Jess — CS2 Stats

CH76561199027487094[U:1:1067221366]Steam profile ↗✓ No bans

3,304Tracked matches52%Win rate2021Tracked since

4,302Hours in CS18Hrs last 2 wks

CSDB Rating5.0 Developing

Premier CS Rating12,949Blue band · top ~39.3% of ranked players (population est.)

CSDB Leaderboard#40034 of 60714 tracked

WingmanMaster Guardian Elite

Ladder ranks via Leetify

Rating over time

12,949Peak Premier on CSDB

1,049Peak Faceit ELO on CSDB

1Days observed since 2026-08-30

Faceit ELO

At peak — 1,049
Next: Level 5 at 1,051 — 2 to go
Reached: Level 4 · Level 3 · Level 2
Level 4 first seen 2026-08-30
Level 3 first seen 2026-08-30

Premier CS Rating

At peak — 12,949
Next: Purple band at 15,000 — 2,051 to go
Reached: Blue band · Light Blue band
Blue band first seen 2026-08-30
Light Blue band first seen 2026-08-30

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

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=3,953), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

Metric	This player	Blue band median	Purple band median	vs Purple band
Headshot rate	38.7%	41.5%	44.2%	5.5% short
Shot accuracy	9.6%	9.1%	11.7%	2.1% short
Kill/death ratio	1.00	0.98	1.03	0.03 short
Match win rate	46.3%	43.7%	45.2%	above

This profile matches the typical Purple band player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Purple band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim59

Positioning45

Utility53

0–100 skill scores via Leetify.

Recent form

HOT48–44–8Last 10048%Win rateWTWWWWWWWL

Last 10 vs previous 10: +60pp win rate · +0.02 avg rating

Player DNA

Aim5.9

Aggression5.4

Utility5.3

Positioning4.5

Opening Duels1.1

Clutch3.8

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 84% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: lower positioning profile; 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. 565ms 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

Aim5.9

Positioning4.5

Utility5.3

Mechanics7.7

Opening Duels1.1

Win Impact5.6

Composite 5.0/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 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 time573ms−65ms

first ⅓ avg 638ms → last ⅓ avg 573ms

Headshot accuracy13.7%+0.4%

first ⅓ avg 13.3% → last ⅓ avg 13.7%

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

0.13Best rating — nuke 15–15

13–1Biggest win — dust2

7Longest win streak

5–8In matches decided by ≤2 rounds

18Overtime games

Map breakdown

cacheBest map · 75% over 8infernoWeakest map · 30% over 20

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	24	12–12	50%	-0.00
inferno	D	20	6–14	30%	-0.00
ancient	A	18	11–7	61%	0.02
dust2	B	17	8–9	47%	0.01
cache	S	8	6–2	75%	-0.01
nuke	C	7	3–4	43%	0.03
anubis	—	4	1–3	25%	-0.01
vertigo	—	1	1–0	100%	0.02
train	—	1	0–1	0%	-0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (30% over 20). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

112,321Lifetime kills

1.00K/D · Top 50% of Blue band

6,122Matches

46.3%Match win rate · Top 50% of Blue band

38.7%Headshot %

9.6%Shot accuracy · Top 50% of Blue band

14,872MVPs

2,523Hours (in match)

4,984Bombs planted

1,362Bombs defused

Most-used weapons

AK-4742,424

M4A4 / M4A1-S27,178

AWP7,738

P2000 / USP-S6,847

FAMAS4,412

Galil AR4,204

P2503,662

XM10142,654

Glock-182,421

Desert Eagle2,205

Lifetime map wins

13,179dust2

12,292inferno

3,383vertigo

2,637nuke

1,310train

146lake

133cbble

67office

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

359Matches

47%Win rate

1.01Avg K/D

81.3ADR

40%Headshot %

Clutches & streaks

39%1v1 clutch win

17%1v2 clutch win

5Longest win streak

Recent Faceit resultsLWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	81	57%	1.11	16.3
Mirage	63	33%	0.94	15.1
Ancient	51	51%	0.99	15.3
Nuke	41	29%	0.84	13.5
Overpass	35	60%	1.23	15.4
Dust2	31	52%	0.94	15.0
Anubis	22	41%	1.00	14.7
Train	17	53%	1.01	18.4

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.

13.3%Headshot accuracy

33.7%Accuracy (enemy spotted)

32.3%Spray accuracy

84.4%Counter-strafing

11.6°Preaim

565msReaction time

36.4%T opening success

32.2%CT opening success

0.48Enemies flashed / flash

3.0%Flash assists

11.06HE damage / grenade

6.36Flashes / 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 13.3208% — 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 0.4766 — below the 0.5 mark we flag
Grenade Lineups →
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 36.4195% — 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.

30% win rate across 20 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
inferno	13–11	0.08	16%	25 Aug →
inferno	15–15	-0.02	3%	25 Aug →
vertigo	13–8	0.02	19%	23 Aug →
inferno	13–10	0.03	18%	22 Aug →
nuke	13–6	0.01	15%	21 Aug →
ancient	13–7	0.03	17%	21 Aug →
inferno	16–12	0.03	12%	17 Aug →
cache	13–9	-0.06	7%	16 Aug →
ancient	13–9	0.05	14%	16 Aug →
nuke	5–13	-0.02	13%	16 Aug →
dust2	6–13	-0.10	13%	15 Aug →
nuke	11–13	0.02	12%	15 Aug →
nuke	13–9	0.03	18%	12 Aug →
mirage	16–13	-0.05	6%	11 Aug →
cache	10–13	-0.05	11%	11 Aug →
dust2	5–13	0.05	17%	10 Aug →
inferno	7–13	0.02	6%	10 Aug →
ancient	12–16	-0.01	15%	9 Aug →
mirage	15–15	0.00	17%	9 Aug →
anubis	8–13	-0.02	11%	9 Aug →
dust2	13–5	0.05	27%	8 Aug →
dust2	13–1	0.04	11%	8 Aug →
mirage	7–13	0.03	19%	8 Aug →
ancient	11–13	0.01	14%	8 Aug →
inferno	7–13	-0.08	7%	7 Aug →
mirage	13–7	-0.00	17%	7 Aug →
ancient	10–13	0.02	11%	7 Aug →
inferno	12–12	-0.03	13%	5 Aug →
mirage	10–13	0.01	16%	5 Aug →
dust2	13–8	0.03	11%	5 Aug →
ancient	13–16	0.00	11%	4 Aug →
mirage	14–16	-0.02	20%	3 Aug →
ancient	13–7	0.04	15%	3 Aug →
ancient	13–4	0.01	8%	3 Aug →
dust2	10–13	-0.00	13%	3 Aug →
cache	6–13	-0.04	9%	2 Aug →
nuke	15–15	0.13	12%	2 Aug →
inferno	6–13	-0.03	15%	2 Aug →
dust2	2–13	-0.05	14%	1 Aug →
ancient	13–10	0.03	13%	1 Aug →
dust2	13–10	-0.02	13%	1 Aug →
mirage	8–13	-0.03	25%	1 Aug →
cache	13–7	0.03	11%	1 Aug →
inferno	15–15	-0.02	15%	31 Jul →
ancient	3–13	-0.03	17%	31 Jul →
cache	13–6	0.02	11%	31 Jul →
mirage	7–2	0.01	0%	31 Jul →
mirage	13–7	0.03	12%	29 Jul →
nuke	13–9	0.02	5%	28 Jul →
mirage	7–13	-0.04	7%	28 Jul →
dust2	11–13	-0.02	11%	28 Jul →
dust2	13–8	0.04	20%	27 Jul →
inferno	5–13	-0.03	5%	27 Jul →
mirage	7–13	-0.01	6%	27 Jul →
anubis	8–13	0.01	16%	26 Jul →
dust2	11–13	0.00	10%	26 Jul →
inferno	8–13	0.01	11%	26 Jul →
inferno	14–16	0.01	9%	26 Jul →
dust2	16–14	0.00	7%	25 Jul →
mirage	15–15	-0.04	14%	25 Jul →
ancient	9–13	-0.06	7%	25 Jul →
mirage	13–10	-0.03	10%	24 Jul →
cache	13–8	-0.02	20%	24 Jul →
ancient	13–11	0.00	17%	24 Jul →
mirage	13–10	0.05	7%	24 Jul →
ancient	13–9	0.01	14%	24 Jul →
inferno	16–14	-0.04	18%	24 Jul →
mirage	15–15	0.03	10%	23 Jul →
nuke	8–13	0.04	15%	23 Jul →
inferno	4–13	0.02	18%	23 Jul →
mirage	13–8	0.02	12%	22 Jul →
inferno	10–13	-0.03	10%	22 Jul →
ancient	8–13	0.02	15%	22 Jul →
dust2	16–13	-0.06	11%	22 Jul →
inferno	13–5	0.03	10%	22 Jul →
dust2	8–13	0.02	21%	21 Jul →
ancient	13–3	0.02	16%	21 Jul →
mirage	6–13	0.00	12%	20 Jul →
mirage	13–3	0.08	9%	20 Jul →
inferno	13–5	0.03	14%	20 Jul →
mirage	13–7	0.03	12%	14 Jul →
cache	16–12	0.04	12%	14 Jul →
ancient	13–6	0.06	26%	14 Jul →
mirage	13–3	0.04	8%	13 Jul →
inferno	5–13	-0.08	6%	13 Jul →
ancient	16–12	0.00	14%	13 Jul →
mirage	8–13	-0.05	13%	11 Jul →
dust2	6–13	0.01	17%	11 Jul →
mirage	13–16	-0.06	8%	11 Jul →
inferno	10–13	-0.02	14%	10 Jul →
cache	13–4	-0.03	17%	10 Jul →
anubis	13–7	-0.02	9%	10 Jul →
mirage	13–4	0.03	14%	8 Jul →
dust2	12–12	0.08	15%	8 Jul →
train	11–13	-0.03	6%	8 Jul →
inferno	10–13	0.10	15%	6 Jul →
ancient	13–11	0.07	11%	6 Jul →
dust2	13–3	0.08	24%	6 Jul →
anubis	11–13	0.00	7%	6 Jul →
mirage	13–7	-0.03	19%	6 Jul →