Saxie Viking — CS2 Stats

76561199127075214[U:1:1166809486]✓ No bans

324Tracked matches57%Win rate2024Tracked since

CSDB Rating6.8 SolidAggressive Rifler

FaceitLevel 5Top 67.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim90

Positioning54

Utility60

0–100 skill scores via Leetify.

Recent form

HOT55–35–10Last 10055%Win rateWLWLWWWWWW

Last 10 vs previous 10: +50pp win rate · +0.01 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim9.0

Aggression7.2

Utility6.0

Positioning5.4

Opening Duels2.7

Clutch3.8

Sharp aimer

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 Twistzz 93% playstyle similarity

Most alike: positioning profile, opening-duel success.

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

Strengths

Aim. Aim score of 90 — the mechanical foundation is a clear strength.

Areas to improve

Preaim. Mechanical aim is strong but the crosshair sits 10.1° off target when enemies appear — placement, not flicking, is the bigger win available.

Positioning. Positioning trails aim by 36 points — deaths here waste a strong aim profile.

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 647ms 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

Aim9.0

Positioning5.4

Utility6.0

Mechanics7.7

Opening Duels2.7

Win Impact7.4

Composite 6.8/10 (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+0.01

first ⅓ avg 0.00 → last ⅓ avg 0.01

Reaction time651ms−64ms

first ⅓ avg 715ms → last ⅓ avg 651ms

Headshot accuracy30.2%+6.8%

first ⅓ avg 23.4% → last ⅓ avg 30.2%

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

0.17Best rating — anubis 13–5

13–0Biggest win — inferno

8Longest win streak

10–8In matches decided by ≤2 rounds

12Overtime games

Map breakdown

infernoBest map · 83% over 12nukeWeakest map · 35% over 23

Map	Grade	Played	Record	Win rate	Avg rating
mirage	S	25	17–8	68%	-0.00
nuke	C	23	8–15	35%	0.01
inferno	S	12	10–2	83%	0.02
cache	C	11	4–7	36%	0.02
anubis	S	10	7–3	70%	0.00
dust2	C	9	4–5	44%	0.00
ancient	A	8	5–3	63%	0.03
overpass	—	1	0–1	0%	0.04
train	—	1	0–1	0%	0.08

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (35% over 23). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

53Matches

55%Win rate

1.02Avg K/D

68.9ADR

52%Headshot %

Clutches & streaks

39%1v1 clutch win

26%1v2 clutch win

7Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	19	53%	1.08	15.5
Ancient	8	62%	0.94	12.6
Dust2	7	57%	0.89	13.1
Nuke	6	50%	1.09	14.8
Inferno	6	67%	1.11	11.0
Cache	4	25%	0.74	10.8
Anubis	3	67%	1.13	16.0

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.

29.2%Headshot accuracy

41.2%Accuracy (enemy spotted)

47.2%Spray accuracy

84.6%Counter-strafing

10.1°Preaim

647msReaction time

43.9%T opening success

37.8%CT opening success

0.67Enemies flashed / flash

5.3%Flash assists

12.36HE damage / grenade

8.28Flashes / 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
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 37.8258% — below the 40% mark we flag

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.

35% win rate across 23 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	13–1	0.13	19%	16 Aug →
cache	11–13	-0.01	13%	13 Jul →
mirage	13–10	-0.06	33%	13 Jul →
cache	1–4	-0.06	100%	13 Jul →
mirage	13–6	-0.01	22%	10 Jul →
mirage	13–8	0.02	23%	10 Jul →
anubis	13–2	-0.00	35%	9 Jul →
anubis	13–4	-0.00	17%	7 Jul →
inferno	13–5	0.06	34%	7 Jul →
cache	13–2	0.08	38%	7 Jul →
inferno	13–8	-0.04	25%	3 Jul →
dust2	13–8	0.14	40%	3 Jul →
cache	2–5	-0.06	17%	1 Jul →
mirage	13–8	0.03	24%	1 Jul →
cache	9–13	0.06	38%	30 Jun →
nuke	5–13	0.00	26%	29 Jun →
inferno	7–13	0.01	29%	29 Jun →
mirage	3–13	-0.02	31%	23 Jun →
nuke	10–13	-0.04	36%	23 Jun →
dust2	15–15	-0.06	20%	23 Jun →
ancient	16–14	0.07	20%	18 Jun →
inferno	13–5	0.03	30%	15 Jun →
ancient	13–8	0.06	24%	15 Jun →
nuke	15–15	0.06	39%	11 Jun →
nuke	13–9	-0.04	40%	11 Jun →
nuke	11–13	-0.03	33%	10 Jun →
mirage	11–13	0.01	31%	10 Jun →
mirage	13–10	0.07	32%	10 Jun →
ancient	7–13	-0.02	16%	9 Jun →
nuke	11–13	-0.03	37%	9 Jun →
mirage	13–11	-0.00	32%	9 Jun →
inferno	13–7	0.01	20%	9 Jun →
nuke	13–11	0.10	22%	8 Jun →
anubis	13–8	-0.01	22%	8 Jun →
inferno	13–10	0.05	13%	7 Jun →
inferno	13–7	-0.02	21%	6 Jun →
inferno	4–13	0.02	25%	6 Jun →
mirage	13–10	-0.02	12%	5 Jun →
dust2	13–7	-0.03	21%	2 Jun →
dust2	6–13	0.05	23%	2 Jun →
mirage	16–14	-0.02	23%	31 May →
mirage	13–8	-0.01	41%	31 May →
dust2	5–13	-0.10	30%	31 May →
nuke	8–13	0.01	19%	31 May →
nuke	13–9	0.05	24%	31 May →
mirage	13–10	-0.01	15%	31 May →
anubis	7–13	-0.04	22%	30 May →
dust2	11–13	-0.04	17%	30 May →
cache	13–10	0.04	26%	30 May →
nuke	7–13	-0.02	23%	29 May →
mirage	15–15	0.00	23%	29 May →
mirage	13–9	0.03	18%	29 May →
mirage	5–13	0.06	24%	29 May →
inferno	13–6	0.06	12%	28 May →
mirage	13–6	0.02	23%	28 May →
nuke	16–12	-0.00	26%	28 May →
ancient	16–14	0.05	20%	28 May →
nuke	13–5	0.01	35%	28 May →
cache	12–12	0.07	30%	28 May →
mirage	13–16	0.01	27%	28 May →
anubis	7–13	-0.04	23%	27 May →
nuke	13–7	0.04	30%	27 May →
anubis	13–4	0.01	24%	27 May →
anubis	13–5	0.17	30%	27 May →
inferno	13–0	0.00	0%	27 May →
cache	13–2	0.02	13%	27 May →
mirage	16–14	0.01	18%	26 May →
mirage	13–6	-0.10	38%	26 May →
mirage	13–11	-0.06	21%	26 May →
overpass	10–13	0.04	30%	26 May →
mirage	10–13	-0.06	21%	26 May →
nuke	10–13	-0.02	18%	26 May →
ancient	16–14	-0.01	29%	26 May →
mirage	13–6	0.03	20%	26 May →
nuke	13–2	0.03	9%	26 May →
nuke	13–11	-0.01	18%	24 May →
mirage	10–13	-0.01	37%	24 May →
mirage	12–12	-0.00	25%	24 May →
dust2	13–7	0.03	15%	21 May →
train	3–13	0.08	20%	20 May →
inferno	13–10	-0.02	18%	20 May →
anubis	13–11	0.05	28%	18 May →
dust2	15–15	-0.01	20%	18 May →
nuke	11–13	0.01	33%	18 May →
inferno	13–9	0.04	11%	18 May →
nuke	15–15	-0.02	19%	18 May →
nuke	11–13	0.01	27%	18 May →
nuke	7–9	-0.02	24%	18 May →
nuke	12–12	-0.01	21%	18 May →
ancient	12–12	0.01	15%	18 May →
cache	6–13	0.04	27%	18 May →
mirage	13–10	0.05	27%	18 May →
nuke	12–12	0.01	26%	18 May →
anubis	0–13	-0.07	33%	18 May →
cache	10–13	-0.01	18%	17 May →
cache	13–9	0.04	30%	17 May →
dust2	13–6	0.06	14%	17 May →
ancient	9–13	-0.06	29%	14 May →
anubis	13–3	-0.03	13%	14 May →
nuke	10–13	0.01	40%	14 May →