b0_0ster

b0_0ster — CS2 Stats

AT76561198146698166[U:1:186432438]Steam profile ↗✓ No bans

1,419Tracked matches52%Win rate2020Tracked since
CSDB Rating7.4 StrongSupport
Premier CS Rating25,668Red band · top ~2.7% of ranked players (population est.)
Ladder ranks via Leetify

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CSDB.GGb0_0sterPREMIER25,668 · Red bandcsdb.gg/stats

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Performance scores

Aim88
Positioning59
Utility63

0–100 skill scores via Leetify.

Recent form

STEADY52–39–9Last 10052%Win rateWLWLTWWLWW

Last 10 vs previous 10: +20pp win rate · +0.01 avg rating · +0.3pp headshot accuracy · −33ms reaction

Win rate up 20pp 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

  • 2–2–1 · 40% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 23%
  • Avg reaction 611ms

Last 10

  • 6–3–1 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 27%
  • Avg reaction 567ms

Last 20

  • 10–8–2 · 50% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 27%
  • 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 (+1.8 against its own average).

Aim8.8
Utility6.3
Positioning5.9
Opening Duels2.7
Clutch3.0

Sharp aimerExcellent counter-strafing

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

NiKo

Plays most like NiKo 93% playstyle similarity

Most alike: positioning profile, 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

Aim. Aim score of 88 — the mechanical foundation is a clear strength.

Counter-strafing. 91% of shots taken properly stopped — movement discipline most players never reach.

Areas to improve

Reaction time. 590ms 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

Aim8.8
Positioning5.9
Utility6.3
Mechanics9.1
Opening Duels3.1
Win Impact5.6

Composite 7.4/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01−0.01
first ⅓ avg 0.02 → last ⅓ avg 0.01
Reaction time599ms−2ms
first ⅓ avg 601ms → last ⅓ avg 599ms
Headshot accuracy28.3%−4.7%
first ⅓ avg 33.1% → last ⅓ avg 28.3%

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

0.15Best match rating · 13–2 · cache, 7 May →
75%Best headshot accuracy · 1–3 · dust2, 12 Jun →
438msFastest reaction time · 13–7 · ancient, 2 Jul →
13–2Biggest win · cache, 10 Oct →

Across the last 100 tracked matches.

Highlights

6Longest win streak
10–7In matches decided by ≤2 rounds
9Overtime games

Map breakdown

ancientBest map · 56% over 9infernoWeakest map · 45% over 11
MapGradePlayedRecordWin rateAvg rating
cacheB2815–1354%0.03
mirageB2612–1446%0.00
dust2A2011–955%0.02
infernoB115–645%0.01
ancientA95–456%0.00
overpass—32–167%0.02
anubis—21–150%0.01
nuke—11–0100%-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (45% over 11). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,610Matches
50%Win rate
1.23Avg K/D
75.6ADR
43%Headshot %

Clutches & streaks

35%1v1 clutch win
21%1v2 clutch win
8Longest win streak

Recent Faceit resultsWWLWW

MapMatchesWin rateAvg K/DAvg kills
Mirage10247%1.1417.3
Ancient7057%1.1015.6
Inferno6157%1.3217.8
Dust24743%1.0615.9
Anubis3339%0.8613.2
Overpass1867%1.3216.2
Cache1258%1.2015.6
Nuke540%0.8511.6

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.

27.1%Headshot accuracy
35.6%Accuracy (enemy spotted)
32.7%Spray accuracy
90.9%Counter-strafing
7.4°Preaim
590msReaction time
49.6%T opening success
35.5%CT opening success
0.62Enemies flashed / flash
9.8%Flash assists
8.91HE damage / grenade
11.55Flashes / 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. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 35.4579% — 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.

45% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient13–70.0432%15 Nov →
cache10–13-0.0216%15 Nov →
anubis13–110.0024%12 Oct →
mirage11–13-0.0129%10 Oct →
cache12–12-0.0115%10 Oct →
cache13–7-0.0233%10 Oct →
cache13–20.0144%10 Oct →
mirage8–130.0324%9 Oct →
nuke13–11-0.0433%9 Oct →
inferno13–50.0523%9 Oct →
dust212–16-0.0138%8 Oct →
cache13–50.0423%8 Oct →
mirage12–120.0636%5 Oct →
cache3–13-0.0126%5 Oct →
cache13–6-0.0125%4 Oct →
inferno1–8-0.0713%4 Oct →
mirage13–10-0.0729%2 Oct →
cache13–7-0.0350%2 Oct →
anubis12–130.0320%2 Oct →
dust211–130.0110%24 Sept →
ancient16–130.0315%24 Sept →
cache6–13-0.0132%23 Sept →
cache13–50.1041%20 Sept →
inferno7–130.0141%2 Aug →
dust213–60.1327%2 Aug →
mirage13–7-0.0214%2 Aug →
mirage4–13-0.0335%31 Jul →
dust28–13-0.0424%31 Jul →
mirage10–130.0523%31 Jul →
cache15–150.0126%28 Jul →
dust213–7-0.0044%28 Jul →
inferno9–130.0040%28 Jul →
mirage13–110.0331%28 Jul →
dust212–16-0.0039%25 Jul →
cache13–8-0.0216%17 Jul →
mirage13–80.0330%17 Jul →
mirage13–100.0634%17 Jul →
mirage10–13-0.0132%16 Jul →
cache15–150.0232%12 Jul →
dust216–120.0337%9 Jul →
inferno13–110.0642%9 Jul →
mirage11–13-0.0114%9 Jul →
cache13–80.1340%9 Jul →
mirage13–110.0842%3 Jul →
ancient8–130.0137%2 Jul →
ancient13–70.0345%2 Jul →
overpass6–13-0.0727%2 Jul →
mirage7–13-0.0728%1 Jul →
ancient13–8-0.0228%30 Jun →
ancient7–13-0.0620%30 Jun →
cache12–12-0.0537%24 Jun →
dust213–110.0019%16 Jun →
overpass10–20.1145%16 Jun →
cache13–60.0628%15 Jun →
mirage15–150.0718%14 Jun →
cache12–120.0235%13 Jun →
dust21–30.0575%12 Jun →
dust213–90.0830%12 Jun →
mirage13–50.0220%12 Jun →
mirage3–7-0.0610%11 Jun →
inferno13–90.0324%11 Jun →
dust26–13-0.0256%5 Jun →
dust213–110.0633%5 Jun →
ancient1–10-0.0145%5 Jun →
dust213–40.0028%5 Jun →
cache7–13-0.0140%5 Jun →
mirage5–13-0.0141%4 Jun →
mirage13–100.0322%4 Jun →
ancient4–10-0.0427%4 Jun →
inferno8–130.0327%4 Jun →
dust213–60.0431%4 Jun →
inferno13–60.0326%28 May →
mirage13–7-0.0017%28 May →
overpass13–90.0224%27 May →
ancient13–110.0242%27 May →
inferno10–13-0.0126%20 May →
mirage10–13-0.0136%20 May →
mirage13–10-0.0230%19 May →
mirage10–130.0221%17 May →
inferno5–130.0217%17 May →
cache9–13-0.0122%15 May →
dust28–13-0.0742%15 May →
dust215–150.0941%15 May →
dust213–60.0340%13 May →
mirage13–60.0137%12 May →
dust213–11-0.0316%12 May →
cache10–130.0343%9 May →
cache13–80.0236%9 May →
mirage5–13-0.0630%7 May →
dust215–150.0234%7 May →
cache13–20.1539%7 May →
inferno13–11-0.0414%4 May →
cache11–130.0741%4 May →
cache13–30.1130%4 May →
cache13–30.0960%4 May →
cache13–70.1037%2 May →
cache13–40.0844%2 May →
dust213–2-0.0160%2 May →
mirage11–50.0040%2 May →
cache11–130.0139%30 Apr →

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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