What actually predicts next week's fantasy points?
Every week, fantasy football managers choose between players using recent form, matchups, and Vegas lines.
This project tests those instincts against 27 NFL seasons (1999-2025, 144,000 player-games): how the game
changed, what never did, a projection model scored on seasons it never saw, a season-long model for drafts, and
live projections for the 2026 season (this week's).
Live, phone-friendly version: joshwilliams332.github.io/nfl-historic-analysis
Python · pandas · scikit-learn · matplotlib · Jupyter · Power BI (DAX) · JavaScript · data from nflverse
Findings: the modern game (2021-2025)
1. Volume is a trait. Touchdowns and efficiency are mostly noise.
Averaging a stat over odd weeks and over even weeks, then correlating the two halves, separates role from luck.
Targets and carries repeat almost perfectly (r ≈ 0.9). Touchdowns repeat far less (r ≈ 0.4-0.6), and yards per
target or per carry hardly repeat at all. When a player's points outrun their volume, expect a pullback.
2. The full season beats the hot hand
The last game is the weakest predictor at every point in the season, and the last three games trail the
season-to-date average. Early in the year, last season's average is as informative as this season's.
3. Matchups and Vegas totals matter, but far less than people assume
From the toughest fifth of matchups to the softest, scoring moves about 10% relative to a typical week. The
Start/Sit heuristic on my fantasy site (Mingus Sports) assumes about
38% across the same groups. Vegas implied totals add about 5% once a player's average is known.
4. A simple model beats every rule of thumb on unseen games
Trained on 2021-2023, tuned on 2024, tested once on 2025 (2,591 player-games):
| Projection | MAE (pts) | Correlation | Start/sit accuracy |
|---|
| Last game | 7.53 | 0.290 | 58.7% |
| Last 3 games | 6.24 | 0.400 | 62.6% |
| Season average | 5.87 | 0.450 | 64.1% |
| Mingus site formula | 6.08 | 0.432 | 64.0% |
| Gradient boosting | 5.63 | 0.475 | 64.9% |
| Ridge regression | 5.67 | 0.488 | 65.5% |
Start/sit accuracy: across every pair of same-position players in the same week, how often the one projected
higher actually scored more (50% = coin flip).
A linear model was enough. Gradient boosting didn't find interactions worth its extra complexity.
5. Know when it's a coin flip
When two players' projections are under 2 points apart, no projection is much better than a coin. At 6+ points,
the call is right about 4 times in 5.
What the model weighs
Target share, this season's average, and last season's average carry the most weight. Touchdowns per game is
negative once points and volume are known: the model has learned to expect touchdown streaks to fade.
Findings: 27 seasons of history (1999-2025)
6. The game changed...
Wide receivers' share of top-150 fantasy points fell from about 46% to about 37% (3-season average). Quarterbacks and
tight ends took most of it.
The 300-carry back went from about 10 a season in the early 2000s to none in 2023, with a small rebound since.
7. ...but what predicts fantasy points didn't
Season average beat the last 3 games, and the last 3 beat the last game, in all 27 seasons. Finding 2 is not a
quirk of the modern NFL.
Touchdown spikes fade over full seasons too. The top fifth by touchdowns per touch dropped from 9.8% to 6.4% the next
year, while their touches per game held steady. Year-to-year correlation: 0.54 for TD rate, 0.85 for touches per game.
8. Aging curves
Delta method (each player compared only with themselves, year over year). Running backs peak at about 24 and fall
off steeply after 26. Receivers and tight ends peak around 25-26 and decline more gradually. Quarterbacks peak around
30 and hold up into their mid-30s. Survivors only, so real declines are steeper.
9. More history doesn't make a better weekly model
| Ridge trained on | Rows | 2025 MAE | Start/sit accuracy |
|---|
| 2021-2023 | 7,894 | 5.674 | 65.5% |
| 2015-2023 | 23,280 | 5.668 | 65.5% |
| 2009-2023 | 38,186 | 5.670 | 65.5% |
Five times the data, the same accuracy. The ceiling is the noise in a single game, not a shortage of examples.
Better information (injuries, snap counts, depth charts) is what would move it.
Better information: snap counts and injury reports
Players who suit up with an injury tag score less than usual: 11% below a typical week when listed questionable, 15%
when they missed practice. But only about 6% of player-games carry a tag, so adding the report barely moves overall
accuracy.
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