♥ E L E P H A N T ♥

♥ E L E P H A N T ♥ — CS2 Stats

CC76561198312642006[U:1:352376278]Steam profile ↗

1,361Tracked matches48%Win rate2021Tracked since
1,205Hours in CS
CSDB Rating3.8 Learning
Premier CS Rating14,485Blue band · top ~31.1% of ranked players (population est.)
CSDB Leaderboard#19833 of 30940 tracked
WingmanGold Nova Master
Ladder ranks via Leetify

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=1,240), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerBlue band medianPurple band medianvs Purple band
Headshot rate45.5%41.7%44.1%above
Shot accuracy8.9%8.8%11.4%2.5% short
Kill/death ratio0.730.971.030.30 short
Match win rate42.3%43.8%45.2%2.9% short

This profile matches the typical Purple band player on 1 of 4 comparable metrics.

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

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Performance scores

Aim48
Positioning45
Utility58

0–100 skill scores via Leetify.

Recent form

STEADY42544Last 10042%Win rateLLLWLWWWWL

Last 10 vs previous 10: +0pp win rate · -0.01 avg rating

Player DNA

Aim4.8
Aggression4.7
Utility5.8
Positioning4.5
Opening Duels1.1

Style profile from tracked-match aggregates — 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 85% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: lower positioning profile; 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. 557ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 58% 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

Aim4.8
Positioning4.5
Utility5.8
Mechanics1.8
Opening Duels1.1
Win Impact4.4

Composite 3.8/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02+0.01
first ⅓ avg -0.02 → last ⅓ avg -0.02
Reaction time562ms−50ms
first ⅓ avg 611ms → last ⅓ avg 562ms
Headshot accuracy19.3%−1.2%
first ⅓ avg 20.5% → last ⅓ avg 19.3%

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.

Highlights

0.11Best rating — dust2 13–2
131Biggest win — dust2
4Longest win streak
L3Current streak
810In matches decided by ≤2 rounds
9Overtime games

Map breakdown

ancientBest map · 53% over 17infernoWeakest map · 29% over 21
MapGradePlayedRecordWin rateAvg rating
dust2C39172244%-0.02
infernoD2161529%-0.03
ancientB179853%-0.01
anubisB126650%-0.01
cache41325%-0.06
overpass330100%0.01
mirage2020%-0.03
nuke1010%-0.04
vertigo1010%-0.09

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 21). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

38,153Lifetime kills
0.73K/D
2,715Matches
42.3%Match win rate
45.5%Headshot % · Top 50% of Blue band
8.9%Shot accuracy · Top 50% of Blue band
3,924MVPs
1,205Hours (in match)
2,604Bombs planted
488Bombs defused

Most-used weapons

Lifetime map wins

9,364inferno
9,041dust2
272train
149nuke
134vertigo
7lake
6italy
3cbble

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

Faceit stats

Combat

9Matches
44%Win rate
0.59Avg K/D
ADR
32%Headshot %

Clutches & streaks

1v1 clutch win
1v2 clutch win
3Longest win streak

Recent Faceit resultsLWWWL

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.

19.5%Headshot accuracy
29.2%Accuracy (enemy spotted)
32.0%Spray accuracy
58.1%Counter-strafing
9.1°Preaim
557msReaction time
32.8%T opening success
35.6%CT opening success
0.58Enemies flashed / flash
6.6%Flash assists
7.75HE damage / grenade
11.56Flashes / 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

    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 32.8241% — 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.

29% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
dust21–13-0.0930%29 Aug
cache10–13-0.0615%29 Aug
inferno9–13-0.0018%16 Aug
dust213–6-0.0019%16 Aug
ancient5–130.1014%16 Aug
ancient13–90.0116%15 Aug
dust213–110.0232%15 Aug
inferno13–11-0.0415%29 Jul
ancient13–9-0.0214%26 Jul
inferno2–13-0.049%26 Jul
dust28–130.0032%26 Jul
inferno13–9-0.0419%25 Jul
dust27–13-0.0135%25 Jul
ancient13–110.0411%25 Jul
dust28–13-0.0210%25 Jul
dust213–3-0.0611%25 Jul
dust29–13-0.0320%24 Jul
dust213–110.0033%24 Jul
inferno7–13-0.0113%22 Jul
anubis13–100.0823%22 Jul
ancient13–10-0.0021%22 Jul
inferno8–13-0.0221%19 Jul
inferno8–130.0126%19 Jul
dust213–8-0.039%19 Jul
inferno15–15-0.0225%19 Jul
anubis2–13-0.067%19 Jul
anubis9–130.0111%18 Jul
cache7–13-0.0723%18 Jul
ancient13–5-0.0316%17 Jul
dust213–5-0.0629%14 Jul
inferno13–16-0.0319%14 Jul
dust212–16-0.0424%14 Jul
ancient13–11-0.0615%13 Jul
dust213–10-0.0219%13 Jul
cache6–13-0.107%12 Jul
inferno8–13-0.0313%12 Jul
dust213–7-0.0123%12 Jul
ancient11–130.0020%12 Jul
dust213–9-0.0124%12 Jul
anubis15–15-0.0313%11 Jul
dust27–13-0.0421%8 Jul
ancient3–13-0.0925%6 Jul
anubis13–20.0224%3 Jul
dust213–100.0124%3 Jul
dust213–20.1123%28 Jun
dust28–13-0.0726%28 Jun
anubis15–15-0.0614%28 Jun
dust213–80.0223%28 Jun
dust29–13-0.0322%27 Jun
ancient13–6-0.0515%27 Jun
inferno11–13-0.0518%27 Jun
anubis10–130.0110%27 Jun
inferno13–11-0.0419%27 Jun
dust211–13-0.0412%27 Jun
anubis13–10-0.0123%26 Jun
dust213–10.0421%26 Jun
inferno11–130.0416%20 Jun
dust26–13-0.0521%20 Jun
inferno3–13-0.0831%20 Jun
dust210–13-0.0511%14 Jun
mirage12–12-0.0513%12 Jun
nuke7–13-0.0418%12 Jun
dust26–13-0.1333%12 Jun
ancient13–7-0.0032%5 Jun
vertigo8–13-0.0914%5 Jun
dust213–11-0.0123%5 Jun
inferno13–100.0226%31 May
ancient11–13-0.0224%31 May
dust213–60.0723%31 May
mirage9–13-0.0017%23 May
dust211–130.0126%23 May
anubis13–90.0613%23 May
inferno5–13-0.0521%10 May
dust20–13-0.0720%10 May
inferno13–80.0222%10 May
ancient3–13-0.1023%10 May
ancient10–13-0.0214%8 May
inferno2–13-0.128%8 May
dust211–13-0.0325%8 May
cache13–11-0.0116%2 May
dust29–13-0.0018%2 May
inferno13–10-0.0425%2 May
overpass13–9-0.0118%29 Apr
dust211–13-0.0516%29 Apr
anubis16–13-0.0323%26 Apr
inferno13–16-0.0417%26 Apr
overpass13–100.0114%26 Apr
dust210–130.0117%26 Apr
ancient13–30.0421%25 Apr
overpass13–50.0338%25 Apr
anubis13–10-0.0626%20 Apr
inferno1–13-0.0730%20 Apr
dust214–16-0.0220%20 Apr
dust27–13-0.0623%20 Apr
dust26–13-0.0524%20 Apr
dust213–6-0.0531%18 Apr
ancient7–13-0.068%18 Apr
ancient9–130.0216%15 Apr
anubis11–13-0.0723%15 Apr
dust216–12-0.0217%14 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 →