Phosphophyllite

Phosphophyllite — CS2 Stats

76561198278448858[U:1:318183130]Steam profile ↗

518Tracked matches50%Win rate2022Tracked since
1,112Hours in CS2Hrs last 2 wks
CSDB Rating3.1 Learning
Ladder ranks via Leetify

Performance scores

Aim31
Positioning26
Utility49

0–100 skill scores via Leetify.

Recent form

STEADY49465Last 10049%Win rateLWLWWLLWWW

Last 10 vs previous 10: +30pp win rate · -0.00 avg rating

Player DNA

Aim3.1
Aggression0.6
Utility4.9
Positioning2.6
Opening Duels0.0
Clutch4.2

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 65% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower opening-fight frequency; 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. 693ms 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

Aim3.1
Positioning2.6
Utility4.9
Mechanics5.2
Opening Duels0.0
Win Impact5.0

Composite 3.1/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.05−0.02
first ⅓ avg -0.03 → last ⅓ avg -0.05
Reaction time695ms−16ms
first ⅓ avg 711ms → last ⅓ avg 695ms
Headshot accuracy12.8%+1.0%
first ⅓ avg 11.9% → last ⅓ avg 12.8%

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

0.04Best rating — jura 13–11
133Biggest win — anubis
9Longest win streak
179In matches decided by ≤2 rounds
6Overtime games

Map breakdown

ancientBest map · 71% over 17infernoWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
dust2B23121152%-0.04
ancientS1712571%-0.04
trainB157847%-0.04
anubisD103730%-0.02
overpassC94544%-0.04
infernoD72529%-0.06
mirageA74357%-0.04
cacheB63350%-0.05
vertigo1010%-0.02
palacio1010%-0.03
golden1010%-0.10
agency1010%-0.01
jura110100%0.04
grail110100%0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

45,249Lifetime kills
0.98K/D
2,159Matches
32.1%Match win rate
29.5%Headshot %
16.0%Shot accuracy · Top 25% of tracked players
2,142MVPs
842Hours (in match)
1,340Bombs planted
489Bombs defused

Most-used weapons

AK-4710,463
AWP9,594
Negev1,748
Tec-91,209
P901,079
Knife957

Lifetime map wins

1,988dust2
1,557inferno
824vertigo
699train
516nuke
385cbble
53office
37italy

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

Faceit stats

Combat

126Matches
52%Win rate
0.75Avg K/D
57.1ADR
33%Headshot %

Clutches & streaks

41%1v1 clutch win
15%1v2 clutch win
6Longest win streak

Recent Faceit resultsLWWLW

MapMatchesWin rateAvg K/DAvg kills
Anubis2544%0.689.6
Ancient1656%0.6810.8
Dust21540%0.619.7
Inferno757%0.709.6
Cache667%0.7410.5
Overpass633%0.6511.5
Train367%0.5511.0
Mirage3100%0.9812.3

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.

12.3%Headshot accuracy
30.8%Accuracy (enemy spotted)
32.2%Spray accuracy
73.3%Counter-strafing
12.1°Preaim
693msReaction time
16.8%T opening success
26.9%CT opening success
0.66Enemies flashed / flash
4.9%Flash assists
11.25HE damage / grenade
7.60Flashes / 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. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 12.0913° — above the 12° mark we flag

    Aim Training
  2. 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 12.3372% — below the 15% mark we flag

    Aim Training
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.

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
dust211–13-0.0418%6 Aug
ancient13–11-0.066%6 Aug
cache7–13-0.0210%6 Aug
ancient13–6-0.0314%9 Jul
cache13–8-0.0612%9 Jul
cache8–13-0.077%9 Jul
inferno7–13-0.0926%1 Jun
ancient13–8-0.0416%1 Jun
cache13–11-0.0414%20 May
cache13–9-0.050%20 May
cache2–13-0.0619%24 Apr
dust210–13-0.0321%27 Feb
dust22–13-0.0811%27 Feb
dust213–11-0.0724%14 Feb
dust26–130.0215%7 Feb
anubis7–130.018%31 Jan
ancient13–7-0.083%31 Jan
anubis13–3-0.063%25 Jan
anubis11–13-0.015%24 Jan
ancient1–13-0.1030%15 Jan
overpass7–13-0.1012%15 Jan
train2–13-0.136%15 Jan
overpass10–13-0.0122%4 Jan
train17–19-0.058%4 Jan
overpass13–70.0122%4 Jan
ancient13–11-0.097%4 Jan
mirage13–11-0.037%27 Dec
train13–9-0.0312%27 Dec
ancient13–7-0.0213%27 Dec
overpass13–7-0.038%27 Dec
train16–14-0.0314%21 Dec
overpass13–7-0.0414%21 Dec
train13–11-0.0319%21 Dec
ancient7–130.0211%21 Dec
mirage13–80.0114%12 Dec
dust26–13-0.084%12 Dec
anubis13–11-0.0018%12 Dec
dust23–13-0.0813%7 Dec
mirage11–13-0.0316%7 Dec
train6–13-0.043%2 Dec
inferno13–10-0.0714%2 Dec
train5–13-0.0122%2 Dec
dust213–8-0.078%1 Dec
dust213–7-0.047%1 Dec
inferno2–13-0.0413%1 Dec
dust210–13-0.0411%28 Nov
ancient13–30.0016%21 Nov
overpass0–13-0.1213%17 Nov
train13–11-0.040%17 Nov
ancient13–7-0.052%17 Nov
vertigo12–12-0.025%15 Nov
anubis9–13-0.0628%11 Nov
ancient13–10-0.080%28 Oct
dust24–13-0.0520%28 Oct
anubis10–130.0414%26 Oct
ancient13–11-0.083%9 Oct
dust215–15-0.059%9 Oct
mirage13–10-0.0719%9 Oct
overpass9–13-0.0615%9 Oct
dust213–6-0.027%9 Oct
palacio8–13-0.034%2 Oct
golden4–13-0.1013%2 Oct
train10–13-0.0320%15 Sept
overpass13–9-0.0512%16 Aug
dust213–10-0.057%16 Aug
mirage8–13-0.0210%5 Aug
train11–13-0.0212%5 Aug
ancient13–40.0213%5 Aug
inferno3–13-0.0210%4 Aug
dust213–11-0.0511%4 Aug
inferno4–13-0.125%27 Jul
train13–8-0.0318%24 Jun
inferno8–13-0.098%24 Jun
dust213–100.025%24 Jun
ancient8–13-0.0612%19 Jun
agency11–13-0.0114%11 Jun
anubis13–11-0.0114%9 Jun
dust27–13-0.0328%9 Jun
train9–13-0.067%9 Jun
ancient13–10-0.0313%6 Jun
dust25–13-0.0619%6 Jun
dust213–5-0.007%25 May
anubis14–16-0.0410%25 May
ancient14–16-0.056%22 May
train15–15-0.0211%22 May
anubis5–13-0.0810%22 May
dust213–11-0.0215%21 May
anubis11–13-0.038%21 May
dust27–1-0.0144%21 May
jura13–110.0411%21 May
grail13–90.008%21 May
mirage4–13-0.0910%21 May
train13–8-0.0711%21 May
dust213–11-0.007%20 May
overpass12–120.0014%20 May
ancient12–120.008%20 May
mirage13–8-0.078%20 May
train13–11-0.0311%20 May
dust213–9-0.046%20 May
inferno13–110.0211%20 May

Match data via Leetify.

Recent teammates

Milestones

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