The slate, in one place.
Start with the sport and market. Bring scattered prop lines into a workspace built for comparison.
Sports data → a searchable board
Founders early access
Find the edge.
SPORTS DATA. A CLEARER PICTURE.
Find the edge.
See the
evidence.
A thousand numbers. One place to make sense of them. Bring prop lines, player history, and market context into focus.
$14.99/month · First 30 subscribers
Monthly · Cancel anytime
THE RESEARCH LENSIllustrative sequence
MARKET COMPARISONCS2
Aster Maps 1–2 killsPP 28.5UD 29.51.0
line gap
line gap
PLAYER HISTORYL10
7/10above the
28.5 line
28.5 line
EVIDENCE, CONNECTED
+11.2 ppestimated edge*History + line + probability
Demo data · *61.2% estimate − 50% reference
YOUR NEXT RESEARCH SESSION STARTS HERE
The board is just
the beginning.
Switch sports. Rank the lines.
Open a prop to see what’s underneath.
Workspace/Edge FinderTHE SHORTLIST
Start with the signal.
Select a row to inspect the evidencePP + UD
Illustrative players & data. Not live lines or betting recommendations.*Demo edge = estimated probability − 50% reference.
Compare the line
Inspect the history
Understand the uncertainty
FOLLOW THE EVIDENCE / 01
Less noise.
More understanding.
Follow one illustrative prop from a fragmented market to a researchable decision. Scroll through the process, or choose a step.
RESEARCH TRACEInteractive demoProp lines → player history → market comparison → probability context → research insight.
Illustrative player, history, and estimates. Not a live prediction.
Every line is a question.
28.5 kills. Before choosing a side, pin down the player, the market, and the threshold that matters.
Aster · CS2 · Maps 1–2 killsGo beyond the percentage.
Seven hits from ten games is a starting point. Look at the distribution, the misses, and how much history is actually available.
Observed results ≠ a forecastSame player. Different bar.
A line of 28.5 and a line of 29.5 ask different things of the same performance. See the difference before comparing the payout.
PrizePicks 28.5 · Underdog 29.5 · DemoAn estimate with context.
Keep the model estimate separate from the historical hit rate. Then compare it with the relevant break-even probability.
The separate CS2 learning model is in trainingA reason to investigate.
The result is a clearer research trail: the line, the sample, and the assumptions. You decide what the evidence is worth.
Go deeper into the research01 / RESEARCH WITH CONTEXT
A percentage is a start.
The sample is the story.
Was it five games or fifty? Against which opponent? In what conditions? Deep Research keeps those questions attached to the number.
01
Open the game log.
See each performance against the line, with recent windows and matchup context.
02
Ask a better question.
Apply sport-specific filters. Find the games that actually resemble the situation.
03
Know how much to trust it.
Keep sample size and uncertainty in view. A higher hit rate can come with less evidence.
DEEP RESEARCHRepresentative demo
JP
Jordan Parker
MLB · Hits + runs + RBIs · Over 1.5
Pitcher hand
Venue
Try a filter. The sample, hit rate and interval recalculate together from the same illustrative game log.
02 / ONE CONNECTED WORKFLOW
From a better line
to a more considered slip.
Keep the research together. Compare the price, explore the player, and inspect the whole entry before you leave the workspace.
COMPARE LINES
Same player. Different proposition.
A half-point matters. Surface cross-app differences and investigate whether a line is an outlier or simply stale.
AsterCS2 · Maps 1–2 killsDemo
PrizePicks28.5Lower line
Underdog29.5Higher line
For More, 28.5 is the lower threshold. Payouts and availability still matter.
SLIP STUDIO
Good legs need a closer look together.
Build an entry with estimated hit probability, payout-based EV, and correlation context where available.
Build a demo entryIndependent events
Selected legs2
All-leg estimate—
Demo multiplies illustrative probabilities for separate events. The app also evaluates payout rules and available correlation evidence.
THE PROPS BOARD
Try the board Your whole slate. Your way in.
Search players, compare recent hit-rate windows, explore price movement, and open the research behind any available prop.
03 / SIX SPORTS. SPECIFIC CONTEXT.
The same workspace.
Different questions.
Research should fit the sport. Available histories and filters depend on the player, market and source coverage.
CS2Supported
Counter-Strike 2
Map kills & headshots
- Map and series context
- Recent form & opponent history
- Map-level game logs
MLBSupported
Major League Baseball
Pitcher & hitter props
- Pitcher-hand splits
- Home, away & conditions
- Opponent matchup context
NFLSupported
National Football League
Passing, rushing & receiving
- Player game logs
- Recent performance windows
- Matchup research
WNBASupported
Women's basketball
Points, rebounds & assists
- Recent-game distributions
- Venue & result splits
- Player performance history
LoLSupported
League of Legends
Series & map kills
- Map-by-map performances
- Series-length context
- Opponent & team form
VALSupported
Valorant
Series & map kills
- Per-map player statistics
- Recent series performance
- Matchup context
Platform lines from PrizePicks and UnderdogSportsbook consensus where available
04 / SHOW YOUR WORK
The evidence stays visible.
So does the uncertainty.
PropNexus is built for informed decisions. Estimates, observed results and unknowns have different jobs—and deserve different labels.
Start with observed results.
Game logs power historical hit rates. The sample count stays beside the percentage so a short streak has context.
7 / 10Observed hits, not a promise.
Make uncertainty readable.
Wilson confidence intervals put a range around a historical hit rate. Smaller samples usually mean wider uncertainty.
Read the range, too.
Keep estimates accountable.
Estimated edge and slip EV depend on probabilities, lines and payout assumptions. They are estimates you can question.
P → EVAssumptions affect the outcome.
The separate CS2 learning model is in training. Its development is not presented as a proven performance claim.
05 / FOUNDERS EARLY ACCESS
A sharper workspace.
A better starting price.
The first 30 subscribers get the full workspace at the founders rate.
Keep that price for as long as you stay subscribed.
FOUNDERS50% off standard
$14.99/ month
Full access. A price that stays with you.
Limited to the first 30 subscribers
- All six supported sports
- Edge Finder & Props Board
- Player Research & Deep Research
- Compare Lines & Slip Studio
- Founders price locked while subscribed
- Help shape what gets built next
Create your account · Secure checkout by Stripe · Cancel anytime
STANDARDFull price
$29.99/ month
The same full workspace, at the standard rate.
- All six supported sports
- Every core research module
- Full platform access
Founders save $15 every month compared with the eventual standard price.
BEFORE YOU JOIN
Good questions.
Straight answers.
The important details, without the fine-print hunt.
What do I actually get with PropNexus?
A player-prop research workspace: a searchable Props Board, Edge Finder, player histories, Deep Research filters, cross-app line comparison and Slip Studio. Coverage varies by sport, player and available source data.
How do I subscribe?
Choose a plan, create your PropNexus account, and Stripe’s secure checkout opens. Your subscription starts when checkout completes, and you can cancel anytime in Settings under Manage billing.
How does the founders price work?
The founders offer is $14.99/month for the first 30 subscribers, compared with the eventual $29.99 standard price. The founders rate stays locked for as long as you remain subscribed. Joining the list alone does not complete a subscription or reserve paid access.
Is a high hit rate the same as an edge?
No. A hit rate describes the observed sample at a given line. Estimated edge compares a probability estimate with the relevant price or break-even requirement. Small samples, changing matchups and payout rules all affect how you should interpret those numbers.
Are these picks guaranteed to win?
No. PropNexus is research and analytics tooling. Historical performance, model estimates and positive expected value do not guarantee future results. You make the final decision.
Can I use it on my phone?
Yes. The web app adapts its boards, player cards and research panels for mobile. You can use the same research workspace from a phone, tablet or desktop.
Are the examples on this page live?
No. The interactive demonstrations use fictional players and clearly labeled illustrative data to explain the workflow. They are not current platform lines, predictions or betting recommendations.
BUILT TODAY. DEVELOPING TOMORROW.
A clear line between now and next.
Early access should mean visibility into the product—not guessing which features exist.
The research workspace
Six-sport board, Edge Finder, player research, line comparison and Slip Studio.
Deeper matchup context
Extending opponent and defense-strength research across sports.
The CS2 learning model
Self-grading projections under development. No promised accuracy or launch date.
Broader coverage
College football and more platform coverage, as reliable sources become available.
FOR DISCORD COMMUNITIES
Bring better research to your server.
Apply for a unique member discount code and a commission on subscriptions referred through it.
Make the research
part of the decision.
Get founders access $14.99/month · First 30 subscribers · Cancel anytime