 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
vertigo1–13-0.0412%13 Nov →
ancient13–90.038%23 Oct →
ancient13–9-0.0112%22 Oct →
office9–13-0.029%21 Oct →
office10–13-0.018%17 Oct →
office6–130.0714%9 Oct →
inferno13–60.058%4 Oct →
office5–13-0.0412%3 Oct →
vertigo13–90.0412%30 Sept →
office10–13-0.066%30 Sept →
dust26–13-0.0314%29 Sept →
office13–110.0113%27 Sept →
vertigo13–110.125%26 Sept →
inferno2–13-0.036%26 Sept →
office4–13-0.0418%26 Sept →
office13–40.1011%26 Sept →
vertigo9–13-0.027%24 Sept →
office10–130.049%24 Sept →
vertigo13–70.0611%24 Sept →
inferno8–13-0.018%16 Sept →
office10–13-0.033%16 Sept →
office13–40.088%12 Sept →
office13–20.2912%10 Sept →
office13–90.0314%9 Sept →
office11–130.0510%9 Sept →
office13–90.036%4 Sept →
inferno3–13-0.038%2 Sept →
vertigo7–130.006%30 Aug →
ancient13–60.056%30 Aug →
ancient13–40.0111%26 Aug →
office4–13-0.039%26 Aug →
office13–90.099%26 Aug →
office4–130.069%23 Aug →
train3–13-0.145%7 Aug →
office9–130.0414%5 Aug →
inferno13–90.1513%4 Aug →
office7–13-0.055%4 Aug →
office13–100.085%4 Aug →
office7–130.0612%29 Jul →
vertigo13–100.029%29 Jul →
vertigo13–30.028%29 Jul →
office13–70.0711%26 Jul →
office2–13-0.046%26 Jul →
inferno13–7-0.0913%23 Jul →
ancient6–130.0518%23 Jul →
office9–13-0.038%23 Jul →
dust25–13-0.1022%22 Jul →
office13–60.0813%17 Jul →
office4–13-0.0616%16 Jul →
cache0–5-0.1017%16 Jul →
inferno13–11-0.0313%14 Jul →
inferno2–13-0.0110%14 Jul →
office10–130.047%12 Jul →
inferno1–13-0.1013%11 Jul →
office9–130.029%4 Jul →
office13–100.058%3 Jul →
office8–130.056%3 Jul →
inferno13–110.0714%1 Jul →
dust29–13-0.0317%29 Jun →
office13–11-0.008%27 Jun →
office10–11-0.0217%27 Jun →
office13–80.0310%27 Jun →
inferno1–10-0.0310%20 Jun →
inferno13–11-0.0010%17 Jun →
alpine13–10-0.0712%12 Jun →
dust213–80.089%12 Jun →
inferno4–40.0418%12 Jun →
office13–10.1110%12 Jun →
ancient13–70.0910%12 Jun →
inferno9–130.0120%12 Jun →
inferno7–13-0.016%10 Jun →
mirage11–5-0.0321%6 Jun →
office6–13-0.0218%6 Jun →
office10–130.059%5 Jun →
vertigo5–13-0.0217%5 Jun →
vertigo13–60.1613%5 Jun →
office10–130.057%3 Jun →
nuke9–13-0.0215%29 May →
office3–130.0411%29 May →
office13–60.0515%27 May →
office12–12-0.0210%24 May →
inferno4–130.0120%20 May →
office7–130.0216%15 May →
office8–1-0.0112%15 May →
office13–30.0518%14 May →
office2–13-0.0511%12 May →
inferno9–13-0.0611%12 May →
office7–130.0312%9 May →
office13–50.0310%8 May →
inferno9–130.017%7 May →
office7–13-0.0116%4 May →
italy3–13-0.128%4 May →
office12–120.1413%3 May →
office10–130.0710%3 May →
office10–130.029%1 May →
vertigo2–13-0.0722%30 Apr →
inferno12–12-0.008%30 Apr →
mirage13–70.0112%26 Apr →
office10–130.116%26 Apr →
office13–90.1313%26 Apr →

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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