SwishLand is a player intelligence dashboard built over 10+ years. It uses AI to generate fair market projections, surface edges, and tell you exactly where the books are wrong.
Most bettors face the same problems every single day.
Most projection tools use box score averages. SwishLand uses usage data — minutes projection, touch rates, pace factors, and matchup context — to estimate what a player should actually produce. Then it compares that against the sportsbook line to show you exactly where the market is off.
Last 10 game trend charts with adjusted closing lines vs. expected value. See the Delta Edge — where usage consistently outpaces market pricing.
The green dashed line is usage-based expectation. The blue line is the sportsbook's adjusted closing line. When green consistently sits above blue — that's the Delta Edge. The market is underpricing this player.
When a star player goes down, most bettors guess who benefits. SwishLand shows you exactly — usage redistributes automatically in the model, so you see updated projections the moment a player is ruled out. No guessing. No lag.
SwishLand has a built-in AI that knows every player, every matchup, and every edge on the slate. Ask any question and get instant answers backed by SwishLand projections, historical data, and edge analysis — not generic AI guesses.
No spreadsheets. No digging through box scores. No wasted time. Just ask — and get the context you need to make a sharper decision.
SwishLand projections tracked across NBA, NFL, and WNBA.
While betting professionally, I built models the same way sharp syndicates did — usage-based, market-driven, built on real data. When AI and machine learning started to mature, I started integrating those tools into the models, pushing the projections further than anything I could build manually.
That process took over a decade of real-money testing, refinement, and iteration. When I partnered with Josh and the Land Your Bets brand, the model found its audience. Today SwishLand powers every edge, every projection, and every piece of analysis on the platform.
It's not a tool we bought. It's a tool we built.
"This is the tool I wish we'd had 15 years ago." — Travis
Meet the Full Team →From the LYB Discord community.
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