Why sports predictions are booming.

Every number below is recomputed from prediction snapshots inside the selected window (last 30 days).

1. 01

   Prediction demand is measurable, not hypothetical

   Our own snapshot log is still filling up — check /trends after the next match cycle to see how many matches we've covered. Every one of those rows was written because a user (or a crawler) hit a match page and asked for a probability read. That is the demand signal, in first-party data.

2. 02

   Esports is now a real professional circuit

   CS2, League of Legends, Dota 2, and Valorant run near-continuous international schedules. Once matches flow through our pipeline, this driver will show the exact per-game split — for now, the log is empty.

3. 03

   AI can finally cover the whole schedule

   Large language models over structured match data can produce calibrated probabilities across a full daily schedule. Once predictions land in the log, this driver will quote the exact count and confidence numbers.

4. 04

   Real-time data is cheap and open

   PandaScore, Abios, and open esports APIs expose team rosters, recent form, and live match state. Once predictions run, this driver will quantify how much of that data we've turned into probabilities.

5. 05

   Mobile fandom is second-screen by default

   Fans watch the stream, then flip to a phone for a probability read. Once traffic hits the app, this driver will show the daily prediction volume that second-screen usage generates.

6. 06

   The schedule never sleeps

   Professional esports runs 24/7 across NA, EU, and APAC. Once predictions accumulate, this driver will show the daily cadence — active days, peak day, and the 30-day distribution.

Every figure above is pulled live from our prediction snapshot log — see the charts and full breakdown on the prediction trends page.