Hurts

Hurts — CS2 Stats

US76561198082800580[U:1:122534852]Steam profile ↗✓ No bans

244Tracked matches45%Win rate2020Tracked since
578Hours in CS9Hrs last 2 wks
CSDB Rating4.6 DevelopingPositional Player
WingmanDistinguished Master Guardian
Ladder ranks via Leetify

Performance scores

Aim55
Positioning46
Utility36

0–100 skill scores via Leetify.

Recent form

STEADY41–49–10Last 10041%Win rateLLWLLWWWWL

Last 10 vs previous 10: +20pp win rate · −0.00 avg rating · −8.1pp headshot accuracy · −137ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (−0.00), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 9%
  • Avg reaction 575ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 13%
  • Avg reaction 558ms

Last 20

  • 8–11–1 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 17%
  • Avg reaction 626ms

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 (+1.5 against its own average).

Aim5.5
Utility3.6
Positioning4.6
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

NiKo

Plays most like NiKo 88% 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

Reaction time. 647ms 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

Aim5.5
Positioning4.6
Utility3.6
Mechanics6.8
Opening Duels1.2
Win Impact3.3

Composite 4.6/10 (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 rating-0.03−0.03
first ⅓ avg -0.00 → last ⅓ avg -0.03
Reaction time666ms+35ms
first ⅓ avg 631ms → last ⅓ avg 666ms
Headshot accuracy19.0%−0.3%
first ⅓ avg 19.3% → 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

0.21Best match rating · 9–0 · overpass, 31 Jan →
100%Best headshot accuracy · 4–0 · inferno, 22 Jun →
453msFastest reaction time · 3–13 · dust2, 8 Oct →
13–2Biggest win · dust2, 8 Jun →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L2Current streak
6–7In matches decided by ≤2 rounds
1Overtime games

Map breakdown

overpassBest map · 67% over 9anubisWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
mirageD185–1328%-0.03
infernoB136–746%-0.01
trainB115–645%-0.04
overpassS96–367%0.00
vertigoD92–722%-0.02
dust2B84–450%-0.00
anubisD61–517%-0.05
nukeA53–260%-0.02
cache—41–325%-0.05
thera—42–250%0.04
ancient—32–167%-0.01
basalt—22–0100%0.04
poseidon—11–0100%-0.07
brewery—10–10%0.03
dogtown—10–10%-0.02
grail—10–10%0.02
palais—10–10%-0.20
edin—11–0100%0.03
assembly—10–10%-0.05
mills—10–10%-0.06

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

12,922Lifetime kills
0.82K/D
856Matches
36.2%Match win rate
45.3%Headshot % · Top 50% of tracked players
14.7%Shot accuracy · Top 50% of tracked players
1,351MVPs
251Hours (in match)
530Bombs planted
271Bombs defused

Most-used weapons

Lifetime map wins

1,100inferno
492dust2
433train
293vertigo
260nuke
65lake
35cbble
24office

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Skill profile

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

16.2%Headshot accuracy
33.9%Accuracy (enemy spotted)
37.6%Spray accuracy
80.5%Counter-strafing
11.8°Preaim
647msReaction time
30.5%T opening success
39.1%CT opening success
0.47Enemies flashed / flash
4.2%Flash assists
4.78HE damage / grenade
8.45Flashes / 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 0.4719 — 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 30.503% — below the 40% mark we flag

Spend your practice time on Anubis

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.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust23–13-0.110%8 Oct →
inferno8–13-0.105%6 Oct →
mirage13–5-0.0318%6 Oct →
dust23–13-0.068%29 Sept →
anubis10–13-0.0016%26 Sept →
ancient16–13-0.0210%26 Sept →
anubis13–10-0.0318%24 Sept →
inferno13–60.0320%24 Sept →
inferno13–30.0018%9 Sept →
mirage3–13-0.0317%9 Sept →
mirage11–13-0.0214%27 Jun →
cache4–13-0.0614%27 Jun →
mirage11–13-0.0312%22 Jun →
inferno4–00.05100%22 Jun →
mirage3–13-0.0610%20 Jun →
mirage12–12-0.0711%8 Jun →
inferno13–40.0110%8 Jun →
nuke11–13-0.0314%8 Jun →
poseidon9–6-0.077%8 Jun →
mirage11–13-0.0320%6 Jun →
cache9–13-0.0512%7 May →
cache11–13-0.0420%7 May →
cache4–1-0.0440%7 May →
overpass3–13-0.0531%1 Feb →
nuke13–10-0.0525%5 Jan →
train13–9-0.0116%5 Jan →
train7–13-0.0310%3 Jan →
overpass13–60.0124%3 Jan →
overpass13–80.0018%2 Jan →
mirage9–13-0.0322%2 Jan →
train13–5-0.0518%2 Jan →
mirage13–10-0.0719%24 Dec →
nuke13–11-0.0529%24 Dec →
train8–13-0.109%26 Nov →
train10–13-0.0423%22 Nov →
train13–5-0.0111%3 Sept →
inferno7–13-0.0424%3 Sept →
mirage12–120.0212%22 Jun →
inferno3–130.000%4 Jun →
brewery6–90.0311%18 May →
dogtown8–8-0.0224%18 May →
grail12–120.0213%12 May →
inferno6–13-0.0312%14 Apr →
inferno7–13-0.0614%18 Mar →
mirage3–13-0.1119%15 Mar →
inferno7–13-0.074%17 Feb →
nuke10–13-0.0814%17 Feb →
train13–10-0.0814%8 Feb →
overpass13–11-0.1023%8 Feb →
train9–13-0.0517%6 Feb →
inferno12–12-0.0115%2 Feb →
mirage13–70.0011%2 Feb →
dust28–00.0630%2 Feb →
train7–13-0.0316%9 Jan →
inferno9–40.0725%8 Jan →
palais2–9-0.2011%8 Jan →
train5–130.0423%7 Jan →
anubis10–13-0.0818%7 Jan →
basalt4–20.1119%30 Dec →
edin13–70.0326%30 Dec →
dust23–130.0023%23 Dec →
vertigo12–12-0.0318%19 Dec →
basalt13–10-0.0314%16 Dec →
train13–8-0.0617%16 Dec →
vertigo2–130.0121%24 Aug →
mirage13–90.0316%24 Aug →
thera10–130.0011%22 Aug →
anubis4–13-0.104%22 Aug →
dust23–13-0.0810%28 Jul →
mirage10–130.0420%27 Jul →
assembly5–9-0.0511%13 Jul →
overpass9–7-0.0011%13 Jul →
anubis8–130.0113%5 Jul →
dust213–30.0014%5 Jul →
vertigo13–80.0318%4 Jul →
vertigo9–3-0.0223%3 Jul →
thera7–20.1150%3 Jul →
vertigo12–12-0.0127%30 Jun →
thera13–110.0030%30 Jun →
mills12–12-0.0621%30 Jun →
thera12–120.0623%27 Jun →
ancient13–60.0310%17 Jun →
dust213–70.0414%17 Jun →
ancient9–13-0.0421%17 Jun →
mirage4–13-0.0126%9 Jun →
vertigo2–13-0.1127%9 Jun →
mirage11–13-0.0426%8 Jun →
nuke9–50.1226%8 Jun →
dust213–20.1220%8 Jun →
anubis3–13-0.089%16 Mar →
overpass6–9-0.0417%11 Mar →
mirage13–80.0226%10 Mar →
mirage8–13-0.0514%29 Feb →
vertigo12–12-0.0516%4 Feb →
inferno11–3-0.0510%4 Feb →
overpass13–11-0.0417%4 Feb →
vertigo7–130.0322%3 Feb →
overpass11–130.0620%3 Feb →
vertigo4–9-0.0535%3 Feb →
overpass9–00.2110%31 Jan →

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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