TrendForge
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How We Score Games

Most trend tools answer "what's popular?" TrendForge answers a different question: where is the content gap? A game can be soaring on Steam while YouTube coverage is still thin — that gap is where small and mid-size creators get a real chance. This page explains the methodology behind every score on the site.

Opportunity Score (0–100)
Opportunity = w₁·Demand + w₂·Supply + w₃·Timing

Three peer signals, each on its own 0–100 scale (higher is always better), blended into one Opportunity score. The blend is run through a fixed calibration curve so the headline number lands on the same 0–100 opportunity scale used by mainstream trend dashboards — a daily top pick reads ~90–94, a saturated evergreen reads ~50 — while the three sub-signals stay on their raw, legible scales. An earlier multiply formula (“Trend × Gap × Freshness × Momentum”) collapsed real-world picks to around 40/100 because any single sub-1 factor halved the score; the blend keeps every signal legible and on the same scale.

1

Demand — is attention there? (0–100)

weight on growth, not size

Heat is measured by rate of change, not absolute size. A giant like CS2 is always big; that tells a creator nothing. We weight growth highest so "rising now" beats "always large".

Demand
Demand = weighted(player growth, player base, search momentum)
2

Supply — how open is the lane? (0–100, higher = less crowded)

creator supply

The flip side of competition. We first score how saturated the YouTube shelf is (video density + big-channel dominance, 0–100, higher = more crowded), then invert it so a wide-open game scores high. High dominance means even a good small-channel video gets buried — so it pushes Supply down.

Supply
Supply = 100 − Competition (video saturation + big-channel dominance)
3

Timing — is now the moment to post? (0–100)

momentum signal

Timing is, above all, a momentum read: how sharply a game is rising right now (Steam player growth trend). A game that's surging scores high; one that's flat or declining scores low. A launch or major-update window adds a bonus on top — the moment a creator wants to be early. Weights are tuned server-side.

Timing
Timing = momentum(player growth) + launch-window bonus
4

Confidence & risk flags — advisory, not a demotion

noise filter

Some spikes are misleading. Each game is checked for three risk flags, shown alongside the score rather than folded into it — so a flagged pick is never hidden, just labeled, and you decide.

discount — game is on sale; player spike may be price-driven, not organic
unsustained — sharp spike, no launch/event, low base: possible one-day meme
ambiguous — generic/short name; search intent may be split

Confidence is derived from flag count: 0 = high, 1 = medium, ≥2 = low. It is a peer signal to Opportunity, not part of the blend — matching how serious creators actually read a recommendation (a "why" before a "how much").

5

Fit — realistic for your channel size

per-card signal

A topic realistic for a 100K channel can be a dead end for a new one. The dashboard's channel-size selector re-reads each card's Fit from the same big-channel dominance signal, scaled by your tier: 50K+ (unaffected) → 10K–50K → 1K–10K → Under 1K (most sensitive to dominance). Fit labels: Good / OK / Risky for your size. The feed's default sort stays Opportunity; Fit is a per-card read.

Worked example: rising indie vs a blockbuster

Two games, same shelf, opposite verdicts. This is why raw popularity is the wrong sort.

Signal (0–100)Rising indie (launch + surging)Saturated blockbuster
Demand7855
Supply3224
Timing10017
Opportunity9053

The blockbuster has higher raw popularity — a best-seller list would rank it first. TrendForge ranks the indie, because demand is climbing into a wide-open lane at the right moment. That is the judgment a creator actually needs.

Where scoring ends and the LLM begins

Scoring is a deterministic formula — fully explainable and tunable, the same math every day. An LLM is used only on the top-ranked games to turn the score breakdown into concrete title/angle ideas. The model never touches the numbers; that separation keeps the ranking trustworthy and lets us tune weights over time against real creator outcomes.

Data sources & limits

Public signals only: Steam / SteamCharts (players, growth, discounts), the YouTube Data API (recent videos, creator supply), and Google Trends (momentum). Recomputed once a day. Scores are research support, not a guarantee of views or growth — validate the evidence before recording. Not affiliated with Valve, Google, or YouTube.

See it in action on the today's ranking, or break down any game on its detail page.