Published August 25, 2026

Research process · 9 minute read

How to Research MLB Home Run Picks

Strong home run research does not begin with one stat. It combines a hitter’s power, the opposing pitcher, expected opportunity, and the game environment into one repeatable process.

Step 1: Confirm the player is starting

Start with the expected lineup, then confirm it when the official lineup is released. A player on the bench may receive only one plate appearance—or none at all. Also check for postponements, late lineup changes, injury news, and doubleheader scheduling.

Lineup position matters because hitters near the top generally have a better chance to receive an additional plate appearance. More opportunity does not guarantee a homer, but it matters when comparing otherwise similar candidates.

Step 2: Establish the hitter’s power profile

Use season-long ability as the foundation, then add recent contact as context. DingerGrid highlights four complementary hitting signals:

Recent performance can show changing contact, but small samples are noisy. Do not erase a player’s larger history because of a few hot or cold games.

Step 3: Study the opposing pitcher

Confirm the probable starter and compare the hitter’s handedness split with the pitcher’s split against that side. Review strikeouts, walks, home runs, barrels, hard contact, fly balls, and expected slugging allowed.

ERA alone is not enough. It summarizes runs allowed, while contact metrics can reveal whether hitters are consistently striking the ball with dangerous combinations of speed and angle.

For a deeper breakdown, read How Pitcher Matchups Affect Home Run Research.

Step 4: Compare pitch mix and hitter performance

Identify the pitches the starter uses most against the hitter’s side: four-seam fastball, sinker, cutter, slider, sweeper, curveball, changeup, splitter, or another offering. Then compare how the hitter performs against those pitch types.

Usage matters. A hitter’s strong numbers against one pitch are less useful when the opposing starter rarely throws it. Location, count, velocity, and movement also affect the matchup, so pitch-type history is evidence—not certainty.

Step 5: Evaluate batted-ball direction

Pull percentage can help connect a hitter’s contact tendencies with a particular ballpark and pitch location. Many hitters create their strongest air contact to the pull side, but not every hitter follows the same pattern.

Treat pull rate as one part of the profile alongside barrels, hard hits, launch angles, and actual power. A pulled ground ball is not the same as a pulled barrel.

Step 6: Check park, weather, and bullpen context

Weather forecasts and probable pitchers can change. Confirm current information close to game time rather than relying on an early-day screenshot.

Step 7: Organize candidates before building tickets

Once the research pool is built, remove duplicates and separate strong cases from uncertain ones. DingerGrid lets you include, lean, lock, or exclude players, select a leg count, and generate unique combinations without repeating the same ticket that day.

1. 01Confirm lineup, probable pitcher, and game status.
2. 02Compare ISO, barrels, hard hits, and launch-angle quality.
3. 03Evaluate handedness splits and the pitcher’s contact allowed.
4. 04Match pitch usage with the hitter’s strengths and weaknesses.
5. 05Check pull tendencies, park, temperature, wind, and roof.
6. 06Account for lineup position, starter workload, and bullpen.
7. 07Deduplicate the pool and build tickets responsibly.

Common research mistakes

• Using a home run drought as proof that someone is “due.”
• Relying on batter-versus-pitcher history with very few plate appearances.
• Ignoring strikeout risk and focusing only on contact when made.
• Forgetting that relievers may cover half of the game.
• Treating odds, alerts, or one highlighted stat as a guarantee.
• Adding the same player twice because he appears in multiple research groups.