Guide
How PropPrizm Works
A practical walkthrough of the matchup projections, player research cards, and results tracking.
1
The Tools
PropPrizm's views work best together:
- Matchup Dashboard — statistical projections for each game. Shows you what the model expects from each pitcher and batter given the specific matchup, park, umpire, and weather conditions.
- Player Cards — click any player for the full research view: game logs against the current line, pitch-arsenal matchups, Statcast quality metrics, and recent form.
- Track Record & Divergence Finder — every projection is logged and graded against the box score, and the Divergence Finder surfaces players whose results are running ahead of or behind their underlying numbers.
The workflow
Use the Matchup Dashboard to understand what's likely to happen → open the player card to see whether the underlying numbers support it.
2
Reading the Matchup Dashboard
Select a game from the strip at the top to load its matchup card. The card is split into a pitcher panel and a batter table.
Pitcher Panel
The key numbers to focus on:
7.4Pred Ks
5.8Est IP
8.9Recent K/9
9.1Season K/9
- Pred Ks — the model's strikeout projection for this start. This is the number to compare against the market's standard K line.
- Est IP — estimated innings pitched. Lower IP = fewer total K opportunities regardless of K rate.
- Recent K/9 / Season K/9 — raw rate stats for context. A gap between recent and season rates signals momentum.
Adjustments Panel
Below the stats you'll see context factors that went into the projection. These are collapsible — click any header to expand:
- Park Factors — some parks suppress strikeouts (e.g., Coors Field) or inflate them. A SO factor below 1.0 drags the K projection down.
- Umpire — umpires with a tight zone generate more walks and contact; umpires with a wide zone favor strikeout pitchers.
- Weather — wind blowing in suppresses home runs; high humidity or cold air affects carry.
Batter Table
Each lineup slot shows the batter's 2026 stats and Statcast quality metrics. Key columns:
- xK / xHits / xHR — the model's per-plate-appearance projections for that batter against this specific pitcher.
- K% — current season strikeout rate. High K% batters boost pitcher K projections.
- xBA / xwOBA — Statcast expected metrics. xBA above actual AVG = batter is due for positive regression.
- Barrel% / HH% — barrel rate and hard-hit rate. Useful for evaluating HR and total bases props.
Tip — lineup confirmation matters
Projections improve significantly once lineups are posted (typically 1–3 hours before first pitch). Check back closer to game time for the most accurate numbers.
3
Going Deeper with the Player Card
Click any pitcher or batter on the dashboard to open their research card — the full picture behind the projection.
What's on the card
- Game log — every recent game charted against the current stat line, with a movable line stepper. Hover (or tap) a bar to see that opponent's team splits for the stat you're viewing, with league ranks.
- Pitch-arsenal matchup — for batters, how they perform against each pitch the opposing starter actually throws (xBA, K%, whiff per pitch type). For pitchers, their own arsenal quality.
- Statcast quality — xBA, xwOBA, barrel rate, hard-hit rate. Expected metrics above actual results signal positive regression coming; below, the opposite.
- Recent form — the last several games with context, so a hot or cold stretch is visible next to the underlying quality numbers.
The sweet spot
The strongest research reads are players where: (1) the model projection is meaningfully different from the market's standard line, (2) the pitch-arsenal matchup supports it, and (3) recent form doesn't contradict it. When all three align — that's a signal worth studying.
4
A Step-by-Step Research Process
1
Scan the slate
Open the Matchup Dashboard and skim the day's games. Look for starters with high projected strikeouts or batters the model rates well above their usual output.
2
Validate the matchup
For any pitcher projection that stands out, pull up that game. Does the matchup support it? Check the opposing lineup's K% — if it's high, that's confirmation. Check park SO factor and umpire tendency.
3
Open the player card
Look at the game log against the line, the pitch-arsenal matchup, and the Statcast quality metrics. The projection should have a visible "why" behind it — if it doesn't, treat it with skepticism.
4
Check recent form honestly
A hot streak with a matching matchup is a real signal. A cold stretch needs explaining — either the expected metrics say it's bad luck, or the model may be missing something.
5
Wait for lineup confirmation
If the opposing lineup isn't posted yet, consider waiting. Projections sharpen considerably once the actual batting order is known — a projection can move a full strikeout when the lineup drops.
5
Important Disclaimers
- PropPrizm provides statistical projections and analysis for informational and entertainment purposes — not guaranteed outcomes or gambling advice.
- The model is strongest for pitcher strikeout projections given the volume of historical data. Batter projections (hits, HRs, total bases) have more variance.
- Baseball is high-variance: a single game proves nothing in either direction. Judge projections over large samples — that's exactly what the Track Record page is for.
- PropPrizm is in beta. Projections will improve over the 2026 season as more data accumulates.
Questions? Reach us at propprizm@gmail.com