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FoxySplash — CS2 Stats

76561198394661053[U:1:434395325]

1,158Tracked matches46%Win rate2021Tracked since
CSDB Rating2.3 Learning
FaceitLevel 2Top 97.9% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGFoxySplashFACEITLevel 2STANDINGTop 97.9% of rankedcsdb.gg/stats

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Performance scores

Aim23
Positioning31
Utility7

0–100 skill scores via Leetify.

Recent form

STEADY35–58–7Last 10035%Win rateLWLLLLWWLW

Last 10 vs previous 10: +20pp win rate · -0.00 avg rating

Player DNA

Aim2.3
Aggression0.0
Utility0.7
Positioning3.1
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

NiKo

Plays most like NiKo 55% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower utility contribution; 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. 664ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 65% 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

Aim2.3
Positioning3.1
Utility0.7
Mechanics3.4
Opening Duels0.0
Win Impact3.8

Composite 2.3/10 (Learning), 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-0.06−0.00
first ⅓ avg -0.06 → last ⅓ avg -0.06
Reaction time666ms−44ms
first ⅓ avg 710ms → last ⅓ avg 666ms
Headshot accuracy9.7%−2.4%
first ⅓ avg 12.1% → last ⅓ avg 9.7%

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

0.06Best rating — golden 13–7
13–1Biggest win — cache
5Longest win streak
4–4In matches decided by ≤2 rounds
2Overtime games

Map breakdown

overpassBest map · 55% over 11infernoWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
anubisD175–1229%-0.07
cacheD133–1023%-0.05
vertigoB126–650%-0.05
nukeD124–833%-0.07
overpassA116–555%-0.07
ancientD102–820%-0.07
trainC94–544%-0.06
infernoD61–517%-0.06
warden—43–175%-0.05
golden—21–150%0.00
shelter—10–10%-0.06
alpine—10–10%-0.07
office—10–10%-0.11
italy—10–10%-0.10

Across the last 100 tracked matches.

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

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

10.1%Headshot accuracy
27.9%Accuracy (enemy spotted)
29.9%Spray accuracy
65.3%Counter-strafing
11.0°Preaim
664msReaction time
17.3%T opening success
21.3%CT opening success
0.00Enemies flashed / flash
0.0%Flash assists
4.46HE damage / grenade
0.00Flashes / 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.

  1. 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 10.1222% — below the 15% mark we flag

    Aim Training →
  2. 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 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 17.2916% — 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 6 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis0–13-0.1011%18 Jul →
anubis13–10-0.0217%17 Jul →
cache8–13-0.0817%17 Jul →
inferno2–13-0.115%16 Jul →
ancient3–13-0.079%16 Jul →
anubis6–13-0.090%16 Jul →
cache13–4-0.0416%15 Jul →
anubis13–4-0.056%15 Jul →
vertigo5–13-0.0714%15 Jul →
overpass13–5-0.0613%15 Jul →
cache13–10.0129%15 Jul →
shelter11–13-0.0619%12 Jul →
train3–13-0.050%12 Jul →
cache8–13-0.045%12 Jul →
nuke13–6-0.086%12 Jul →
overpass7–13-0.0611%5 Jul →
nuke0–13-0.114%5 Jul →
nuke10–13-0.099%5 Jul →
cache1–13-0.110%5 Jul →
ancient8–13-0.096%5 Jul →
vertigo13–1-0.069%27 Jun →
warden13–6-0.0513%27 Jun →
cache12–12-0.093%27 Jun →
overpass13–3-0.0313%21 Jun →
cache10–13-0.0415%14 Jun →
vertigo13–7-0.0412%14 Jun →
anubis13–10-0.0416%24 May →
vertigo13–4-0.0210%24 May →
ancient12–12-0.018%24 May →
cache13–5-0.033%24 May →
train13–9-0.068%23 May →
nuke13–5-0.0213%23 May →
overpass13–6-0.100%22 May →
cache10–13-0.0415%22 May →
anubis10–13-0.094%18 May →
vertigo12–12-0.0713%18 May →
cache8–13-0.100%18 May →
vertigo13–7-0.0213%15 May →
warden13–8-0.057%15 May →
cache12–12-0.0516%15 May →
cache6–13-0.0118%1 May →
anubis6–13-0.0413%1 May →
cache4–13-0.0812%1 May →
ancient13–9-0.056%25 Apr →
vertigo9–13-0.0515%25 Apr →
warden6–13-0.0219%11 Apr →
alpine8–13-0.0722%11 Apr →
anubis7–13-0.110%11 Apr →
anubis6–13-0.0919%3 Apr →
ancient9–13-0.1016%3 Apr →
nuke9–13-0.0012%7 Mar →
ancient6–13-0.117%7 Mar →
anubis6–13-0.0917%7 Mar →
warden13–9-0.083%28 Feb →
vertigo8–13-0.127%28 Feb →
anubis5–13-0.086%28 Feb →
overpass2–13-0.1016%7 Feb →
train4–13-0.0410%7 Feb →
inferno1–13-0.0417%24 Jan →
anubis6–13-0.0515%24 Jan →
ancient6–13-0.0713%11 Jan →
anubis13–11-0.0721%11 Jan →
nuke13–5-0.0312%11 Jan →
train13–11-0.097%3 Jan →
office8–13-0.119%3 Jan →
anubis8–13-0.0511%2 Jan →
ancient1–13-0.0818%2 Jan →
italy12–12-0.108%2 Jan →
anubis8–13-0.078%29 Dec →
overpass13–11-0.099%29 Dec →
ancient13–4-0.0113%29 Dec →
nuke5–13-0.118%29 Dec →
overpass13–4-0.0219%26 Dec →
anubis13–10-0.0528%26 Dec →
anubis11–13-0.125%24 Dec →
golden13–70.069%24 Dec →
vertigo13–10.0221%24 Dec →
vertigo4–3-0.070%24 Dec →
overpass13–8-0.0319%24 Dec →
train13–3-0.0820%23 Dec →
inferno9–13-0.0610%23 Dec →
overpass8–13-0.0919%23 Dec →
train12–16-0.0510%6 Dec →
nuke9–13-0.057%6 Dec →
vertigo9–13-0.0416%6 Dec →
train4–13-0.0513%28 Nov →
nuke10–13-0.0610%28 Nov →
nuke7–13-0.1014%14 Nov →
inferno10–130.008%14 Nov →
train13–8-0.0214%13 Nov →
inferno13–10-0.0623%13 Nov →
golden7–13-0.0514%11 Nov →
ancient12–12-0.1017%11 Nov →
vertigo6–13-0.064%8 Nov →
inferno11–13-0.0710%8 Nov →
overpass11–13-0.0914%8 Nov →
train6–13-0.065%8 Nov →
overpass15–15-0.059%8 Nov →
nuke13–7-0.0611%8 Nov →
nuke3–13-0.084%1 Nov →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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