1948 — CS2 Stats

76561198247444120[U:1:287178392]✓ No bans

3,536Tracked matches63%Win rate2021Tracked since
CSDB Rating6.5 SolidAggressive Rifler
FaceitLevel 9 · 1,477 ELOTop 20.7% of ranked FACEIT players
WingmanMaster Guardian Elite
Ladder ranks via Leetify

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CSDB.GG1948FACEITLevel 9 · 1,477 ELOSTANDINGTop 20.7% of rankedcsdb.gg/stats

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Performance scores

Aim91
Positioning57
Utility55

0–100 skill scores via Leetify.

Recent form

STEADY6436Last 10064%Win rateLLWWLLLWWL

Last 10 vs previous 10: -40pp win rate · -0.08 avg rating

Player DNA

Primary style: Aggressive RiflerTakes opening fights often, backed by a strong aim profile.

Aim9.1
Aggression9.3
Utility5.5
Positioning5.7
Opening Duels4.4
Clutch3.6

Sharp aimer

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

sh1ro

Plays most like sh1ro 95% playstyle similarity

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

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

Aim. Aim score of 91 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 34 points — deaths here waste a strong aim profile.

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

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

Aim9.1
Positioning5.7
Utility5.5
Mechanics7.4
Opening Duels4.4
Win Impact9.4

Composite 6.5/10 (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 rating0.05−0.04
first ⅓ avg 0.09 → last ⅓ avg 0.05
Reaction time487ms+36ms
first ⅓ avg 451ms → last ⅓ avg 487ms
Headshot accuracy26.5%+5.3%
first ⅓ avg 21.2% → last ⅓ avg 26.5%

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

0.36Best rating — cache 13–4
130Biggest win — cache
8Longest win streak
L2Current streak
33In matches decided by ≤2 rounds
2Overtime games

Map breakdown

mirageBest map · 82% over 11trainWeakest map · 36% over 11
MapGradePlayedRecordWin rateAvg rating
cacheS1613381%0.11
ancientB137654%0.04
dust2S128467%-0.00
trainC114736%0.01
mirageS119282%0.04
infernoS97278%0.07
anubisA95456%0.03
nukeS64267%-0.01
officeS64267%0.19
vertigo43175%0.13
overpass2020%-0.06
italy1010%0.18

Across the last 100 tracked matches.

Faceit stats

Combat

1,987Matches
51%Win rate
1.04Avg K/D
77.5ADR
47%Headshot %

Clutches & streaks

38%1v1 clutch win
21%1v2 clutch win
12Longest win streak

Recent Faceit resultsLWLLL

MapMatchesWin rateAvg K/DAvg kills
Ancient38253%1.0816.3
Anubis31856%1.0916.2
Dust229149%0.9715.1
Mirage25749%0.9815.0
Inferno19849%1.0215.2
Nuke14353%1.0716.0
Vertigo7946%0.9814.9
Overpass6743%0.9314.6

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.

23.2%Headshot accuracy
36.9%Accuracy (enemy spotted)
43.9%Spray accuracy
83.5%Counter-strafing
8.5°Preaim
499msReaction time
42.5%T opening success
53.0%CT opening success
0.51Enemies flashed / flash
10.6%Flash assists
13.16HE damage / grenade
12.19Flashes / match

Recommended for you

Spend your practice time on Train

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.

Train callouts & strategy

Recent matches

MapScoreRatingHS%Date
ancient10–13-0.0419%26 Aug
dust26–13-0.0420%19 Aug
train13–50.0517%8 Aug
cache13–11-0.0111%8 Aug
mirage9–13-0.0714%7 Aug
inferno2–13-0.085%7 Aug
nuke7–13-0.0324%31 Jul
cache13–00.2326%24 Jul
anubis13–40.0522%24 Jul
anubis3–13-0.0729%14 Jul
dust27–13-0.0422%14 Jul
inferno2–60.0625%14 Jul
cache13–40.0935%13 Jul
mirage13–70.0622%13 Jul
mirage2–00.13100%13 Jul
anubis13–00.1336%13 Jul
nuke13–50.1015%11 Jul
cache13–30.0943%11 Jul
inferno13–20.2023%11 Jul
inferno13–9-0.0123%10 Jul
dust20–4-0.100%10 Jul
office4–50.0747%9 Jul
anubis13–10.1735%6 Jul
ancient13–60.0822%5 Jul
office13–30.2040%5 Jul
ancient13–40.1323%4 Jul
anubis13–00.000%4 Jul
ancient13–90.0322%3 Jul
inferno13–10.0922%1 Jul
ancient5–13-0.0527%1 Jul
ancient13–60.1527%1 Jul
mirage13–4-0.0137%1 Jul
italy2–130.1842%23 Jun
cache3–11-0.0911%20 Jun
train0–13-0.330%20 Jun
train7–130.1016%20 Jun
train2–8-0.060%18 Jun
train7–130.0560%17 Jun
train13–70.0516%17 Jun
nuke13–5-0.0716%17 Jun
train6–130.0021%17 Jun
overpass8–13-0.089%16 Jun
mirage13–90.0736%10 Jun
inferno13–40.0120%10 Jun
office10–10.2435%10 Jun
dust213–60.0033%9 Jun
overpass4–9-0.0317%9 Jun
ancient3–13-0.0357%9 Jun
dust213–70.0229%9 Jun
mirage9–13-0.0012%8 Jun
vertigo13–40.2630%3 Jun
vertigo13–60.1419%3 Jun
vertigo6–13-0.030%3 Jun
dust213–8-0.0117%29 May
anubis4–13-0.0213%27 May
anubis6–1-0.0036%27 May
nuke13–40.0217%25 May
ancient13–90.0114%25 May
ancient9–13-0.0218%25 May
cache13–10.0336%24 May
nuke13–100.0020%23 May
cache13–60.1020%23 May
ancient9–13-0.0514%22 May
mirage16–120.0518%22 May
cache6–80.0631%20 May
train13–60.1528%16 May
mirage13–70.1111%15 May
ancient11–130.1215%13 May
dust213–70.0619%13 May
anubis7–13-0.0119%13 May
mirage13–60.0722%13 May
dust213–100.0322%13 May
office13–30.1530%13 May
office13–00.2827%13 May
vertigo13–70.1432%8 May
cache13–2-0.0124%8 May
cache13–100.1219%7 May
cache13–00.2227%7 May
nuke1–13-0.0612%5 May
inferno13–40.1817%5 May
ancient13–70.0820%5 May
office8–130.1927%2 May
cache13–40.3634%2 May
cache13–20.1917%30 Apr
cache13–30.1127%30 Apr
cache13–10.1122%30 Apr
cache8–130.1125%30 Apr
anubis8–130.0318%28 Apr
dust213–40.0926%27 Apr
ancient13–30.1313%27 Apr
dust24–13-0.0420%24 Apr
train13–70.0913%22 Apr
train4–130.0626%22 Apr
train9–13-0.0012%22 Apr
dust213–11-0.0711%21 Apr
dust213–100.0823%21 Apr
inferno16–130.1022%20 Apr
inferno7–00.0720%20 Apr
mirage13–10-0.0123%20 Apr
mirage13–90.0413%20 Apr

Match data via Leetify.

Milestones

1,000 MatchesAim 90+
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →