Frøslev — CS2 Stats

DK76561198035339225[U:1:75073497]Steam profile ↗

2,114Tracked matches37%Win rate2020Tracked since

CSDB Rating5.8 SolidSupport

FaceitLevel 10 · 3,312 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

Share this profile

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim78

Positioning47

Utility73

0–100 skill scores via Leetify.

Recent form

COLD46–54Last 10046%Win rateLLLLLLLWLL

Last 10 vs previous 10: -50pp win rate · -0.04 avg rating

Player DNA

Primary style: Support — Utility contribution leads the profile while opening activity stays low.

Aim7.8

Aggression0.5

Utility7.3

Positioning4.7

Opening Duels0.1

Clutch3.8

Strong CT-side opener

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 NiKo 80% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-duel success; lower 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

Areas to improve

Positioning. Positioning trails aim by 31 points — deaths here waste a strong aim profile.

T-side openings. Opening success drops from 46% on CT to 15% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim7.8

Positioning4.7

Utility7.3

Mechanics6.1

Opening Duels2.0

Win Impact0.6

Composite 5.8/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.01

first ⅓ avg -0.01 → last ⅓ avg -0.02

Reaction time498ms−8ms

first ⅓ avg 506ms → last ⅓ avg 498ms

Headshot accuracy19.0%+0.5%

first ⅓ avg 18.5% → last ⅓ avg 19.0%

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 — inferno 13–2

13–1Biggest win — nuke

9Longest win streak

L7Current streak

10–11In matches decided by ≤2 rounds

21Overtime games

Map breakdown

overpassBest map · 70% over 10ancientWeakest map · 29% over 21

Map	Grade	Played	Record	Win rate	Avg rating
nuke	A	23	14–9	61%	-0.00
ancient	D	21	6–15	29%	-0.02
inferno	C	17	7–10	41%	0.00
dust2	B	13	6–7	46%	-0.00
overpass	S	10	7–3	70%	0.00
train	C	7	3–4	43%	-0.02
anubis	—	4	2–2	50%	-0.06
cache	—	2	0–2	0%	-0.03
mirage	—	2	0–2	0%	-0.02
vertigo	—	1	1–0	100%	0.02

Across the last 100 tracked matches.

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

Faceit stats

Combat

7,229Matches

65%Win rate

1.28Avg K/D

83.4ADR

53%Headshot %

Clutches & streaks

39%1v1 clutch win

22%1v2 clutch win

46Longest win streak

Recent Faceit resultsLWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	262	60%	1.18	15.9
Nuke	206	66%	1.17	16.5
Inferno	100	58%	1.10	16.0
Dust2	94	53%	1.22	16.9
Anubis	84	50%	1.05	16.2
Train	82	51%	1.11	15.3
Vertigo	59	63%	1.19	16.5
Overpass	52	46%	1.18	15.8

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.

18.8%Headshot accuracy

37.1%Accuracy (enemy spotted)

41.2%Spray accuracy

77.6%Counter-strafing

11.3°Preaim

500msReaction time

15.0%T opening success

46.2%CT opening success

0.61Enemies flashed / flash

11.6%Flash assists

10.84HE damage / grenade

13.32Flashes / 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.

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 15.0093% — below the 40% mark we flag

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.

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

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	9–13	-0.02	19%	24 Aug →
ancient	6–13	-0.04	24%	24 Aug →
nuke	8–13	-0.06	14%	23 Aug →
ancient	9–13	-0.04	23%	23 Aug →
nuke	6–13	-0.02	28%	21 Aug →
cache	9–13	-0.03	22%	21 Aug →
dust2	3–13	-0.03	23%	21 Jun →
nuke	13–9	0.04	10%	13 Jun →
inferno	9–13	-0.02	23%	13 Jun →
ancient	10–13	-0.08	25%	13 Jun →
ancient	13–10	0.03	20%	13 Jun →
overpass	13–11	0.05	26%	13 Jun →
nuke	11–13	-0.04	19%	13 Jun →
nuke	16–14	0.08	12%	13 Jun →
dust2	13–11	0.01	15%	13 Jun →
overpass	13–10	0.01	22%	12 Jun →
ancient	13–16	-0.03	6%	12 Jun →
inferno	17–19	0.01	17%	12 Jun →
nuke	13–6	0.02	22%	12 Jun →
dust2	9–13	-0.04	17%	23 May →
inferno	16–14	-0.00	23%	23 May →
ancient	9–13	-0.02	15%	23 May →
nuke	11–13	-0.06	22%	20 May →
inferno	7–13	-0.08	15%	20 May →
ancient	13–11	0.04	22%	20 May →
nuke	13–9	-0.02	20%	19 May →
ancient	6–13	0.01	18%	19 May →
inferno	13–8	0.03	19%	19 May →
anubis	13–16	-0.09	10%	17 May →
ancient	8–13	-0.05	24%	17 May →
nuke	13–7	0.04	20%	17 May →
anubis	13–16	-0.09	10%	17 May →
ancient	8–13	-0.05	24%	17 May →
nuke	13–7	0.04	20%	17 May →
dust2	13–6	-0.02	16%	17 May →
overpass	13–10	-0.00	16%	17 May →
overpass	13–10	-0.00	16%	17 May →
dust2	13–6	-0.02	16%	17 May →
nuke	13–11	0.05	16%	16 May →
dust2	13–2	0.11	23%	16 May →
nuke	13–11	0.05	16%	16 May →
dust2	13–2	0.11	23%	16 May →
dust2	10–13	-0.03	22%	16 May →
inferno	4–13	-0.03	28%	16 May →
dust2	10–13	-0.03	22%	16 May →
anubis	13–9	-0.03	25%	16 May →
ancient	22–25	-0.02	17%	16 May →
nuke	19–16	-0.02	27%	16 May →
anubis	13–9	-0.03	25%	16 May →
ancient	22–25	-0.02	17%	16 May →
nuke	19–16	-0.02	27%	16 May →
ancient	3–13	-0.07	33%	15 May →
nuke	13–6	-0.01	21%	15 May →
nuke	13–9	-0.00	20%	15 May →
nuke	13–1	0.02	22%	15 May →
inferno	13–2	0.11	38%	15 May →
dust2	6–13	-0.06	28%	13 May →
inferno	8–13	-0.01	10%	13 May →
ancient	13–10	-0.03	18%	13 May →
inferno	13–9	0.01	41%	12 May →
ancient	7–13	-0.03	25%	12 May →
dust2	16–12	-0.01	22%	12 May →
overpass	11–13	-0.04	21%	18 Mar →
mirage	7–13	-0.03	16%	15 Feb →
nuke	1–13	-0.06	18%	15 Feb →
ancient	13–10	0.10	13%	29 Dec →
nuke	9–13	-0.04	20%	18 Nov →
dust2	10–13	-0.00	10%	17 Nov →
nuke	11–13	0.02	15%	17 Nov →
train	5–13	-0.05	16%	17 Nov →
inferno	16–13	-0.00	26%	17 Nov →
ancient	13–6	-0.02	17%	17 Nov →
train	13–7	0.03	20%	15 Nov →
inferno	17–19	0.01	18%	2 Nov →
train	5–13	-0.05	24%	2 Nov →
dust2	17–19	-0.00	15%	1 Nov →
inferno	11–13	0.03	26%	1 Nov →
nuke	14–9	-0.04	12%	1 Nov →
train	16–13	0.03	19%	1 Nov →
vertigo	13–11	0.02	16%	23 Oct →
inferno	13–16	0.04	23%	30 Sept →
overpass	16–14	0.01	21%	30 Sept →
ancient	1–13	-0.02	10%	30 Sept →
train	13–8	-0.04	24%	29 Sept →
inferno	13–9	0.02	28%	29 Sept →
ancient	5–13	-0.03	24%	29 Sept →
train	16–19	-0.03	23%	28 Sept →
ancient	13–11	-0.01	21%	28 Sept →
overpass	13–7	-0.01	13%	28 Sept →
overpass	8–13	-0.02	18%	26 Sept →
inferno	5–13	-0.05	18%	26 Sept →
overpass	7–13	-0.04	13%	14 Aug →
ancient	7–14	-0.00	27%	14 Aug →
inferno	13–7	0.00	18%	13 Aug →
nuke	11–13	0.02	13%	13 Aug →
overpass	13–7	0.05	20%	13 Aug →
train	7–13	-0.05	23%	11 Aug →
mirage	10–13	-0.01	18%	11 Aug →
nuke	14–16	0.01	12%	11 Aug →
inferno	11–13	-0.01	11%	1 Aug →