almonds #11 — CS2 Stats

76561197991130349[U:1:30864621]Steam profile ↗

1,271Tracked matches68%Win rate2023Tracked since

CSDB Rating5.7 Solid

Premier CS Rating22,416Top 50% of 17,162 CSDB-tracked playersPink band · top ~5.8% of ranked players (population est.)

CSDB Leaderboard#6608 of 23005 tracked

FaceitLevel 4 · 908 ELOTop 81.0% of ranked FACEIT players

Ladder ranks via Leetify

Rating over time

22,416Peak Premier on CSDB

908Peak Faceit ELO on CSDB

1Days observed since 2026-08-28

Faceit ELO

At peak — 908
Next: Level 5 at 1,051 — 143 to go
Reached: Level 4 · Level 3 · Level 2
Level 4 first seen 2026-08-28
Level 3 first seen 2026-08-28

Premier CS Rating

At peak — 22,416
Next: Red band at 25,000 — 2,584 to go
Reached: Pink band · Purple band · Blue band · Light Blue band
Pink band first seen 2026-08-28
Purple band first seen 2026-08-28

CSDB's own observations — this history builds from the day a profile is first viewed and cannot be backfilled.

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Performance scores

Aim49

Positioning61

Utility41

0–100 skill scores via Leetify.

Recent form

STEADY58–37–5Last 10058%Win rateLLWWLWWLWT

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

Player DNA

Aim4.9

Aggression7.2

Utility4.1

Positioning6.1

Opening Duels3.2

Clutch4.6

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

Plays most like b1t 86% playstyle similarity

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

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. 599ms 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

Aim4.9

Positioning6.1

Utility4.1

Mechanics6.2

Opening Duels3.2

Win Impact10.0

Composite 5.7/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00−0.01

first ⅓ avg 0.01 → last ⅓ avg 0.00

Reaction time595ms−19ms

first ⅓ avg 614ms → last ⅓ avg 595ms

Headshot accuracy12.5%+1.1%

first ⅓ avg 11.4% → last ⅓ avg 12.5%

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

0.16Best rating — anubis 13–2

13–0Biggest win — inferno

12Longest win streak

L2Current streak

11–7In matches decided by ≤2 rounds

7Overtime games

Map breakdown

ancientBest map · 89% over 9cacheWeakest map · 47% over 17

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	22	11–11	50%	0.01
nuke	S	20	14–6	70%	-0.00
cache	B	17	8–9	47%	-0.01
anubis	B	13	7–6	54%	0.01
dust2	B	12	6–6	50%	-0.02
ancient	S	9	8–1	89%	0.04
mirage	A	5	3–2	60%	0.00
train	—	2	1–1	50%	-0.04

Across the last 100 tracked matches.

Faceit stats

Combat

16Matches

38%Win rate

0.92Avg K/D

73.2ADR

37%Headshot %

Clutches & streaks

43%1v1 clutch win

22%1v2 clutch win

4Longest win streak

Recent Faceit resultsLLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	3	33%	1.00	13.0
Mirage	3	0%	0.83	16.7
Inferno	3	67%	0.71	13.0
Train	2	0%	0.90	17.0
Nuke	2	100%	1.10	16.0
Ancient	2	0%	0.94	15.0
Overpass	1	100%	1.22	11.0

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.

11.6%Headshot accuracy

31.1%Accuracy (enemy spotted)

32.1%Spray accuracy

78.1%Counter-strafing

10.0°Preaim

599msReaction time

40.6%T opening success

45.3%CT opening success

0.35Enemies flashed / flash

3.0%Flash assists

9.51HE damage / grenade

4.47Flashes / 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.

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 11.6211% — below the 15% mark we flag
Aim Training →
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 0.3515 — below the 0.5 mark we flag
Grenade Lineups →

Spend your practice time on Cache

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

47% win rate across 17 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
inferno	10–13	-0.05	6%	21 Aug →
nuke	11–13	-0.03	9%	17 Aug →
nuke	13–10	-0.01	6%	17 Aug →
nuke	13–10	-0.02	8%	17 Aug →
dust2	4–13	0.03	10%	14 Aug →
nuke	13–8	-0.01	12%	12 Aug →
inferno	13–4	0.09	8%	12 Aug →
inferno	8–13	-0.03	18%	12 Aug →
ancient	13–8	0.05	12%	11 Aug →
inferno	15–15	0.01	14%	11 Aug →
cache	7–13	-0.03	14%	11 Aug →
inferno	13–11	0.04	14%	11 Aug →
dust2	0–4	-0.15	33%	11 Aug →
dust2	9–13	-0.01	17%	9 Aug →
cache	13–8	-0.05	15%	9 Aug →
nuke	13–9	0.02	5%	9 Aug →
inferno	13–6	0.02	16%	9 Aug →
anubis	10–13	0.02	16%	9 Aug →
nuke	13–5	0.07	11%	8 Aug →
cache	11–13	-0.00	8%	8 Aug →
anubis	13–11	0.06	18%	8 Aug →
dust2	13–5	0.02	10%	8 Aug →
cache	13–8	0.03	8%	7 Aug →
nuke	13–6	0.02	20%	7 Aug →
inferno	13–9	0.02	13%	7 Aug →
ancient	13–9	0.02	13%	7 Aug →
cache	15–15	-0.02	8%	6 Aug →
mirage	13–10	-0.02	6%	5 Aug →
train	13–7	-0.01	12%	5 Aug →
inferno	16–13	0.03	7%	4 Aug →
nuke	13–9	0.03	21%	3 Aug →
mirage	7–13	-0.00	10%	3 Aug →
inferno	5–13	-0.03	12%	3 Aug →
nuke	11–13	-0.04	14%	3 Aug →
ancient	13–2	0.07	15%	3 Aug →
anubis	13–10	-0.05	11%	3 Aug →
anubis	13–8	0.03	8%	3 Aug →
ancient	13–8	0.01	17%	2 Aug →
mirage	13–9	-0.00	10%	2 Aug →
dust2	10–13	-0.03	15%	2 Aug →
dust2	9–13	-0.04	15%	2 Aug →
nuke	3–13	-0.03	15%	2 Aug →
dust2	13–11	-0.01	10%	2 Aug →
inferno	10–13	0.02	13%	1 Aug →
cache	2–13	-0.09	5%	1 Aug →
dust2	13–11	-0.04	12%	1 Aug →
anubis	5–13	0.02	13%	1 Aug →
nuke	13–11	-0.04	8%	29 Jul →
inferno	12–16	-0.06	16%	29 Jul →
anubis	7–13	-0.01	8%	29 Jul →
inferno	9–13	0.01	12%	27 Jul →
ancient	8–13	-0.00	9%	27 Jul →
cache	9–13	-0.03	11%	27 Jul →
nuke	10–13	-0.06	13%	27 Jul →
inferno	10–13	0.03	9%	27 Jul →
cache	13–5	-0.01	9%	27 Jul →
inferno	13–7	0.01	4%	27 Jul →
nuke	13–4	0.06	10%	26 Jul →
cache	11–13	0.00	12%	26 Jul →
ancient	13–6	0.08	3%	26 Jul →
anubis	5–13	-0.07	11%	26 Jul →
nuke	13–9	-0.05	21%	26 Jul →
cache	13–10	-0.00	14%	25 Jul →
inferno	13–10	0.01	10%	25 Jul →
anubis	13–11	-0.03	7%	25 Jul →
dust2	13–7	-0.02	12%	25 Jul →
dust2	13–10	-0.00	14%	25 Jul →
cache	13–1	0.08	7%	25 Jul →
anubis	13–10	0.01	16%	24 Jul →
nuke	13–11	-0.01	15%	23 Jul →
inferno	13–11	-0.01	11%	23 Jul →
nuke	13–10	0.01	8%	21 Jul →
anubis	13–10	-0.01	12%	21 Jul →
dust2	10–13	0.02	15%	21 Jul →
inferno	15–15	0.03	11%	20 Jul →
nuke	10–13	-0.00	15%	20 Jul →
cache	13–8	0.01	12%	20 Jul →
nuke	13–7	-0.02	19%	20 Jul →
inferno	13–0	0.13	20%	20 Jul →
ancient	13–5	0.05	14%	20 Jul →
inferno	13–7	0.01	3%	20 Jul →
anubis	0–13	-0.04	4%	20 Jul →
nuke	15–15	0.01	13%	20 Jul →
inferno	13–11	0.06	12%	19 Jul →
ancient	13–8	0.03	15%	19 Jul →
cache	6–13	-0.01	5%	19 Jul →
mirage	11–13	0.01	15%	18 Jul →
cache	13–6	0.02	15%	18 Jul →
inferno	8–13	0.01	9%	17 Jul →
mirage	13–10	0.02	8%	17 Jul →
inferno	5–13	-0.07	18%	17 Jul →
cache	16–14	0.04	13%	17 Jul →
train	12–12	-0.06	10%	15 Jul →
ancient	13–6	0.03	8%	15 Jul →
nuke	13–11	0.07	11%	15 Jul →
anubis	11–13	-0.00	11%	15 Jul →
anubis	13–2	0.16	10%	15 Jul →
cache	6–13	-0.08	5%	15 Jul →
dust2	13–9	0.00	13%	14 Jul →
cache	11–13	-0.02	3%	14 Jul →