Hanabi

Hanabi — CS2 Stats

76561199020751754[U:1:1060486026]Steam profile ↗✓ No bans

804Tracked matches48%Win rate2023Tracked since
CSDB Rating3.8 LearningSupport
WingmanSilver III
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 20 Sep 2026 (27 days ago). Ranks are recorded once per day this page is viewed.

+12Tracked matches · now 804
−2.0ppWin rate · 50.0% → 48.0%

Rating over time

49Days played since 2026-02-11

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

Performance scores

Aim35
Positioning45
Utility49

0–100 skill scores via Leetify.

Recent form

COLD38–50–12Last 10038%Win rateLLTLWTTLWW

Last 10 vs previous 10: +20pp win rate · +0.01 avg rating · +1.1pp headshot accuracy · −55ms 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

  • 1–3–1 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 29%
  • Avg reaction 675ms

Last 10

  • 3–4–3 · 30% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 20%
  • Avg reaction 675ms

Last 20

  • 4–12–4 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 20%
  • Avg reaction 702ms

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 (+1.4 against its own average).

Aim3.5
Utility4.9
Positioning4.5
Opening Duels1.0

Effective flashes

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

ZywOo

Plays most like ZywOo 70% 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

Strengths

Flashes. 0.76 enemies blinded per flash — utility that consistently lands.

Areas to improve

T-side openings. Opening success drops from 40% on CT to 22% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 716ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 68% 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

Aim3.5
Positioning4.5
Utility4.9
Mechanics3.9
Opening Duels1.3
Win Impact4.3

Composite 3.8/10 (Learning), 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 rating-0.04+0.02
first ⅓ avg -0.06 → last ⅓ avg -0.04
Reaction time708ms−39ms
first ⅓ avg 747ms → last ⅓ avg 708ms
Headshot accuracy17.0%−0.1%
first ⅓ avg 17.1% → last ⅓ avg 17.0%

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

0.13Best match rating · 13–2 · dust2, 13 Sept →
60%Best headshot accuracy · 13–11 · mirage, 28 Feb →
438msFastest reaction time · 12–12 · office, 27 Sept →
13–1Biggest win · dust2, 27 Mar →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L2Current streak
10–8In matches decided by ≤2 rounds

Map breakdown

dust2Best map · 45% over 44trainWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
dust2B4420–2445%-0.04
mirageC2510–1540%-0.06
infernoD72–529%-0.06
trainD61–517%-0.07
cache—42–250%-0.07
office—31–233%0.02
nuke—32–167%-0.01
vertigo—20–20%-0.08
overpass—20–20%-0.06
ancient—20–20%-0.13
poseidon—10–10%-0.15
anubis—10–10%-0.07

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.

17.7%Headshot accuracy
39.2%Accuracy (enemy spotted)
45.5%Spray accuracy
67.6%Counter-strafing
18.0°Preaim
716msReaction time
22.4%T opening success
40.2%CT opening success
0.76Enemies flashed / flash
9.7%Flash assists
6.51HE damage / grenade
7.25Flashes / 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

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 17.9581° — above the 12° mark we flag

    Aim Training →
  2. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 716.2862ms — above the 700ms mark we flag

    Aim Training →
Spend your practice time on Train

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.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
dust211–13-0.0435%9 Oct →
mirage4–13-0.0315%9 Oct →
vertigo12–12-0.0519%9 Oct →
mirage3–4-0.0250%2 Oct →
dust213–8-0.0227%1 Oct →
dust212–12-0.1012%1 Oct →
office12–120.0525%27 Sept →
office2–9-0.110%27 Sept →
office13–80.130%25 Sept →
dust213–5-0.0221%20 Sept →
dust212–120.0231%20 Sept →
dust27–13-0.056%20 Sept →
dust26–13-0.0529%13 Sept →
dust25–13-0.0221%13 Sept →
dust213–20.1329%13 Sept →
mirage3–13-0.0217%22 Aug →
dust210–13-0.0414%22 Aug →
poseidon5–9-0.159%29 Jun →
overpass5–9-0.0730%29 Jun →
vertigo4–9-0.117%29 Jun →
nuke9–30.070%29 Jun →
inferno7–9-0.1311%29 Jun →
dust213–50.0618%20 Jun →
ancient0–13-0.140%13 Jun →
cache13–9-0.104%30 May →
cache13–10-0.0517%9 May →
cache11–13-0.0615%9 May →
cache12–12-0.0617%30 Apr →
dust213–11-0.0716%27 Apr →
train13–4-0.1224%19 Apr →
mirage13–7-0.0719%19 Apr →
dust213–11-0.0211%13 Apr →
dust27–13-0.1113%12 Apr →
mirage11–13-0.1125%12 Apr →
dust213–90.019%11 Apr →
mirage7–13-0.0924%11 Apr →
dust212–12-0.058%10 Apr →
mirage13–6-0.0520%10 Apr →
nuke13–3-0.050%9 Apr →
overpass7–13-0.0617%9 Apr →
dust213–9-0.095%7 Apr →
mirage7–13-0.0729%7 Apr →
mirage13–11-0.0323%2 Apr →
dust22–13-0.0911%2 Apr →
dust213–11-0.150%2 Apr →
dust26–130.0018%2 Apr →
mirage10–13-0.1015%31 Mar →
dust213–110.0517%31 Mar →
dust24–13-0.080%30 Mar →
mirage13–2-0.0825%30 Mar →
train4–13-0.0833%27 Mar →
mirage10–13-0.080%27 Mar →
dust213–10.028%27 Mar →
mirage13–10-0.0725%25 Mar →
inferno7–13-0.0819%24 Mar →
dust28–30.1229%24 Mar →
dust213–10-0.094%23 Mar →
mirage5–13-0.0815%22 Mar →
dust212–12-0.0213%22 Mar →
mirage12–12-0.0913%21 Mar →
dust212–12-0.029%21 Mar →
train12–12-0.0720%19 Mar →
dust29–13-0.0720%19 Mar →
dust24–13-0.0219%18 Mar →
mirage12–12-0.0540%18 Mar →
inferno4–13-0.0333%17 Mar →
dust29–13-0.0213%17 Mar →
ancient3–13-0.110%16 Mar →
inferno11–13-0.0011%16 Mar →
dust213–7-0.0511%16 Mar →
dust213–9-0.0812%9 Mar →
nuke11–13-0.0650%8 Mar →
anubis1–13-0.0740%8 Mar →
dust29–13-0.0431%8 Mar →
dust211–13-0.090%8 Mar →
mirage13–9-0.0317%8 Mar →
dust213–11-0.0514%5 Mar →
inferno3–13-0.080%5 Mar →
dust25–13-0.0117%3 Mar →
dust24–13-0.0712%2 Mar →
mirage9–13-0.087%2 Mar →
train12–12-0.0523%1 Mar →
mirage3–13-0.0310%1 Mar →
dust22–13-0.070%1 Mar →
mirage13–11-0.0760%28 Feb →
dust24–13-0.097%28 Feb →
mirage13–9-0.0321%27 Feb →
train7–130.0015%27 Feb →
dust213–8-0.007%27 Feb →
dust213–110.0014%20 Feb →
mirage9–13-0.0914%18 Feb →
dust213–11-0.0614%18 Feb →
train8–13-0.0817%16 Feb →
dust26–0-0.0450%16 Feb →
mirage6–13-0.100%15 Feb →
mirage13–9-0.0535%14 Feb →
inferno13–8-0.0310%14 Feb →
inferno13–11-0.0717%11 Feb →
mirage10–2-0.030%11 Feb →
dust24–13-0.1629%11 Feb →

Match data via Leetify.

Recent teammates

Milestones

500 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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