League Tables and Metric Intelligence

How fast a creator is gaining traction right now across viewers, clips, consistency and live activity.

Blends recent viewer growth, peak viewer growth, clip performance, schedule consistency, category performance and cross-platform activity into a single 0–100 score.

Surfaces creators on the rise — even smaller ones — before they become obvious through raw viewer counts alone.

Short-term spikes from one-off events or collabs can temporarily inflate momentum.

How regular a creator's streaming cadence is — frequency, start times, stream length and gaps between streams.

Combines streams per week, start-time stability, stream-length stability and gap variance into a 0–100 score.

Consistent creators build reliable audiences. Useful when comparing two creators with similar viewer counts.

Does not capture intentional breaks, travel, or planned schedule changes.

How concentrated a creator's activity is on a single platform versus spread across Twitch, Kick, YouTube and TikTok.

Share of live hours, live viewers and clip activity on the creator's primary platform, expressed as a percentage.

High dependency means a creator is more exposed to a single platform's rules, outages or policy changes.

Some creators intentionally concentrate effort on one platform. High dependency is not always negative.

How a creator performs inside each category they stream — hours, average and peak viewers, retention and clip velocity per category.

Aggregates per-category live hours, average viewers, peak viewers, retention and clip output from observed and mock signals.

Helps tell whether a creator is a category specialist or a true variety streamer, and where their strongest audience sits.

Category labels supplied by platforms can be coarse or mis-tagged by the creator.

How efficiently a creator's streams generate clip activity that travels beyond the live audience.

Clips created per stream hour, combined with clip views relative to live viewers.

High clip velocity often predicts discovery and growth on short-form platforms.

Clip counts depend on platform clip tools and on community behaviour, not just creator output.

When during the week a creator typically goes live, shown as a day-by-hour heatmap.

Aggregated start times and live hours grouped by day of week and hour of day.

Helps viewers plan, and helps analysts spot creators with stable, plannable cadences.

Recent schedule changes take time to show up clearly in the pattern.

Other creators a given creator is most similar to based on shared signals.

Scores category overlap, viewer range, shared FiveM server, platform mix, schedule and momentum into a 0–100 similarity score.

Useful for discovering adjacent creators and for grouping creators into peer sets.

Similarity is structural, not stylistic — it does not capture tone, voice or content style.

The overall arc of a stream — does it spike early, hold steady, ramp into a peak, or fade late.

Classifies a stream as strong opening, holding peak, stable, ramping or late fade based on viewer curve shape.

Two streams with the same average viewers can behave very differently. Shape exposes that.

Short streams have less curve to analyse and may be classified less reliably.

How strong viewer arrival is in the first 15 minutes of a stream versus the creator's baseline.

Average viewers in the opening window compared with the creator's recent baseline.

Strong opening pull suggests loyal audience and good notification reach.

Can be inflated by scheduled raids or external promotion.

How quickly a stream reaches its peak concurrent viewers.

Minutes from stream start to the highest concurrent viewer reading. Lower means peaks arrive earlier.

Tells you whether a creator front-loads attention or builds it gradually.

Sensitive to start-time accuracy reported by the platform.

How long a stream stays near its peak viewer count.

Minutes the stream stays within a band around the peak viewer reading.

Strong peak hold indicates content that keeps a packed audience watching.

Defined relative to the stream's own peak, so does not compare absolute size across creators.

How stable viewer counts are through the middle of a stream.

Variance of viewer counts during the middle portion of the stream, normalised against the average.

High stability suggests sustained engagement rather than a quick spike and drift.

Long streams with multiple content segments may show natural variance that is not a problem.

How much the stream loses from peak in its final hour.

Difference between peak viewers and average viewers in the last hour of the stream.

Heavy end decay can indicate fatigue, scheduling issues or a slow wind-down.

A planned soft-close stream may show high end decay by design.

How well a stream recovers viewers after mid-stream dips.

Net viewer recovery after the deepest dip in the second half of the stream.

Resilient streams build sticky communities that come back during the same session.

Dips driven by external events (raids, outages) can distort the read.

How current viewers compare with the creator's recent baseline.

Current concurrent viewers compared with the creator's rolling baseline, shown as a percentage delta.

Surfaces streams that are over- or under-performing for that specific creator right now.

A small baseline can make modest absolute swings look like large percentage moves.

Number of players currently connected to the server.

Aggregate count reported by the server. Aggregate only — no individual player names.

Baseline measure of in-world activity on the server.

Does not say anything about how much of that activity is being streamed.

Maximum player slots the server is configured to allow.

Server-supplied slot limit.

Sets the ceiling for occupancy and for player-based metrics.

Server owners can change the cap. Historical comparisons can shift.

How full a server is right now.

Players online divided by max players, shown as a percentage.

High occupancy near cap indicates a saturated, hard-to-join server.

Server caps can be raised or lowered, changing the meaning over time.

Number of tracked creators currently streaming the server.

Count of tracked creators with live streams linked to this server.

Indicates how much streaming coverage the server is currently getting.

Only counts creators ContentLore tracks — untracked streamers are not included.

Combined live viewers across all tracked streams of this server.

Sum of concurrent viewers for every tracked live stream linked to the server.

Shows the size of the audience the server is reaching right now.

Different viewers may overlap across multiple streams of the same server.

How many viewers each player on the server is attracting on average.

Total live viewers divided by players online. Read as viewers per player.

A server with fewer players can still be culturally important if the multiplier is high.

Skews high when player counts are small. Best read alongside player counts.

How big the audience is for a typical streamer covering this server.

Total live viewers divided by streamers live.

Tells you whether attention is broadly distributed or concentrated on a few large streams.

An average hides distribution. Inspect the linked streams for the full picture.

Share of players on the server who are currently streaming.

Streamers live divided by players online, shown as a percentage.

Low coverage on a busy server signals opportunity — activity exists but visibility is low.

Coverage can spike on small servers where a few streamers swing the percentage.

Whether a server is trending up, holding steady or cooling off.

Combines short- and medium-term player and viewer trends into rising, established, major or fading signals.

Quickly surfaces servers gaining attention before raw player counts catch up.

Server-side events such as updates and wipes can cause short-term spikes that fade quickly.

The highest player count observed on the server in the last 24 hours.

Maximum players-online reading recorded across the last 24 hours of samples.

Captures the server's true ceiling, not just its current snapshot.

Single-sample spikes can dominate if sampling is sparse.

How player activity has moved over the last seven days.

Percentage change in average players online versus the prior seven days.

Smooths out daily noise to show whether the server is genuinely growing or fading.

Treats a one-off event week the same as sustained growth.