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almond man

almond man — CS2 Stats

76561198095814649[U:1:135548921]Steam profile ↗✓ No bans

735Tracked matches27%Win rate2020Tracked since
CSDB Rating2.9 Learning
Premier CS Rating6,732Light Blue band · top ~70.5% of ranked players (population est.)
CSDB Leaderboard#23642 of 31182 tracked
FaceitLevel 4Top 81.0% of ranked FACEIT players
WingmanGold Nova II
Ladder ranks via Leetify

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CSDB.GGalmond manFACEITLevel 4STANDINGTop 81.0% of rankedPREMIER6,732 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim43
Positioning35
Utility3

0–100 skill scores via Leetify.

Recent form

COLD42–56–2Last 10042%Win rateWLLLLLWLLL

Last 10 vs previous 10: -20pp win rate · -0.03 avg rating

Player DNA

Aim4.3
Aggression2.7
Utility0.3
Positioning3.5
Opening Duels0.8
Clutch0.0

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 66% playstyle similarity

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

Where you differ: lower aim profile; lower utility contribution.

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

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

Reaction time. 657ms 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

Aim4.3
Positioning3.5
Utility0.3
Mechanics6.9
Opening Duels1.2
Win Impact0.0

Composite 2.9/10 (Learning), 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 rating-0.03−0.04
first ⅓ avg 0.01 → last ⅓ avg -0.03
Reaction time656ms−39ms
first ⅓ avg 695ms → last ⅓ avg 656ms
Headshot accuracy12.1%−4.8%
first ⅓ avg 16.8% → last ⅓ avg 12.1%

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

0.22Best rating — nuke 9–5
13–2Biggest win — dust2
4Longest win streak
8–13In matches decided by ≤2 rounds
13Overtime games

Map breakdown

mirageBest map · 46% over 24infernoWeakest map · 38% over 13
MapGradePlayedRecordWin rateAvg rating
dust2C2712–1544%0.01
mirageB2411–1346%-0.01
infernoC135–838%-0.04
ancientC125–742%-0.02
cacheC94–544%0.01
nukeC83–538%0.01
anubis—41–325%0.03
office—21–150%-0.01
train—10–10%-0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 13). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

13Matches
38%Win rate
0.97Avg K/D
88.0ADR
52%Headshot %

Clutches & streaks

0%1v1 clutch win
0%1v2 clutch win
1Longest win streak

Recent Faceit resultsWLLWL

MapMatchesWin rateAvg K/DAvg kills
Inferno10%0.8113.0
Mirage10%0.8117.0
Anubis10%0.569.0
Nuke1100%1.3615.0

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.

12.0%Headshot accuracy
28.6%Accuracy (enemy spotted)
30.5%Spray accuracy
81.2%Counter-strafing
9.4°Preaim
657msReaction time
26.5%T opening success
39.6%CT opening success
0.03Enemies flashed / flash
0.0%Flash assists
2.53HE damage / grenade
0.32Flashes / 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. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 12.0172% — below the 15% mark we flag

    Aim Training →
  2. 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 0.0347 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 26.5197% — 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.

38% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage13–40.0219%28 Aug →
dust22–13-0.0727%28 Aug →
inferno10–13-0.0211%28 Aug →
ancient9–13-0.129%28 Aug →
mirage9–13-0.066%27 Aug →
dust27–13-0.053%27 Aug →
dust213–70.0314%27 Aug →
mirage7–13-0.0716%27 Aug →
inferno7–13-0.0831%27 Aug →
mirage9–130.0210%27 Aug →
cache10–130.1010%27 Aug →
dust27–13-0.0216%26 Aug →
dust216–13-0.0614%26 Aug →
cache14–16-0.058%26 Aug →
anubis6–13-0.039%21 Aug →
mirage16–13-0.0110%21 Aug →
dust25–80.077%21 Aug →
mirage5–13-0.047%21 Aug →
mirage16–14-0.038%20 Aug →
inferno13–30.0020%20 Aug →
anubis13–70.0813%20 Aug →
dust22–13-0.0413%20 Aug →
inferno13–16-0.093%18 Aug →
cache11–13-0.099%17 Aug →
ancient9–13-0.0712%17 Aug →
ancient7–130.0314%17 Aug →
train4–13-0.050%15 Aug →
dust213–6-0.0421%15 Aug →
cache8–13-0.0320%15 Aug →
ancient6–13-0.0410%15 Aug →
inferno13–7-0.132%15 Aug →
ancient13–8-0.017%14 Aug →
anubis11–130.0420%14 Aug →
mirage6–13-0.0611%14 Aug →
mirage13–110.0218%14 Aug →
dust210–13-0.0019%13 Aug →
mirage13–16-0.0117%13 Aug →
dust213–20.1227%13 Aug →
dust213–60.0011%13 Aug →
dust27–130.0415%13 Aug →
dust213–40.0111%13 Aug →
inferno6–9-0.099%12 Aug →
nuke13–100.0213%12 Aug →
dust216–130.0216%12 Aug →
dust25–13-0.1113%11 Aug →
mirage13–11-0.0112%11 Aug →
mirage7–13-0.068%11 Aug →
mirage13–4-0.0120%11 Aug →
ancient13–40.0312%11 Aug →
dust213–110.0410%11 Aug →
mirage13–8-0.0116%10 Aug →
cache11–130.0223%10 Aug →
ancient4–13-0.0418%10 Aug →
inferno5–90.0124%7 Aug →
nuke8–13-0.0312%7 Aug →
mirage13–10-0.0015%6 Aug →
cache13–50.0517%6 Aug →
ancient11–13-0.0212%6 Aug →
inferno15–15-0.0117%6 Aug →
nuke9–130.0518%4 Aug →
ancient13–8-0.0414%2 Aug →
mirage7–13-0.0314%29 Jul →
nuke3–13-0.0415%29 Jul →
dust214–160.0621%27 Jul →
dust210–13-0.0218%27 Jul →
ancient13–11-0.0113%27 Jul →
mirage13–70.1015%26 Jul →
mirage11–13-0.0216%26 Jul →
cache13–60.0017%25 Jul →
ancient13–100.0119%25 Jul →
cache13–60.0610%23 Jul →
mirage6–130.0420%23 Jul →
dust213–50.0413%23 Jul →
dust213–80.0013%21 Jul →
mirage5–13-0.025%21 Jul →
dust213–40.1013%21 Jul →
nuke6–130.0223%21 Jul →
inferno9–5-0.0216%21 Jul →
ancient0–13-0.0118%19 Jul →
cache13–70.0817%19 Jul →
nuke9–50.2220%19 Jul →
dust213–110.0224%18 Jul →
dust214–16-0.0019%18 Jul →
mirage11–130.0615%15 Jul →
inferno16–12-0.0116%14 Jul →
dust21–13-0.1019%14 Jul →
mirage13–6-0.0220%9 Jul →
nuke2–9-0.1411%7 Jul →
office4–13-0.0810%7 Jul →
office13–80.0721%7 Jul →
dust26–130.0525%7 Jul →
mirage11–13-0.0223%11 Jun →
inferno11–130.0122%10 Jun →
dust211–130.0717%10 Jun →
inferno16–14-0.0112%17 May →
anubis6–130.0125%17 May →
mirage13–8-0.037%17 May →
dust211–13-0.0124%14 May →
nuke13–11-0.0215%14 May →
inferno15–15-0.0314%14 May →

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 →

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