Jakefun — CS2 Stats

76561198049260583[U:1:88994855]✓ No bans

1,033Tracked matches52%Win rate2022Tracked since

826Hours in CS

CSDB Rating5.9 SolidPassive Rifler

FaceitLevel 5Top 67.6% 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

Positioning41

Utility67

0–100 skill scores via Leetify.

Recent form

COLD44–47–9Last 10044%Win rateTLTWLTLWLW

Last 10 vs previous 10: -20pp win rate · -0.01 avg rating

Player DNA

Primary style: Passive Rifler — Aim-led profile without a single dominant tendency.

Aim7.8

Aggression2.2

Utility6.7

Positioning4.1

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

Plays most like NiKo 83% playstyle similarity

Most alike: utility contribution, aim profile.

Where you differ: lower positioning profile; 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 36 points — deaths here waste a strong aim profile.

Reaction time. 602ms 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

Aim7.8

Positioning4.1

Utility6.7

Mechanics7.9

Opening Duels0.4

Win Impact5.6

Composite 5.9/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01−0.00

first ⅓ avg 0.01 → last ⅓ avg 0.01

Reaction time605ms−7ms

first ⅓ avg 612ms → last ⅓ avg 605ms

Headshot accuracy20.6%+2.2%

first ⅓ avg 18.4% → last ⅓ avg 20.6%

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

0.19Best rating — anubis 13–5

13–2Biggest win — ancient

5Longest win streak

8–3In matches decided by ≤2 rounds

5Overtime games

Map breakdown

cacheBest map · 63% over 16infernoWeakest map · 17% over 12

Map	Grade	Played	Record	Win rate	Avg rating
ancient	C	24	9–15	38%	0.01
cache	A	16	10–6	63%	0.00
nuke	B	15	8–7	53%	0.05
anubis	B	13	7–6	54%	0.02
inferno	D	12	2–10	17%	-0.00
dust2	C	10	4–6	40%	0.00
overpass	D	9	3–6	33%	0.00
mirage	—	1	1–0	100%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (17% over 12). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

38,227Lifetime kills

0.97K/D

2,160Matches

37.7%Match win rate

47.0%Headshot % · Top 50% of tracked players

11.6%Shot accuracy

3,682MVPs

826Hours (in match)

2,393Bombs planted

684Bombs defused

Most-used weapons

AK-4718,141

M4A4 / M4A1-S8,759

P2000 / USP-S1,715

Glock-181,605

Galil AR1,075

FAMAS1,060

MP91,030

P250577

MAC-10499

Five-SeveN480

Lifetime map wins

3,153dust2

2,448inferno

2,156nuke

677train

630vertigo

92office

32cbble

26aztec

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.

21.0%Headshot accuracy

37.5%Accuracy (enemy spotted)

38.5%Spray accuracy

85.4%Counter-strafing

10.7°Preaim

602msReaction time

22.9%T opening success

33.0%CT opening success

0.63Enemies flashed / flash

5.8%Flash assists

12.08HE damage / grenade

12.54Flashes / 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 22.8525% — 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.

17% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	15–15	-0.01	23%	9 Aug →
ancient	11–13	-0.00	25%	9 Aug →
cache	12–12	0.02	15%	9 Aug →
dust2	13–4	0.09	23%	8 Aug →
inferno	7–13	0.01	20%	8 Aug →
ancient	12–12	-0.05	17%	8 Aug →
dust2	6–13	0.02	25%	6 Aug →
cache	13–4	0.01	16%	2 Aug →
nuke	6–13	-0.02	27%	1 Aug →
ancient	13–11	0.00	22%	1 Aug →
cache	13–11	-0.03	9%	1 Aug →
inferno	13–5	-0.04	28%	1 Aug →
ancient	6–13	0.01	27%	1 Aug →
cache	16–14	0.02	25%	31 Jul →
nuke	9–13	-0.02	14%	30 Jul →
dust2	4–13	-0.09	13%	30 Jul →
nuke	13–6	0.10	16%	25 Jul →
inferno	3–13	0.00	16%	25 Jul →
inferno	9–13	-0.00	46%	25 Jul →
anubis	13–5	0.19	33%	24 Jul →
nuke	13–4	0.03	21%	24 Jul →
cache	13–7	0.05	19%	19 Jul →
dust2	2–13	-0.05	19%	18 Jul →
inferno	8–13	-0.01	25%	18 Jul →
ancient	13–5	0.06	13%	18 Jul →
anubis	13–11	0.09	24%	18 Jul →
ancient	13–11	0.02	23%	17 Jul →
ancient	13–2	-0.01	11%	15 Jul →
dust2	10–13	-0.03	13%	15 Jul →
cache	4–13	-0.02	19%	15 Jul →
ancient	11–13	-0.01	30%	12 Jul →
cache	5–13	-0.06	12%	12 Jul →
cache	5–13	-0.05	13%	12 Jul →
anubis	10–13	-0.01	29%	11 Jul →
cache	13–5	-0.04	54%	11 Jul →
inferno	1–13	-0.09	21%	11 Jul →
ancient	13–10	0.01	10%	11 Jul →
inferno	8–13	0.01	24%	10 Jul →
cache	13–10	0.04	32%	10 Jul →
ancient	13–3	0.08	22%	5 Jul →
cache	13–8	0.05	17%	5 Jul →
overpass	13–6	0.00	23%	5 Jul →
anubis	13–4	-0.01	8%	5 Jul →
dust2	3–13	-0.03	30%	4 Jul →
nuke	4–13	0.01	25%	4 Jul →
cache	13–7	0.01	26%	3 Jul →
ancient	7–13	0.09	22%	3 Jul →
anubis	13–4	0.02	29%	3 Jul →
cache	13–5	0.03	14%	3 Jul →
cache	13–9	0.06	32%	1 Jul →
anubis	13–11	0.04	16%	28 Jun →
anubis	10–13	0.05	19%	28 Jun →
ancient	10–13	-0.00	24%	28 Jun →
cache	12–12	-0.02	21%	27 Jun →
anubis	13–6	0.01	23%	27 Jun →
ancient	13–5	0.10	18%	27 Jun →
ancient	7–13	0.02	17%	26 Jun →
nuke	13–10	0.10	28%	26 Jun →
ancient	7–13	0.07	23%	21 Jun →
overpass	9–13	0.04	17%	17 Jun →
nuke	13–3	0.11	27%	17 Jun →
inferno	10–13	0.02	22%	14 Jun →
inferno	13–8	0.06	26%	14 Jun →
ancient	9–13	-0.01	16%	13 Jun →
overpass	4–13	-0.01	25%	13 Jun →
ancient	13–6	0.02	19%	13 Jun →
nuke	13–8	0.07	19%	13 Jun →
anubis	7–13	-0.00	22%	13 Jun →
inferno	4–13	-0.03	10%	13 Jun →
overpass	13–10	0.03	20%	13 Jun →
ancient	7–13	-0.02	36%	10 Jun →
dust2	13–5	0.07	23%	10 Jun →
dust2	5–13	0.01	34%	10 Jun →
dust2	13–11	0.03	13%	8 Jun →
nuke	13–3	0.02	13%	8 Jun →
overpass	12–12	-0.02	23%	5 Jun →
overpass	15–15	0.03	24%	5 Jun →
ancient	9–13	-0.01	16%	5 Jun →
anubis	4–13	-0.00	18%	5 Jun →
anubis	13–4	0.03	15%	31 May →
nuke	9–13	0.08	23%	31 May →
mirage	13–3	0.01	38%	31 May →
anubis	7–13	-0.01	15%	31 May →
inferno	7–13	-0.04	8%	28 May →
nuke	11–13	0.00	13%	28 May →
anubis	1–13	-0.11	20%	28 May →
ancient	15–15	-0.02	16%	27 May →
overpass	4–13	-0.07	21%	27 May →
ancient	6–13	-0.02	17%	27 May →
ancient	12–12	0.02	18%	26 May →
nuke	15–15	-0.02	24%	23 May →
inferno	8–13	0.07	12%	23 May →
ancient	13–6	-0.00	14%	23 May →
nuke	13–2	0.08	7%	23 May →
overpass	13–7	-0.03	11%	17 May →
nuke	13–11	0.13	23%	17 May →
ancient	8–13	0.01	23%	17 May →
dust2	13–5	-0.01	9%	16 May →
overpass	10–13	0.05	16%	16 May →
nuke	9–13	0.03	16%	16 May →