PIPER Now Covers 45 Sports. Here Is Why That Matters.

From 5 Sports to 45

When we built the first version of PIPER, we covered NBA, NFL, NCAAB, NHL, and MLB. Those are the marquee American markets. They are well-known, well-traded, and where most bettors spend their time.

They are also the most efficiently priced markets in the world.

That is the problem.

The books have their best analysts pricing NFL spreads. NBA totals get serious attention. The major leagues are hard to beat because information is fast, volumes are high, and the lines are tight.

So we started asking a different question. Where are the books less sharp?

The answer led us to expand to 45 sports.

Where the Inefficiencies Are

College sports are one of the largest inefficiency pools in American sports betting. College baseball, softball, volleyball, and hockey lines are set with less precision than NFL or NBA. Public perception drives more of the movement. Historical data is harder to find. We loaded 5 years of ESPN data for all of them and built full pipelines.

Women's sports are consistently underanalyzed. WNBA, NCAAB Women, NWSL, LPGA, NCAA Softball, and NCAA Volleyball lines are all influenced more heavily by public money because sharp bettors have historically paid less attention. That dynamic creates opportunity for a data-first approach.

Tennis has a specific structural edge available. Court surface — clay, grass, or hard court — affects player performance in ways that are statistically significant. A player's win rate on clay can differ from their hard court rate by 15 to 20 percentage points. Not every book fully adjusts for surface transitions. We track surface as a dedicated signal on every match for both ATP and WTA.

Esports is the most uncharted territory we cover. Markets are thin. The same confluence methodology applies. We require 2 or more independent signals regardless of the sport. PandaScore provides historical data for League of Legends, Dota 2, and CS2.

The Full List

Basketball: NBA, NCAAB Men, NCAAB Women, WNBA Football: NFL, NCAAF, CFL Baseball and Softball: MLB, NCAA Baseball, NCAA Softball Hockey: NHL, NCAA Hockey Soccer: Premier League, La Liga, Bundesliga, Serie A, Ligue 1, Champions League, MLS, NWSL Golf: PGA Tour, LPGA Tour, LIV Golf, DP World Tour Tennis: ATP, WTA Combat Sports: UFC, Boxing Racing: NASCAR, Formula 1 Rugby and International: Six Nations, Super Rugby, NRL, AFL, Cricket IPL Esports: League of Legends, Dota 2, CS2 Volleyball: NCAA Volleyball Niche Markets: Darts, Snooker, Table Tennis, Handball, Horse Racing, Pickleball

Confluence Engine v3

Alongside the data expansion, the confluence scorer was upgraded from 5 signal paths to 15.

New signals added: rest differential, travel fatigue, weather conditions for outdoor venues, officiating crew tendencies, head to head situational ATS records, home and away situational ATS, motivation index, line movement confirmation, and steam move detection across 8 sportsbooks.

The minimum signal requirement stays at 2. Most games still get rejected. The engine is just working with significantly more data across significantly more markets.

Free Picks Start Today

Starting March 11th, we are posting free picks on Twitter with the full signal breakdown shown. Not just the pick, but every signal that triggered it and why.

If you want to follow along or get notified when full access opens, sign up below.