WOOD7

WOOD7 — CS2 Stats

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BR76561198003142163[U:1:42876435]Steam profile ↗

2,435Tracked matches60%Win rate2020Tracked since
CSDB Rating7.9 StrongAggressive Rifler
FaceitLevel 10 · 3,341 ELOTop 12.4% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGWOOD7FACEITLevel 10 · 3,341 ELOSTANDINGTop 12.4% of rankedcsdb.gg/stats

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Performance scores

Aim87
Positioning71
Utility81

0–100 skill scores via Leetify.

Recent form

STEADY59401Last 10059%Win rateWWWLWLLLLW

Last 10 vs previous 10: -10pp win rate · -0.08 avg rating

Player DNA

Primary style: Aggressive RiflerTakes opening fights often, backed by a strong aim profile.

Aim8.7
Aggression10.0
Utility8.1
Positioning7.1
Opening Duels5.8
Clutch4.6

Sharp aimerStrong CT-side openerEffective flashesHigh utility contribution

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

sh1ro

Plays most like sh1ro 92% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: higher utility contribution.

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 87 — the mechanical foundation is a clear strength.

CT openings. 62% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Flashes. 0.83 enemies blinded per flash — utility that consistently lands.

Utility. Utility score of 81 — grenade impact well above the norm.

Areas to improve

T-side openings. Opening success drops from 62% on CT to 45% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim8.7
Positioning7.1
Utility8.1
Mechanics5.7
Opening Duels5.8
Win Impact8.3

Composite 7.9/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.05+0.03
first ⅓ avg 0.02 → last ⅓ avg 0.05
Reaction time488ms+19ms
first ⅓ avg 469ms → last ⅓ avg 488ms
Headshot accuracy21.3%+3.4%
first ⅓ avg 17.8% → last ⅓ avg 21.3%

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

0.22Best rating — dust2 13–2
131Biggest win — cache
8Longest win streak
W3Current streak
87In matches decided by ≤2 rounds
6Overtime games

Map breakdown

cacheBest map · 78% over 9infernoWeakest map · 38% over 8
MapGradePlayedRecordWin rateAvg rating
dust2S36241267%0.06
ancientA27171063%0.03
cacheS97278%0.03
mirageB84450%0.05
infernoC83538%0.04
nukeC52340%0.02
anubis42250%0.03
overpass3030%0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,150Matches
62%Win rate
1.35Avg K/D
84.9ADR
37%Headshot %

Clutches & streaks

43%1v1 clutch win
25%1v2 clutch win
13Longest win streak

Recent Faceit resultsWLWWW

MapMatchesWin rateAvg K/DAvg kills
Anubis22964%1.3817.1
Ancient21461%1.3616.4
Dust215965%1.4917.9
Nuke9758%1.4316.9
Vertigo4452%1.2917.1
Inferno4052%1.1714.1
Mirage3244%1.2616.4
Overpass1856%1.3519.6

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Inventory

$3,056Inventory value34ItemsFull inventory breakdown →
★ Butterfly Knife | Marble Fade (Minimal Wear)$1,773★ Specialist Gloves | Fade (Field-Tested)$300M4A1-S | Hyper Beast (Minimal Wear)$172StatTrak™ USP-S | The Traitor (Minimal Wear)$131StatTrak™ AK-47 | Inheritance (Field-Tested)$115StatTrak™ M4A4 | The Emperor (Field-Tested)$107

Skill profile

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

21.4%Headshot accuracy
38.6%Accuracy (enemy spotted)
37.2%Spray accuracy
75.8%Counter-strafing
8.1°Preaim
485msReaction time
44.6%T opening success
61.6%CT opening success
0.83Enemies flashed / flash
10.9%Flash assists
12.86HE damage / grenade
13.03Flashes / match

Recommended for you

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.

38% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
ancient13–11-0.026%27 Aug
mirage13–4-0.025%27 Aug
dust213–90.0415%26 Aug
inferno10–13-0.0317%26 Aug
ancient13–5-0.0327%26 Aug
ancient8–13-0.049%25 Aug
dust29–13-0.0613%25 Aug
ancient4–13-0.0419%10 Aug
mirage5–13-0.0619%9 Aug
dust213–50.1417%9 Aug
inferno8–13-0.0020%9 Aug
ancient11–13-0.0124%9 Aug
dust213–80.1635%8 Aug
ancient13–40.0330%3 Aug
inferno16–190.1018%2 Aug
dust213–100.1828%2 Aug
ancient13–80.1235%27 Jul
dust216–130.0935%27 Jul
inferno14–160.0315%27 Jul
ancient13–80.0423%26 Jul
cache13–5-0.0421%26 Jul
cache13–100.0625%17 Jul
ancient8–130.1122%17 Jul
dust213–50.1727%17 Jul
dust27–130.0627%15 Jul
dust211–130.0820%15 Jul
inferno13–60.0915%14 Jul
dust213–50.1128%14 Jul
anubis13–80.0614%13 Jul
dust213–20.0533%12 Jul
cache13–110.0020%6 Jul
dust213–80.1119%6 Jul
inferno13–20.0718%6 Jul
ancient13–100.0817%3 Jul
dust29–130.1025%3 Jul
ancient13–50.0822%3 Jul
dust24–13-0.0631%1 Jul
ancient10–130.0414%1 Jul
mirage13–30.1225%29 Jun
dust213–100.1523%29 Jun
ancient16–140.0720%26 Jun
dust213–40.0535%26 Jun
dust211–130.0120%26 Jun
ancient10–13-0.0119%25 Jun
dust28–130.0612%25 Jun
ancient13–100.0411%25 Jun
cache14–160.0423%25 Jun
mirage13–90.0324%25 Jun
cache13–60.0521%24 Jun
nuke13–60.0322%24 Jun
ancient13–70.1223%24 Jun
ancient13–110.0527%23 Jun
dust213–100.0928%23 Jun
nuke10–13-0.0124%23 Jun
anubis9–130.0124%23 Jun
cache5–13-0.0313%21 Jun
dust213–50.1046%21 Jun
dust210–130.0716%18 Jun
ancient10–130.0420%18 Jun
dust213–20.2225%18 Jun
mirage13–40.1819%18 Jun
dust210–13-0.069%16 Jun
inferno13–110.0724%16 Jun
ancient13–50.0625%16 Jun
cache13–110.1118%15 Jun
dust213–20.0515%15 Jun
overpass10–130.0531%15 Jun
mirage10–130.0218%15 Jun
ancient6–130.0214%15 Jun
dust213–10-0.0519%14 Jun
cache13–6-0.0011%14 Jun
cache13–10.0621%14 Jun
dust213–50.0644%14 Jun
dust213–110.0316%11 Jun
dust213–80.0527%10 Jun
ancient13–100.0820%10 Jun
mirage7–130.0919%10 Jun
dust213–40.0515%9 Jun
dust213–80.0923%9 Jun
ancient8–13-0.0517%1 Jun
anubis9–13-0.0021%31 May
dust28–130.0820%31 May
overpass10–130.0115%31 May
dust213–3-0.0414%27 May
ancient13–40.0516%27 May
nuke13–110.0613%26 May
dust210–6-0.0629%11 May
ancient13–7-0.015%11 May
nuke7–130.0315%11 May
dust23–30.016%11 May
ancient13–100.0425%10 May
overpass2–13-0.0516%10 May
dust211–130.0323%10 May
ancient11–13-0.086%10 May
inferno8–13-0.0219%10 May
mirage7–130.0014%9 May
nuke6–13-0.0220%9 May
anubis14–90.0521%9 May
dust213–90.0710%9 May
ancient13–40.0420%8 May

Match data via Leetify.

Recent teammates

Milestones

Faceit Level 103K ELO Club1,000 Matches
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