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πšˆπŸΊπ™Ίπš„πš‰πŸΊ

πšˆπŸΊπ™Ίπš„πš‰πŸΊ β€” CS2 Stats

BR76561198154390187[U:1:194124459]Steam profile β†—βœ“ No bans

302Tracked matches57%Win rate2021Tracked since
2,193Hours in CS16Hrs last 2 wks
CSDB Rating5.9 SolidHybrid Rifler
Premier CS Rating22,256Top 50% of 17,162 CSDB-tracked playersPink band Β· top ~6% of ranked players (population est.)
CSDB Leaderboard#9221 of 33382 tracked
Ladder ranks via Leetify

How this compares with the same rank

Median values for Pink band among CSDB-tracked players (n=3,917), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here β€” those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerPink band medianRed band medianvs Red band
Headshot rate42.1%47.2%49.9%7.8% short
Shot accuracy10.2%12.7%13.4%3.1% short
Kill/death ratio0.811.091.120.31 short
Match win rate37.1%46.6%48.4%11.3% short

This profile sits below the typical Red band player on every metric we can compare.

Widest gap: Kill/death ratio. That is the metric furthest from the Red band median in relative terms β€” not necessarily the one holding a rank back, which no statistic here can establish.

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CSDB.GGπšˆπŸΊπ™Ίπš„πš‰πŸΊPREMIER22,256 Β· Pink bandcsdb.gg/stats

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Performance scores

Aim68
Positioning48
Utility63

0–100 skill scores via Leetify.

Recent form

STEADY60–35–5Last 10060%Win rateWLLWLLWLLW

Last 10 vs previous 10: -20pp win rate Β· +0.04 avg rating

Player DNA

Primary style: Hybrid Rifler β€” Aim-led profile without a single dominant tendency.

Aim6.8
Aggression6.4
Utility6.3
Positioning4.8
Opening Duels1.9

Effective flashes

Style profile from tracked-match aggregates β€” how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

NiKo

Plays most like NiKo 89% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: higher opening-fight frequency; lower aim profile.

Similarity of playstyle shape across shared dimensions β€” it says how you play, not that you play at their level. Full comparison β†’

Strengths & areas to improve

Areas to improve

Reaction time. 570ms from enemy-visible to first shot leaves fights decided before they start β€” warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers β€” no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim6.8
Positioning4.8
Utility6.3
Mechanics5.9
Opening Duels1.9
Win Impact7.2

Composite 5.9/10 (Solid), a weighted mean of the bars with a small opposition adjustment (Γ—1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.00βˆ’0.02
first β…“ avg 0.01 β†’ last β…“ avg -0.00
Reaction time575msβˆ’43ms
first β…“ avg 618ms β†’ last β…“ avg 575ms
Headshot accuracy14.4%βˆ’2.8%
first β…“ avg 17.2% β†’ last β…“ avg 14.4%

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.

Highlights

0.12Best rating β€” dust2 13–3
13–2Biggest win β€” cache
7Longest win streak
9–4In matches decided by ≀2 rounds
16Overtime games

Map breakdown

infernoBest map Β· 72% over 29ancientWeakest map Β· 45% over 11
MapGradePlayedRecordWin rateAvg rating
infernoS2921–872%-0.00
dust2A2011–955%0.01
mirageA1710–759%-0.01
cacheA127–558%0.01
ancientB115–645%-0.01
anubisβ€”42–250%0.01
overpassβ€”43–175%0.06
nukeβ€”31–233%0.00

Across the last 100 tracked matches.

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

Lifetime stats

57,836Lifetime kills
0.81K/D
3,252Matches
37.1%Match win rate
42.1%Headshot %
10.2%Shot accuracy
5,079MVPs
1,246Hours (in match)
2,781Bombs planted
792Bombs defused

Most-used weapons

AK-4719,567
M4A4 / M4A1-S11,426
AWP7,299
Desert Eagle3,120
P2000 / USP-S2,733
Glock-182,335
MAC-101,649
MP91,245
Galil AR1,170
FAMAS788

Lifetime map wins

5,873dust2
5,466inferno
1,308nuke
570train
387vertigo
376office
18lake
14ar_shoots

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

Skill profile

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

14.3%Headshot accuracy
36.6%Accuracy (enemy spotted)
41.5%Spray accuracy
76.6%Counter-strafing
10.6Β°Preaim
570msReaction time
33.7%T opening success
41.5%CT opening success
0.74Enemies flashed / flash
6.8%Flash assists
8.33HE damage / grenade
6.49Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag β€” 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 β€” usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 14.3311% β€” below the 15% mark we flag

    Aim Training β†’
  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 33.6893% β€” below the 40% mark we flag

Spend your practice time on Ancient

Map knowledge compounds faster than mechanics β€” lineups and callouts you learn once keep paying out every time the map comes up.

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

Ancient callouts & strategy β†’Ancient grenade lineups β†’

Recent matches

MapScoreRatingHS%Date
inferno13–110.0129%26 Aug β†’
dust29–13-0.0220%26 Aug β†’
dust211–130.0324%25 Aug β†’
inferno13–70.0313%24 Aug β†’
ancient11–13-0.033%24 Aug β†’
mirage10–130.0319%24 Aug β†’
inferno13–110.0110%23 Aug β†’
inferno11–13-0.0215%22 Aug β†’
cache9–13-0.0218%22 Aug β†’
dust213–90.0612%21 Aug β†’
inferno16–14-0.0011%20 Aug β†’
ancient5–13-0.0011%20 Aug β†’
inferno13–5-0.0618%20 Aug β†’
mirage9–13-0.047%16 Aug β†’
ancient9–13-0.0512%13 Aug β†’
ancient13–10-0.0518%13 Aug β†’
dust213–11-0.0215%13 Aug β†’
dust211–13-0.0311%12 Aug β†’
cache13–7-0.0211%11 Aug β†’
inferno13–5-0.0519%10 Aug β†’
inferno13–16-0.0315%10 Aug β†’
cache13–110.0114%10 Aug β†’
cache13–8-0.077%10 Aug β†’
cache16–120.0620%9 Aug β†’
dust213–30.1210%9 Aug β†’
inferno13–80.0013%9 Aug β†’
ancient16–13-0.014%9 Aug β†’
anubis10–130.0017%8 Aug β†’
cache5–13-0.0718%8 Aug β†’
inferno13–90.0518%4 Aug β†’
anubis13–80.0812%4 Aug β†’
anubis6–13-0.0416%3 Aug β†’
cache13–160.0216%3 Aug β†’
mirage13–6-0.0210%2 Aug β†’
inferno13–7-0.0118%2 Aug β†’
dust216–14-0.0124%2 Aug β†’
mirage12–160.0113%1 Aug β†’
inferno13–100.0411%31 Jul β†’
inferno8–13-0.0222%31 Jul β†’
inferno10–13-0.0413%29 Jul β†’
dust210–13-0.0322%28 Jul β†’
mirage13–9-0.0221%27 Jul β†’
inferno16–140.0417%26 Jul β†’
mirage15–15-0.0117%26 Jul β†’
dust213–16-0.0110%23 Jul β†’
dust210–13-0.0311%22 Jul β†’
inferno13–10-0.0320%21 Jul β†’
mirage13–6-0.0224%19 Jul β†’
cache13–20.0032%19 Jul β†’
dust24–130.0013%19 Jul β†’
mirage10–13-0.069%19 Jul β†’
ancient13–60.0323%19 Jul β†’
mirage9–130.0011%18 Jul β†’
inferno13–9-0.0523%18 Jul β†’
dust213–10-0.0426%16 Jul β†’
ancient5–130.0239%16 Jul β†’
nuke13–40.0220%15 Jul β†’
inferno13–40.0631%14 Jul β†’
inferno13–80.0520%14 Jul β†’
inferno15–150.029%13 Jul β†’
cache9–13-0.0325%13 Jul β†’
dust213–2-0.0217%13 Jul β†’
inferno13–100.0314%12 Jul β†’
inferno10–13-0.0315%5 Jul β†’
nuke9–13-0.0322%5 Jul β†’
mirage13–60.0110%5 Jul β†’
mirage13–7-0.0323%5 Jul β†’
ancient13–20.0720%1 Jul β†’
ancient10–13-0.0111%28 Jun β†’
mirage13–5-0.0121%27 Jun β†’
overpass13–30.0313%27 Jun β†’
mirage8–13-0.0621%27 Jun β†’
inferno13–6-0.056%23 Jun β†’
inferno13–30.0120%23 Jun β†’
inferno2–13-0.119%22 Jun β†’
ancient16–13-0.0111%21 Jun β†’
mirage13–80.0417%21 Jun β†’
inferno13–80.0216%21 Jun β†’
overpass13–30.0910%14 Jun β†’
mirage13–80.0525%14 Jun β†’
dust213–60.0822%14 Jun β†’
overpass13–60.1121%14 Jun β†’
overpass15–15-0.0110%14 Jun β†’
ancient7–13-0.0718%10 Jun β†’
dust213–8-0.0315%9 Jun β†’
dust213–11-0.0021%9 Jun β†’
dust213–70.0621%9 Jun β†’
inferno15–15-0.0019%8 Jun β†’
dust29–13-0.0413%2 Jun β†’
inferno13–20.0611%19 May β†’
cache12–120.0918%18 May β†’
cache13–40.1118%18 May β†’
anubis16–130.0125%17 May β†’
mirage13–60.0115%17 May β†’
inferno13–90.0114%17 May β†’
dust28–130.0126%16 May β†’
nuke6–130.0228%16 May β†’
cache13–50.0115%7 May β†’
mirage16–14-0.0320%7 May β†’
dust213–100.0417%7 May β†’

Match data via Leetify.

Recent teammates

Milestones

100 Matches
Compare this player with someone β†’Inventory value for this account β†’Where does this rating sit? Premier rank tiers β†’

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