Server statistics
Overview
Leaderboards
No players in the selected filter.
Combat
Combat metrics from telemetry. TTK = time from the victim’s first hit to their death; distance = average hit distance. Fills up after matches on the latest server version.
Fastest to kill (Ø TTK)
Collecting — no data from the new telemetry yet.
Longest-range hit
Collecting — no data from the new telemetry yet.
Most first bloods
Collecting — no data from the new telemetry yet.
Most airborne hits
Collecting — no data from the new telemetry yet.
Most hits from behind
Collecting — no data from the new telemetry yet.
Player style: distance vs pace
The chart appears once engagement-distance data is collected.
Does First Blood Decide?
How often the first-blood scorer wins vs random chance.
Trends over time
Matches and kills
Matches (columns) and kills (line) per period. The basic overview of server activity. Aggregation: day (change in the filter).
Average players per match
Average number of players in matches over time. Shows when the server was packed and when it was empty.
Unique humans
Number of distinct human players in each period. Growth means new faces, decline means just the regulars.
Server pace (kills/min)
Average kills per minute across matches over time. Measures how wild the server played.
Average match length
Average match duration in minutes over time. Long matches mean close fights or high limits.
Server performance (FPS)
Average FPS of the game server during matches. A drop signals machine overload and helps track down lag causes.
Cumulative kills of top players
Running total of the best players' kills over time. The race for overall first place, live.
Cumulative score of top players
Running total of the best players' score over time. Like kills, but punishing suicides.
Cumulative deaths of top players
Running total of the best players' deaths over time. Even champions die sometimes — here you see how often.
Cumulative matches of top players
Running count of matches played by the best players. Who builds their numbers through persistence.
Elo rating over time
How the top players' Elo changed match by match. Climbing means wins over strong opponents.
Headshots over time
Headshots per period. Grows with player accuracy and the sniper's popularity.
New players over time
How many brand-new people appeared on the server for the first time in each period. The pulse of community growth.
Kills: humans vs bots
Who kills more — humans or bots. Columns show each camp's share of kills over time.
Suicides over time
Suicides per period. Spikes reveal treacherous maps or wild experiments.
Ø kill distance over time
Average kill distance in meters over time. Rising means more sniping, falling means close combat.
Humans at Once Over Time
Peak human players per match over time - real community growth without bot fill.
Bot Difficulty Over Time
Average bot difficulty per period - is the server getting harder?
Reinforcements Over Time (%)
Share of matches where adaptive bot reinforcements kicked in.
Match Tempo Curve
When kills happen within a match - split into tenths of match time.
Server FPS vs Load
Each match as a point: player count vs server FPS.
Activity by day and hour
Kill heatmap by weekday and hour — from the exact time of every kill. Darker cells mean more action.
Curiosities
Kills by distance
Distribution of all kills by distance between shooter and victim. Shows whether the server fights up close or from afar.
Multikills by level
How many Double, Multi, Mega, Ultra and Monster kills happened. The higher the level, the rarer the catch.
Suicides by cause
What people on the server die from without enemy help — falls, own rockets, lava and similar accidents.
Match profile
Which minute of a match sees the most kills. Reveals the typical rhythm from a careful start to the final rush.
Match closeness
Score gap between the winner and the runner-up at the end. Many close finishes mean a balanced server.
Players per match
Distribution of matches by participant count. Shows the most common game size on the server.
Match lengths
Distribution of matches by duration. Short games mean the limit was reached quickly, long ones mean even fights.
Time to first blood
How quickly after match start the first kill lands. Measures how long the initial calm survives.
Sprees by length
Distribution of kill streaks by length. Long streaks are rare — they require surviving under constant pressure.
Special kills
Kills by special means: Shock Combo, telefrag, Redeemer and CampKiller punishments. Treats for connoisseurs.
Players by country
Where the server's human players come from, by IP address. The map of UT3.sk's international fame.
How matches end
Whether matches end by reaching the kill limit or by running out of time. Older matches did not record the end reason — those sit in the “Unknown” category and nothing can be concluded from them.
Overkill Masters
Total damage dealt beyond what was needed for the kill - who keeps firing into corpses.
Airborne Kills
Kills scored while the killer was mid-jump or falling.
Speed at Kill
Average movement speed at the moment of a kill (m/s, min. 10 kills with data).
Kills per Life
How many kills a player gets out of one life on average (min. 10 lives).
Average Life Length
Average seconds survived per life (same players as the kills-per-life chart).
Wire-to-Wire Wins
Wins while leading from the first frag to the end. Full history, ignores the filter.
Comeback Wins
Wins after trailing by 3+ points. Full history, ignores the filter.
Time in the Lead
Share of match time spent in sole lead (min. 5 matches). Full history, ignores the filter.
Match Drama
How many lead changes matches have. More = more drama. Full history, ignores the filter.
Match Length by Player Count
Average match length by how many played.
Match Goal Scores
How matches are configured - distribution of goal scores.
Match Time Limits
Distribution of configured time limits.
High-Ground Battle (Server)
Share of kills from above, level and below (128+ UU height difference).
Item Control vs Winning
Win rate by how many powerups (belt/keg/UDamage) the player grabbed.
Ground vs Air
Share of kills by killer/victim being on the ground or airborne (v5 data).
Maps
Most played maps
Which maps get played the most. Arena popularity by number of matches.
Game modes
Matches split by game mode — Normal, Instagib and others. What the server likes to play.
Map pace (kills/min)
Average kills per minute on each map. Small maps tend to be bloodier than sprawling ones.
Kills by map
Total kills on each map. Combines a map's popularity with its bloodiness.
Ø players per map
Average number of players in matches on each map. Shows which arenas attract full games.
Ø match length per map
Average match duration per map in minutes. Long times mean the limit is harder to reach.
Map treachery
Average suicides per match on each map. High numbers reveal chasms, lava and treacherous ledges.
Ø kill distance per map
Average kill distance on each map. Open maps favor snipers, tight corridors favor the Flak.
Worst FPS Maps
Maps with the lowest average server FPS (min. 3 matches).
Map Closeness
Average winning margin per map - low = nail-biters, high = blowouts.
Match Endings by Map
How matches end on each map. A map where the limit is rarely reached may be too big for the player count — but judge that only from matches with a known end reason.
Weapons
Kill share
Which weapon owns the biggest share of all server kills. The queen of the arsenal in one pie.
Average kill distance
The average kill distance of each weapon. The sniper rules the long range, the Flak the corridors.
Headshot % by weapon
Headshot share for each weapon. The sniper naturally leads; the exceptions are the interesting part.
Weapon popularity over time
How weapon popularity shifted over time. Reveals the server meta — when Flak ruled and when Shock did.
Multikill share by weapon
What percentage of each weapon's kills were part of a multikill. Which gun mows down crowds best.
Weapon vs Weapon
Matchup matrix: which weapon kills which - the victim held weapon is recorded since telemetry v5.
Weapons: humans vs bots
Which weapons humans kill with versus bots. The differences reveal play styles and bot limits.
Hits per Kill by Weapon
How many landed hits a weapon needs per kill - lower = deadlier per hit (min. 20 kills).
Favorite Weapon (Population)
How many players call each weapon their favorite.
Rivalries
No rivalries in the selected filter.
Fair play
Fair-play indicators from server data. No single chart proves cheating — only a value far outside everyone else is suspicious.
Rapid target switches
Percentage of kills that came within 1 second of killing a different victim. Splash multikills form a natural baseline — only a value far above everyone else is suspicious (an aimbot switches targets unnaturally fast).
Suspicious moves
Sudden moves of more than ~50 metres within 2 seconds, per hour of play (telemetry matches only). On maps with teleporters a non-zero value is normal, elsewhere it is not.
Ping stability
The gap between the highest and the average ping in a match. Big swings mean an unstable connection — or deliberate throttling (lag switch). It is calculated as a trimmed mean, so a single one-off spike does not skew the result.
Ping vs Performance
X = weighted ping (ms), Y = K/D. Shows whether higher ping hurts performance.
Visits
Real server visits — including visits where the match never finished (server restart etc.). Filtered by date only; map/mode do not apply to visits.
Time online
Total real time spent connected to the server. Counted from visits, not matches played.
Number of visits
How many times the player connected to the server. Loyalty measured in arrivals, not performance.
Longest visit
The longest single continuous connection in minutes. The marathon runners of server sessions.
Visits over time
Number of connections per period. The server's life curve.
Visits by weekday
Which weekday brings the most visitors. Weekend peaks versus workdays.
Visits by hour
At which hour of the day players connect most often. The evening rush in full glory.
| Player | Visits | Time online | Ø visit | Max | Last seen |
|---|---|---|---|---|---|
| Bogota | 1 | 0,5 h | 28:00 | 28:00 | 08.09.2026 18:12 |
| freedie00 | 1 | 0,3 h | 15:59 | 15:59 | 08.09.2026 18:14 |
| Vulgarus | 2 | 0,1 h | 3:00 | 3:01 | 11.09.2026 23:54 |
| takeiteasy | 1 | 0,0 h | 2:59 | 2:59 | 10.09.2026 11:27 |
| bartery2 | 1 | 0,0 h | 2:00 | 2:00 | 12.09.2026 00:46 |
| greg417 | 1 | 0,0 h | 2:00 | 2:00 | 08.09.2026 18:39 |
| Geozuso | 1 | 0,0 h | 2:00 | 2:00 | 07.09.2026 10:47 |
Recent matches in the filter
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