waylo22 — CS2 Stats

76561198202615134[U:1:242349406]

1,187Tracked matches37%Win rate2020Tracked since

CSDB Rating4.3 Developing

FaceitLevel 5Top 67.6% of ranked FACEIT players

WingmanGold Nova I

Ladder ranks via Leetify

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Performance scores

Aim52

Positioning51

Utility52

0–100 skill scores via Leetify.

Recent form

COLD40–59–1Last 10040%Win rateLLLLLLLLWW

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

Player DNA

Aim5.2

Aggression8.4

Utility5.2

Positioning5.1

Opening Duels3.7

Clutch5.0

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 ropz 84% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: 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. 601ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 64% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim5.2

Positioning5.1

Utility5.2

Mechanics3.2

Opening Duels3.7

Win Impact0.6

Composite 4.3/10 (Developing), 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 rating-0.01−0.01

first ⅓ avg 0.00 → last ⅓ avg -0.01

Reaction time590ms−33ms

first ⅓ avg 623ms → last ⅓ avg 590ms

Headshot accuracy17.3%−1.2%

first ⅓ avg 18.5% → last ⅓ avg 17.3%

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

0.09Best rating — inferno 13–10

13–2Biggest win — ancient

5Longest win streak

L8Current streak

11–12In matches decided by ≤2 rounds

6Overtime games

Map breakdown

ancientBest map · 71% over 14nukeWeakest map · 14% over 7

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	20	10–10	50%	-0.01
anubis	B	20	9–11	45%	-0.00
cache	D	19	5–14	26%	0.01
ancient	S	14	10–4	71%	0.02
dust2	D	10	2–8	20%	-0.03
mirage	D	8	2–6	25%	0.00
nuke	D	7	1–6	14%	-0.03
vertigo	—	1	0–1	0%	-0.00
overpass	—	1	1–0	100%	0.05

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

276Matches

49%Win rate

1.09Avg K/D

74.4ADR

41%Headshot %

Clutches & streaks

45%1v1 clutch win

20%1v2 clutch win

8Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	51	37%	0.99	14.8
Ancient	49	43%	1.05	15.4
Dust2	42	45%	1.00	14.1
Nuke	40	60%	1.13	17.1
Inferno	33	70%	1.21	15.6
Anubis	24	46%	1.21	15.7
Overpass	21	57%	1.15	15.6
Train	6	33%	1.19	15.5

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.

17.8%Headshot accuracy

34.4%Accuracy (enemy spotted)

35.9%Spray accuracy

64.4%Counter-strafing

10.7°Preaim

601msReaction time

43.6%T opening success

46.4%CT opening success

0.48Enemies flashed / flash

5.0%Flash assists

8.27HE damage / grenade

12.46Flashes / 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.

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 0.4832 — below the 0.5 mark we flag
Grenade Lineups →

Spend your practice time on Nuke

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

14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	5–13	-0.03	8%	5 Aug →
inferno	9–13	-0.01	9%	5 Aug →
inferno	14–16	-0.05	20%	2 Aug →
ancient	3–13	0.00	19%	30 Jul →
anubis	7–13	-0.01	27%	21 Jul →
cache	7–13	0.00	6%	19 Jul →
cache	3–13	-0.05	11%	19 Jul →
dust2	6–13	-0.02	19%	19 Jul →
inferno	13–8	-0.06	17%	18 Jul →
cache	13–9	0.00	0%	18 Jul →
cache	11–13	0.03	11%	18 Jul →
cache	8–13	0.02	35%	16 Jul →
nuke	0–4	-0.08	0%	15 Jul →
cache	10–13	-0.01	26%	15 Jul →
inferno	13–10	0.09	32%	14 Jul →
dust2	2–13	-0.06	18%	14 Jul →
anubis	9–13	-0.03	21%	14 Jul →
anubis	16–14	-0.06	11%	14 Jul →
inferno	13–3	0.02	21%	13 Jul →
anubis	10–13	-0.04	23%	13 Jul →
cache	3–13	-0.07	10%	12 Jul →
inferno	8–13	-0.02	11%	12 Jul →
nuke	4–13	-0.02	7%	12 Jul →
cache	13–5	0.03	33%	12 Jul →
ancient	13–2	0.07	12%	12 Jul →
inferno	13–6	-0.02	24%	12 Jul →
inferno	6–13	-0.02	39%	12 Jul →
anubis	13–7	-0.06	15%	12 Jul →
ancient	16–14	0.02	7%	10 Jul →
cache	13–7	0.08	31%	10 Jul →
ancient	13–11	0.03	8%	10 Jul →
cache	16–13	-0.01	14%	9 Jul →
inferno	11–13	-0.01	24%	9 Jul →
cache	4–13	-0.06	5%	8 Jul →
vertigo	10–13	-0.00	24%	8 Jul →
inferno	4–13	-0.07	5%	7 Jul →
nuke	13–11	-0.04	11%	5 Jul →
anubis	10–13	0.02	6%	5 Jul →
inferno	9–13	-0.01	21%	5 Jul →
ancient	13–11	0.01	14%	5 Jul →
overpass	13–5	0.05	15%	5 Jul →
anubis	11–13	0.01	13%	5 Jul →
inferno	13–11	0.02	23%	4 Jul →
anubis	13–10	0.05	23%	4 Jul →
inferno	3–13	-0.09	8%	4 Jul →
anubis	13–11	-0.05	25%	4 Jul →
inferno	4–6	-0.02	11%	4 Jul →
cache	2–8	0.08	17%	4 Jul →
dust2	7–13	-0.06	14%	4 Jul →
mirage	5–13	0.06	14%	4 Jul →
cache	11–13	-0.00	23%	4 Jul →
dust2	8–13	-0.04	26%	3 Jul →
ancient	3–0	-0.06	0%	3 Jul →
anubis	11–13	-0.04	13%	3 Jul →
mirage	6–13	-0.05	24%	3 Jul →
ancient	13–7	0.02	22%	3 Jul →
cache	13–10	0.07	8%	3 Jul →
ancient	13–6	-0.02	7%	3 Jul →
inferno	13–11	0.01	23%	3 Jul →
cache	1–9	-0.08	25%	2 Jul →
nuke	8–13	0.01	10%	2 Jul →
anubis	11–13	0.03	40%	1 Jul →
inferno	13–8	-0.01	10%	30 Jun →
anubis	13–11	0.08	19%	30 Jun →
anubis	6–13	-0.00	14%	30 Jun →
inferno	13–11	0.02	16%	28 Jun →
mirage	5–13	0.01	25%	28 Jun →
anubis	13–3	-0.03	13%	28 Jun →
ancient	9–13	0.02	11%	28 Jun →
cache	7–13	0.03	13%	28 Jun →
anubis	7–13	0.01	19%	27 Jun →
dust2	11–13	-0.07	7%	27 Jun →
mirage	13–6	0.03	10%	27 Jun →
ancient	13–3	0.07	21%	27 Jun →
anubis	8–13	-0.03	15%	27 Jun →
ancient	6–13	0.02	17%	27 Jun →
dust2	11–13	0.01	15%	27 Jun →
ancient	13–5	0.01	24%	26 Jun →
mirage	10–13	0.03	20%	26 Jun →
inferno	8–13	0.00	18%	25 Jun →
nuke	14–16	-0.01	21%	25 Jun →
anubis	13–4	-0.00	12%	24 Jun →
ancient	13–11	0.05	25%	24 Jun →
cache	4–13	-0.06	13%	24 Jun →
nuke	6–13	-0.01	13%	24 Jun →
dust2	13–3	0.02	6%	23 Jun →
anubis	13–10	0.04	18%	23 Jun →
anubis	4–13	-0.04	20%	23 Jun →
inferno	13–10	-0.04	10%	23 Jun →
mirage	8–13	-0.04	17%	22 Jun →
anubis	13–10	0.05	20%	22 Jun →
dust2	10–13	-0.03	22%	21 Jun →
inferno	13–4	0.08	24%	21 Jun →
cache	10–13	0.06	26%	21 Jun →
cache	8–13	0.08	31%	21 Jun →
mirage	13–7	-0.01	22%	21 Jun →
mirage	12–12	0.00	31%	21 Jun →
dust2	2–13	-0.12	25%	20 Jun →
nuke	14–16	-0.04	31%	20 Jun →
dust2	13–8	0.00	20%	20 Jun →