Space-Man Gympy

Space-Man Gympy — CS2 Stats

US76561197967768699[U:1:7502971]Steam profile ↗

799Tracked matches40%Win rate2020Tracked since
2,623Hours in CS5Hrs last 2 wks
CSDB Rating3.2 Learning
Premier CS Rating10,019Blue band · top ~54.8% of ranked players (population est.)
CSDB Leaderboard#24829 of 34228 tracked
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 rate36.9%41.7%44.1%7.2% short
Shot accuracy15.5%8.8%11.4%above
Kill/death ratio0.910.971.030.12 short
Match win rate64.4%43.8%45.2%above

This profile matches the typical Purple band player on 2 of 4 comparable metrics.

Widest gap: Headshot rate. 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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CSDB.GGSpace-Man GympyPREMIER10,019 · Blue bandcsdb.gg/stats

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Performance scores

Aim33
Positioning39
Utility38

0–100 skill scores via Leetify.

Recent form

STEADY46531Last 10046%Win rateLWWWLWLLLL

Last 10 vs previous 10: -20pp win rate · +0.00 avg rating

Player DNA

Aim3.3
Aggression3.0
Utility3.8
Positioning3.9
Opening Duels0.0

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 71% playstyle similarity

Most alike: opening-fight frequency, opening-duel success.

Where you differ: lower utility contribution; 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. 670ms 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

Aim3.3
Positioning3.9
Utility3.8
Mechanics5.4
Opening Duels0.1
Win Impact1.7

Composite 3.2/10 (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+0.02
first ⅓ avg -0.03 → last ⅓ avg -0.02
Reaction time667ms−31ms
first ⅓ avg 698ms → last ⅓ avg 667ms
Headshot accuracy16.4%+4.4%
first ⅓ avg 12.0% → last ⅓ avg 16.4%

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

0.09Best rating — dust2 13–6
131Biggest win — cache
5Longest win streak
79In matches decided by ≤2 rounds
8Overtime games

Map breakdown

anubisBest map · 60% over 5ancientWeakest map · 36% over 11
MapGradePlayedRecordWin rateAvg rating
mirageC25101540%-0.03
dust2C2081240%-0.02
infernoA169756%-0.04
nukeB147750%-0.04
ancientC114736%-0.00
cacheA74357%-0.01
anubisA53260%0.02
overpass1010%-0.01
train110100%0.03

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (36% over 11). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

71,020Lifetime kills
0.91K/D
8,624Matches
64.4%Match win rate · Top 5% of Blue band
36.9%Headshot %
15.5%Shot accuracy · Top 25% of Blue band
5,822MVPs
1,474Hours (in match)
4,292Bombs planted
716Bombs defused

Most-used weapons

AK-4717,907
P903,434
AWP2,871
FAMAS2,480
SG 5532,150
P2502,063
AUG1,743

Lifetime map wins

5,602inferno
4,563dust2
3,400nuke
1,386office
1,071train
659vertigo
223lake
170militia

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.

15.7%Headshot accuracy
28.9%Accuracy (enemy spotted)
35.4%Spray accuracy
74.2%Counter-strafing
13.4°Preaim
670msReaction time
22.2%T opening success
30.9%CT opening success
0.61Enemies flashed / flash
6.8%Flash assists
7.83HE damage / grenade
4.69Flashes / 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 13.4352° — above the 12° mark we flag

    Aim Training
Spend your practice time on Ancient

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

36% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
dust29–13-0.0532%25 Aug
mirage13–30.007%17 Aug
anubis13–11-0.0114%17 Aug
mirage13–9-0.0719%15 Aug
anubis8–13-0.0313%15 Aug
inferno13–9-0.0127%15 Aug
nuke8–13-0.0312%15 Aug
dust27–130.0024%15 Aug
ancient5–130.0110%15 Aug
dust23–13-0.0617%13 Aug
mirage13–11-0.0413%13 Aug
nuke13–50.0311%12 Aug
inferno13–5-0.0615%12 Aug
dust210–13-0.0412%9 Aug
mirage13–30.0416%8 Aug
inferno3–13-0.038%8 Aug
dust216–12-0.0223%8 Aug
nuke8–13-0.0213%8 Aug
cache10–13-0.067%8 Aug
mirage13–9-0.0616%8 Aug
inferno9–13-0.0814%8 Aug
cache10–13-0.0510%1 Aug
nuke8–13-0.0116%1 Aug
dust211–130.0115%27 Jul
anubis13–70.0611%27 Jul
ancient0–40.0240%26 Jul
mirage5–13-0.0521%26 Jul
cache13–10.0220%26 Jul
inferno7–13-0.0117%26 Jul
dust25–13-0.0013%25 Jul
mirage3–130.0128%25 Jul
mirage16–13-0.0214%23 Jul
ancient13–4-0.0515%23 Jul
inferno13–11-0.0413%23 Jul
mirage0–13-0.0717%13 Jul
mirage9–13-0.086%12 Jul
cache3–130.0519%12 Jul
dust213–6-0.004%12 Jul
ancient14–16-0.0114%12 Jul
mirage14–16-0.055%12 Jul
cache13–5-0.0213%12 Jul
dust24–13-0.0212%11 Jul
nuke13–8-0.0415%11 Jul
dust24–13-0.1314%11 Jul
inferno13–8-0.066%11 Jul
cache13–50.0119%11 Jul
ancient13–20.0616%11 Jul
inferno11–13-0.0915%11 Jul
cache13–30.0111%11 Jul
mirage13–50.0417%11 Jul
inferno13–9-0.0213%10 Jul
mirage10–130.0113%9 Jul
mirage11–130.0528%6 Jul
dust29–13-0.0513%6 Jul
nuke13–7-0.0416%6 Jul
dust213–60.0923%6 Jul
mirage7–130.078%6 Jul
dust213–30.029%6 Jul
overpass12–16-0.0112%5 Jul
anubis13–110.0013%4 Jul
inferno10–13-0.098%4 Jul
inferno13–9-0.0212%3 Jul
ancient13–80.066%3 Jul
ancient11–130.0216%3 Jul
nuke2–13-0.0822%3 Jul
mirage2–13-0.088%19 Jun
mirage15–15-0.0210%19 Jun
inferno11–13-0.0417%19 Jun
ancient5–13-0.0611%19 Jun
inferno6–13-0.0610%17 Jun
nuke6–13-0.086%17 Jun
mirage3–13-0.0730%17 Jun
dust213–100.0315%17 Jun
ancient14–16-0.038%14 Jun
mirage4–13-0.099%14 Jun
dust27–13-0.0814%14 Jun
nuke13–100.037%14 Jun
inferno13–8-0.0313%13 Jun
dust213–20.0615%13 Jun
ancient13–6-0.0227%13 Jun
inferno13–8-0.0312%13 Jun
mirage8–13-0.048%13 Jun
mirage13–3-0.0210%7 Jun
dust213–5-0.0212%7 Jun
anubis11–130.066%7 Jun
mirage8–13-0.029%7 Jun
nuke13–16-0.0113%7 Jun
dust210–13-0.024%7 Jun
dust213–9-0.0317%26 May
ancient5–13-0.048%25 May
dust27–13-0.0214%25 Apr
nuke13–11-0.1412%11 Apr
mirage13–11-0.1016%11 Apr
nuke10–13-0.0717%4 Apr
train13–60.0313%29 Mar
mirage13–3-0.027%29 Mar
mirage9–13-0.0612%28 Mar
nuke13–4-0.064%25 Mar
nuke13–6-0.069%17 Mar
inferno13–11-0.0413%17 Mar

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 →