hao_sekiro

hao_sekiro — CS2 Stats

JP76561199581692376[U:1:1621426648]Steam profile ↗✓ No bans

624Tracked matches52%Win rate2026Tracked since
CSDB Rating5.5 SolidPositional Player
Premier CS Rating5,837Light Blue band · top ~74.8% of ranked players (population est.)
WingmanMaster Guardian II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 6 Oct 2026 (29 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: 5,837 +3,476 3 Sept – 6 Oct · 5 days played
2,3615,961peak 5,9613 Sept6 Oct
5,961Peak Premier in tracked matches
21Days played since 2026-09-03

Premier CS Rating

  • 124 below peak (5,961)
  • +3,476 over 30 days · improving
  • Next: Blue band at 10,000 — 4,163 to go
  • Reached: Light Blue band

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

Share this profile

CSDB.GGhao_sekiroPREMIER5,837 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim61
Positioning62
Utility37

0–100 skill scores via Leetify.

Recent form

COLD59–39–2Last 10059%Win rateLWWLLLLLLL

Last 10 vs previous 10: −10pp win rate · −0.04 avg rating · +6.2pp headshot accuracy · +18ms reaction

Win rate −10pp 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 -0.06
  • Avg headshot accuracy 19%
  • Avg reaction 644ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 22%
  • Avg reaction 671ms

Last 20

  • 5–13–2 · 25% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 19%
  • Avg reaction 662ms

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 (+1.9 against its own average).

Aim6.1
Utility3.7
Positioning6.2
Opening Duels3.1

Excellent counter-strafingStrong CT-side opener

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

m0NESY

Plays most like m0NESY 83% 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

Strengths

T openings. 63% T opening-duel success — entries that actually open the round.

Areas to improve

Reaction time. 682ms 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

Aim6.1
Positioning6.2
Utility3.7
Mechanics8.5
Opening Duels6.9
Win Impact5.6

Composite 5.5/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01+0.00
first ⅓ avg -0.01 → last ⅓ avg -0.01
Reaction time681ms+25ms
first ⅓ avg 657ms → last ⅓ avg 681ms
Headshot accuracy19.0%−0.9%
first ⅓ avg 19.9% → last ⅓ avg 19.0%

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 · 13–9 · cache, 23 Oct →
67%Best headshot accuracy · 1–5 · rush_001, 1 Oct →
422msFastest reaction time · 9–7 · inferno, 27 Sept →
13–1Biggest win · ancient, 14 Oct →

Across the last 100 tracked matches.

Highlights

13Longest win streak
12–9In matches decided by ≤2 rounds
3Overtime games

Map breakdown

anubisBest map · 83% over 6rush_001Weakest map · 36% over 14
MapGradePlayedRecordWin rateAvg rating
dust2S2115–671%0.01
infernoA149–564%-0.04
rush_001C145–936%-0.01
nukeA117–464%-0.03
mirageA116–555%0.01
cacheC83–538%0.03
ancientA74–357%0.01
anubisS65–183%-0.01
vertigo—32–167%-0.03
train—33–0100%0.05
overpass—10–10%-0.08
boulder—10–10%-0.00

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.

19.9%Headshot accuracy
28.7%Accuracy (enemy spotted)
28.3%Spray accuracy
88.3%Counter-strafing
7.8°Preaim
682msReaction time
62.9%T opening success
52.1%CT opening success
0.47Enemies flashed / flash
2.3%Flash assists
6.66HE damage / grenade
6.87Flashes / 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 0.467 — below the 0.5 mark we flag

    Grenade Lineups →
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.

38% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
nuke7–130.0119%3 Nov →
dust213–11-0.0423%3 Nov →
mirage13–80.1118%3 Nov →
inferno1–9-0.3118%3 Nov →
dust21–13-0.0620%1 Nov →
inferno4–13-0.0329%1 Nov →
mirage7–13-0.0615%1 Nov →
dust27–130.0034%31 Oct →
inferno4–9-0.0724%31 Oct →
mirage11–130.0721%31 Oct →
cache8–130.0714%30 Oct →
cache4–13-0.0924%30 Oct →
nuke10–13-0.0018%30 Oct →
vertigo5–13-0.0615%30 Oct →
dust213–7-0.0118%27 Oct →
ancient13–50.0116%27 Oct →
cache12–120.0716%23 Oct →
cache13–90.1319%23 Oct →
inferno8–8-0.0418%22 Oct →
rush_0015–8-0.080%22 Oct →
rush_0015–10.0411%22 Oct →
dust213–80.0427%22 Oct →
inferno13–11-0.0325%22 Oct →
inferno9–20.0513%22 Oct →
inferno2–9-0.157%22 Oct →
mirage13–70.0217%22 Oct →
dust213–11-0.0219%22 Oct →
dust25–130.1039%18 Oct →
nuke13–70.0714%18 Oct →
rush_0015–8-0.090%18 Oct →
rush_0014–00.0440%18 Oct →
cache11–130.0017%18 Oct →
ancient7–13-0.0220%18 Oct →
nuke1–9-0.1918%18 Oct →
overpass7–9-0.0832%18 Oct →
inferno9–60.0629%18 Oct →
inferno13–70.1222%18 Oct →
nuke9–6-0.068%14 Oct →
inferno13–50.0419%14 Oct →
anubis13–2-0.018%14 Oct →
cache13–2-0.0115%14 Oct →
mirage9–130.0120%14 Oct →
ancient13–10.0914%14 Oct →
boulder0–13-0.0018%14 Oct →
mirage13–90.0022%12 Oct →
rush_0012–60.0246%10 Oct →
dust213–60.0018%10 Oct →
dust25–13-0.0131%10 Oct →
rush_0016–80.0427%9 Oct →
rush_0017–30.0517%9 Oct →
rush_0012–6-0.0645%9 Oct →
rush_0018–70.0023%9 Oct →
rush_0016–8-0.0322%9 Oct →
dust29–130.0019%9 Oct →
rush_0018–60.0718%9 Oct →
ancient9–13-0.0619%6 Oct →
train13–40.0919%5 Oct →
ancient16–140.0420%5 Oct →
dust213–110.0226%5 Oct →
dust27–00.0315%5 Oct →
dust213–80.0821%5 Oct →
dust213–70.0519%5 Oct →
mirage13–9-0.0116%2 Oct →
ancient11–13-0.0010%2 Oct →
mirage16–13-0.0014%1 Oct →
dust213–9-0.0620%1 Oct →
rush_0016–80.0011%1 Oct →
rush_0010–4-0.110%1 Oct →
rush_0011–5-0.0767%1 Oct →
inferno13–5-0.0517%1 Oct →
ancient13–110.0214%1 Oct →
dust25–13-0.0822%1 Oct →
dust213–30.0618%1 Oct →
mirage8–13-0.0415%30 Sept →
nuke13–10-0.0326%30 Sept →
anubis16–140.0019%30 Sept →
nuke13–7-0.0116%30 Sept →
nuke13–100.0117%30 Sept →
mirage13–7-0.0018%29 Sept →
cache11–130.0217%29 Sept →
anubis9–13-0.0913%29 Sept →
anubis13–4-0.0314%29 Sept →
cache13–40.0716%28 Sept →
train13–4-0.0019%28 Sept →
train13–60.0515%28 Sept →
dust213–7-0.0723%27 Sept →
dust213–70.0019%27 Sept →
anubis6–40.0111%27 Sept →
nuke13–4-0.0224%27 Sept →
dust213–20.0328%27 Sept →
vertigo13–30.0121%27 Sept →
anubis13–50.0431%27 Sept →
inferno9–7-0.1029%27 Sept →
dust213–50.0618%26 Sept →
nuke7–90.0418%26 Sept →
nuke9–6-0.1211%26 Sept →
inferno9–50.0317%26 Sept →
vertigo13–11-0.0426%26 Sept →
mirage7–130.0118%26 Sept →
inferno9–5-0.0420%26 Sept →

Match data via Leetify.

Recent teammates

Milestones

500 Matches13-Win Streak
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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