Research

We publish what we tested

Most sites selling picks won't tell you when a market is already priced correctly. We backtest our own angles against the close, and we say so either way.

Live studies

Recomputed from our game logs · every player measured against their own baseline

WNBAReal home edge

Home court in the WNBA

How often does the home team win, and by how many points?

54.9%

home team win rate

HomeAway

Win rate54.9%45.1%

Points per game85.683.5

Home teams won 338 of 616 games (54.9%, z = 2.4) and outscored visitors 85.6 to 83.5 per game — about 2.2 points.

How we measured it · 616 games▾

Every regular-season game in our WNBA logs (playoffs excluded — higher seeds host more); final scores are the sum of each team's player points (every player who played is logged).

WNBASmall but real

Does a big scoring night carry over?

After a player scores above her own average, is her next game more likely to be above average too?

+2.3 pts

next-game edge after an above-average night

47.0%

After above-avg game

44.7%

After below-avg game

Next game above own averageaxis starts at 40.9%

After an above-average scoring night, players topped their average again 47.0% of the time; after a below-average night, 44.7% (z = 2.2). A small edge — most likely role and minutes changes (an injury ahead of her, a new starting spot) rather than a 'hot hand'.

How we measured it · 9,375 game pairs▾

Games with 10+ minutes; each player's average is her own for that season (15+ such games). Consecutive games only.

WNBANo effect

Do back-to-backs tire scorers out?

When a team plays on consecutive days, do its players score less than they usually do?

+0.2 pts

on the 2nd night vs her own average

vs own avgGames

Back-to-back+0.24420

1 day rest−0.054,769

2+ days rest+0.034,265

On the second night of a back-to-back, players scored +0.24 points relative to their own season average (z = 0.9), versus −0.05 with one day off and +0.03 with two or more. Fatigue doesn't show up in the scoring column.

How we measured it · 9,454 player-games▾

Rest = days since the team's previous game (from every team's game dates in our logs). Each game is scored against that player's own season average (10+ minutes, 15+ such games).

Market backtests

Already live · deepest example today

What We've Measured — College Football

Four angles we tested and killed on our own archive of FBS results and closing lines — SP+ ratings vs the spread (49.8% ATS on 1,589 games), wind, rain and altitude on totals. Published with the same numbers whether they worked or not.

Read the full page →

Other written studies

College Football — SP+, wind, rain, altitude

The angles above, in full: methodology, sample sizes, and the ones that didn't beat the closing line.

NFL — Numbers

Team and player trends pulled from the same gamelog archive our NFL picks are graded against.

WNBA — Numbers

Team and player trends from the WNBA box-score archive, same treatment.

Our track record

MLB — Results

Every MLB pick we've published, graded win or loss, in full.

NFL — Results

Every NFL pick we've published, graded win or loss, in full.

WNBA — Results

Every WNBA pick we've published, graded win or loss, in full.

MLB — NRFI record

Every no-run-first-inning pick, graded, against the league base rate.

MLB — Closing line value

Whether the line moved our way after we made the pick — the standard sportsbooks themselves use to judge a bettor.

Descriptive market statistics, computed daily

64%

of MLB props priced +200 or longer

Of 1,227,167 graded props this season, 782,904 closed at +200 or longer. Staked flat at one unit each, that group returned -29.7%. This describes what the shelf has done, not a strategy.

mlb · computed from props_resolved

CFB is our deepest write-up because that market has been backtested most extensively — but it's not the only one. NFL and WNBA have their own published number studies above, and our full pick history is public too. Same standard everywhere: publish it whether it worked or not.