Dodgers vs San Francisco Giants Match Player Stats

The dodgers vs san francisco giants match player stats for September 26, 2026, provide a detailed look at two National League West teams heading in very different directions. The Los Angeles Dodgers enter the matchup at 96-60 and in first place, while the San Francisco Giants sit at 64-92 in fourth. The Dodgers have also won four straight games and lead the 2026 regular season series 6-4. San Francisco, meanwhile, has lost three consecutive games.

The matchup is scheduled for Oracle Park in San Francisco, with the official MLB schedule listing a 1:05 PM PDT start on September 26. Tyler Glasnow is listed as the Dodgers’ probable starter, while the Giants’ starting pitcher was still undecided in the supplied matchup data.

For readers searching for the dodgers vs san francisco giants match player stats, the most useful approach is not simply to look at the win-loss records. The numbers reveal important differences in hitting production, run creation, pitching efficiency, home and road performance, recent form, and individual player impact.

This breakdown brings those figures together to explain what the statistical picture says about the matchup.

Dodgers vs San Francisco Giants Match Player Stats

The clearest starting point is the overall team comparison.

Category	Los Angeles Dodgers	San Francisco Giants
Record	96-60	64-92
NL West Standing	1st	4th
Winning Percentage	.615	.410
Team Batting Average	.257	.247
Runs	780	656
Hits	1,349	1,303
Home Runs	197	177
OBP	.339	.308
SLG	.426	.405
ERA	3.62	4.39
WHIP	1.15	1.37
Walks	471	581
Strikeouts	1,450	1,159
Opponent Batting Average	.219	.249
Night Record	76-41	40-55
Last Five Games	4-1	2-3
Current Streak	W4	L3
Series Record	Dodgers lead 6-4	Dodgers trail 4-6

These numbers show that the Dodgers have produced more runs despite only a modest advantage in batting average. That difference matters because batting average does not capture every way a team creates offensive opportunities.

Los Angeles has a .339 on-base percentage compared with .308 for San Francisco. The Dodgers also have a .426 slugging percentage compared with .405 for the Giants. MLB defines OBP as the frequency with which a hitter reaches base and SLG as total bases per at-bat, making the two figures useful complements to batting average.

The pitching comparison is even more pronounced.

Los Angeles has a 3.62 team ERA and 1.15 WHIP, while San Francisco has a 4.39 ERA and 1.37 WHIP. WHIP measures walks and hits allowed per inning and is commonly used to evaluate how effectively a pitcher limits baserunners.

That combination gives the Dodgers an advantage in both run prevention and offensive efficiency based on the supplied season numbers.

Offensive Production Comparison

The Dodgers have scored 780 runs compared with 656 for the Giants.

That is a difference of 124 runs over 156 games, or roughly 0.79 additional runs per game for Los Angeles.

The Dodgers have also recorded 46 more home runs and 46 more hits despite playing the same number of games. Their advantage in OBP and SLG adds further context to the raw totals.

Dodgers Batting Profile

Los Angeles enters the matchup with:

• .257 team batting average
• .339 OBP
• .426 SLG
• 1,349 hits
• 197 home runs
• 780 runs

Those figures describe an offense that combines contact with extra-base production and regular opportunities to put runners on base.

Shohei Ohtani leads the Dodgers in the supplied home run and RBI categories with 30 home runs and 80 RBIs.

Freddie Freeman leads the team in batting average at .292.

The difference between those two statistical roles is worth noting. A player leading in home runs does not necessarily lead in batting average, while a high batting average does not automatically translate into the most runs driven in. Baseball offense is built from several interconnected events.

Giants Batting Profile

San Francisco enters with:

• .247 team batting average
• .308 OBP
• .405 SLG
• 1,303 hits
• 177 home runs
• 656 runs

Rafael Devers leads the Giants with 37 home runs and 98 RBIs.

Jung Hoo Lee leads San Francisco with a .276 batting average in the supplied data.

The Giants therefore have a notable individual power producer in Devers, while Lee represents the team’s leading batting average figure.

The team-level difference is that Los Angeles has generated more total offensive production across the lineup.

Key Dodgers Players to Watch

Individual player statistics become more meaningful when viewed in the context of the team’s overall offensive profile.

Shohei Ohtani

Ohtani is listed as the Dodgers’ home run leader with 30 home runs and team RBI leader with 80.

Those numbers make his plate appearances particularly important in a matchup where San Francisco needs to prevent the Dodgers from turning baserunners into multiple-run innings.

His value in this statistical preview is not based on one category alone. The combination of home run production and RBI output indicates that he has been a central part of the Dodgers’ run-producing structure.

Freddie Freeman

Freeman’s .292 batting average is the highest listed mark among Dodgers players in the supplied data.

A high batting average can be especially useful when considered alongside team OBP and SLG. A hitter who consistently records hits can help sustain innings, move runners into scoring position, and create additional opportunities for middle-of-the-order power hitters.

Freeman’s number therefore fits into a larger offensive sequence rather than existing as an isolated statistic.

Tyler Glasnow

Glasnow is the most important pitching name in the matchup data.

His supplied statistics are:

• Record: 5-1
• ERA: 3.46
• WHIP: 0.96
• Innings pitched: 67.2
• Hits allowed: 42
• Strikeouts: 87
• Walks: 23
• Home runs allowed: 7

The 0.96 WHIP is particularly notable because it indicates that he has limited the combination of hits and walks that create traffic on the bases.

His 87 strikeouts over 67.2 innings also point to a high strikeout rate. Based on those innings and strikeout totals, he has recorded roughly 11.6 strikeouts per nine innings.

The 42 hits allowed across 67.2 innings work out to approximately 5.6 hits per nine innings.

ERA remains an important measure, although MLB notes that park and defensive factors can influence ERA, which means it should be interpreted in context rather than treated as a complete description of pitching quality.

The combination of a 3.46 ERA and 0.96 WHIP makes Glasnow one of the most important statistical variables in this game.

Key Giants Players to Watch

Rafael Devers

Devers leads the Giants in the supplied data with:

• 37 home runs
• 98 RBIs

Those are the highest listed power and run-production totals on the San Francisco side.

His 37 home runs exceed Ohtani’s 30, while his 98 RBIs also exceed Ohtani’s 80. That gives San Francisco a major individual power source even though the Giants trail the Dodgers in overall team runs.

This distinction is important when interpreting team statistics. A team can have a lower overall offensive output while still possessing players capable of changing a game with one swing.

Jung Hoo Lee

Lee leads the Giants with a .276 batting average in the supplied statistics.

That figure is 29 points below Freeman’s .305? No. The correct comparison from the supplied data is Freeman at .292 and Lee at .276, giving Freeman an advantage of 16 percentage points.

Lee’s role is therefore more closely associated with San Francisco’s contact production than its leading home run totals.

One important caveat is that the supplied injury list also identifies Jung Hoo Lee as injured. His availability should therefore be confirmed before using his individual statistics to project the final lineup.

Tyler Glasnow vs. the Giants Offense

The most direct statistical question is how San Francisco’s offense matches up against Glasnow.

The Giants have 656 runs and a .247 batting average as a team. Glasnow, meanwhile, has allowed a .96 WHIP and recorded 87 strikeouts in 67.2 innings.

That creates an interesting contrast.

San Francisco’s path to offensive production may depend heavily on avoiding empty plate appearances and taking advantage of any baserunners created by walks or hits. Glasnow’s low WHIP indicates that he has generally limited those opportunities.

His seven home runs allowed are another important number. Home runs are one of the fastest ways for an offense to overcome strong baserunner prevention because a single swing can produce multiple runs.

That makes Devers particularly relevant to the pitching matchup.

If San Francisco can generate traffic before Devers bats, his home run and RBI production becomes more dangerous. If Glasnow consistently keeps the bases empty, the Giants have fewer opportunities to turn his power into large innings.

Dodgers Pitching vs. Giants Pitching

The team pitching comparison strongly favors Los Angeles in the supplied statistics.

The Dodgers have a 3.62 ERA compared with 4.39 for San Francisco.

They also have:

• 1.15 WHIP versus 1.37
• .219 opponent batting average versus .249
• 1,450 strikeouts versus 1,159

The Dodgers have therefore recorded 291 more strikeouts as a team.

At the same time, San Francisco has issued 581 walks compared with 471 by Los Angeles.

That difference is significant because walks extend innings without requiring the opposing offense to record a hit.

The Dodgers’ combination of lower ERA, lower WHIP, lower opponent batting average, and more strikeouts suggests stronger run prevention across the season represented by the supplied statistics.

Why WHIP Matters in This Matchup

WHIP is especially useful for understanding this game because it focuses on the frequency with which pitchers allow hits and walks.

The Dodgers’ 1.15 team WHIP means they have allowed substantially fewer baserunners per inning than the Giants’ 1.37 figure.

That does not mean every inning will follow the season average. Baseball is highly variable, and one poor pitch can change the score immediately.

Still, WHIP helps explain why Los Angeles has allowed fewer runs over the season.

For readers studying dodgers vs san francisco giants match player stats, this is one of the statistics worth checking alongside ERA rather than looking only at win-loss records.

Home and Away Performance

The Dodgers have a 46-32 road record.

The Giants have a 36-39 home record.

This is another important layer of context because the September 26 matchup is being played at Oracle Park.

The Giants’ home record is below .500, while Los Angeles has performed considerably better away from home.

That does not guarantee a particular game result. It simply provides historical context for how each club has performed under the relevant location conditions during the supplied 2026 season.

Oracle Park can also create a different statistical environment from other MLB venues. Park context is one reason ERA and offensive statistics are best interpreted with multiple pieces of evidence rather than one isolated figure.

Night Game Trends

The supplied data also includes each team’s night record.

The Dodgers are 76-41 at night.

The Giants are 40-55.

That is another substantial difference.

Los Angeles has won approximately 64.9% of its listed night games, while San Francisco has won approximately 42.1%.

Although the September 26 game is officially scheduled for the afternoon in San Francisco, these figures remain useful for understanding each team’s overall performance under the supplied game-condition splits.

They should not be treated as a direct prediction of an afternoon game.

Recent Form

Recent results add another layer to the statistical picture.

The Dodgers are 4-1 over their last five games and are currently on a four-game winning streak.

The Giants are 2-3 over their last five games and have lost three straight.

Recent form can help describe the current competitive environment, but it should not replace the larger season sample.

A five-game stretch is far smaller than a 156-game season. That means recent results are useful as context but can be misleading if treated as a complete representation of team strength.

The most useful reading combines recent form with season-long offense and pitching statistics.

In this case, the two sets of numbers point in the same general direction: Los Angeles has the stronger season record and enters with better recent results.

The 6-4 Regular Season Series

The Dodgers lead the 2026 regular season series 6-4 according to the supplied matchup data.

That means San Francisco has already won four games against Los Angeles this season.

This is important because the rivalry has produced results on both sides despite the Dodgers’ much stronger overall record.

Head-to-head results can reveal matchup-specific patterns that a season record does not capture.

However, a 10-game series sample is still relatively small compared with the full season.

For that reason, the 6-4 series advantage is best presented as one piece of the matchup rather than as a standalone explanation of what happens next.

What the Team Statistics Reveal

The most interesting feature of the statistical comparison is that the Dodgers’ advantage is not dependent on one category.

Los Angeles leads San Francisco in:

• Batting average
• Runs
• Hits
• Home runs
• OBP
• SLG
• ERA
• WHIP
• Strikeouts
• Opponent batting average
• Overall record
• Recent five-game record

San Francisco leads in the supplied individual power categories through Devers, who has more home runs and RBIs than the Dodgers’ listed leaders.

The Giants also have more team walks, with 581 compared with 471.

That last point deserves context. More walks can mean an offense is patient and willing to reach base without swinging at everything. But walks can also contribute to longer innings for a pitching staff when the team is on defense.

The meaning depends on whether the statistic is being evaluated for the offense or pitching side.

A Closer Look at Run Creation

The Dodgers have scored 780 runs in 156 games.

That equals exactly 5.00 runs per game.

The Giants have scored 656 runs over the same number of games, which equals approximately 4.21 runs per game.

The difference is approximately 0.79 runs per game.

Across a full season, that is a substantial offensive gap.

The Dodgers’ .339 OBP also indicates that their lineup has been more successful at getting hitters onto base than the Giants’ .308 mark.

Their .426 SLG compared with San Francisco’s .405 further indicates that Los Angeles has produced more total bases per at-bat.

Taken together, these statistics explain the run differential more effectively than batting average alone.

Strikeouts and Pitching Pressure

Los Angeles has recorded 1,450 team strikeouts.

San Francisco has recorded 1,159.

The difference is 291 strikeouts.

That does not automatically mean every Dodgers pitcher has been more effective than every Giants pitcher. Team strikeout totals depend on innings, staff composition, usage patterns, and game situations.

But the gap is large enough to be meaningful when evaluating the overall pitching profiles supplied for the two clubs.

Glasnow’s individual 87 strikeouts in 67.2 innings fit that broader Dodgers pitching profile.

His strikeout total also suggests that San Francisco hitters could face considerable swing-and-miss pressure when he is able to command his pitches.

Injuries and Their Statistical Importance

The supplied injury information lists several players for both teams.

Dodgers Injury List

The Dodgers’ listed injured players are:

• Gavin Stone
• Jake Cousins
• Dalton Rushing
• Andy Pages
• Kyle Tucker

Giants Injury List

The Giants’ listed injured players are:

• JT Brubaker
• Matt Gage
• Jung Hoo Lee
• Bryce Eldridge
• Marcelo Mayer

Injuries matter to statistical analysis because season totals do not necessarily represent the lineup or pitching staff that will appear on a specific day.

This is particularly relevant for Jung Hoo Lee because he is listed as the Giants’ batting average leader in the supplied data but is also listed among the team’s injuries.

The final lineup should therefore be checked close to game time.

Why Lineup Confirmation Matters

Baseball statistics are often presented as if the players listed in a season table are guaranteed to appear in the next game.

They are not.

Managers can change batting orders because of injuries, rest, platoon considerations, defensive needs, or pitching matchups.

That means a player-level preview should distinguish between season statistics and confirmed game availability.

The same principle applies to the Giants’ starting pitcher.

The supplied data identifies the Giants’ probable starter as undecided. Until that pitcher is confirmed, a full pitcher-versus-batter analysis would be premature.

This is one reason a responsible statistical preview should avoid inventing a matchup that has not been confirmed.

What to Watch at the Plate

Several statistical signals deserve attention when the game begins.

First, watch whether the Giants can create baserunners against Glasnow.

His 0.96 WHIP indicates that limiting baserunners has been one of his strengths in the supplied season sample.

Second, watch how the Dodgers respond to San Francisco’s pitching staff.

The Dodgers have a .339 OBP and .426 SLG. If those numbers are reflected in the game, the lineup can create pressure through both baserunners and extra-base hits.

Third, watch the home run situation.

Devers has 37 home runs, while Ohtani has 30. Both represent genuine power threats.

One mistake with runners aboard can quickly change the game.

How to Read the Matchup Beyond Batting Average

Batting average remains useful, but it should not be the only offensive statistic considered.

For example, the Dodgers have a .257 batting average compared with .247 for the Giants.

That is only a 10-point difference.

Yet Los Angeles has scored 124 more runs.

The reason becomes clearer when OBP and SLG are added.

The Dodgers have:

• 31 points of OBP advantage
• 21 points of SLG advantage
• 124 more runs
• 46 more home runs
• 46 more hits

This demonstrates why a multi-stat approach gives a more complete picture.

MLB’s statistical glossary also distinguishes batting average, OBP, SLG, OPS, and other measures rather than treating batting average as a complete offensive evaluation.

Advanced Metrics and the Bigger Picture

Modern baseball analysis increasingly uses advanced statistics alongside traditional numbers.

Metrics such as wOBA can account for the different run values of walks, singles, doubles, triples, and home runs. MLB describes wOBA as an offensive measure that gives different outcomes different weights based on their relationship to run production.

For this matchup, advanced metrics can be useful if the goal is to understand why two hitters with similar batting averages may have very different offensive impacts.

They can also help separate actual results from the context in which those results occurred.

However, the supplied data does not include player-level wOBA, xwOBA, barrel rate, hard-hit rate, exit velocity, or other Statcast measurements for the full expected lineups.

It would therefore be inappropriate to invent those numbers.

The available statistics already provide enough evidence for a meaningful matchup analysis without filling missing information with estimates.

Dodgers vs Giants Matchup: Key Statistical Questions

The most important questions heading into the game are straightforward.

Can San Francisco generate traffic against Glasnow?

Glasnow’s 0.96 WHIP gives the Giants a difficult starting point.

San Francisco needs baserunners to create RBI opportunities for its power hitters.

Can Devers convert opportunities?

Devers has 98 RBIs and 37 home runs in the supplied statistics.

His ability to capitalize on runners aboard is an important part of San Francisco’s offensive profile.

Can the Giants limit Dodgers baserunners?

The Dodgers’ .339 OBP is higher than San Francisco’s .308.

That difference means the Giants need to prevent Los Angeles from repeatedly extending innings.

Which pitching staff controls the middle innings?

The Dodgers’ 3.62 ERA and 1.15 WHIP are both better than San Francisco’s 4.39 ERA and 1.37 WHIP.

The middle innings can expose bullpen depth and determine whether a close game remains close.

Does the Giants’ home setting change the statistical pattern?

The Giants are 36-39 at home.

The Dodgers are 46-32 on the road.

Those figures suggest both teams have experienced different levels of success in the conditions relevant to this matchup.

How Fans Can Use These Stats

For someone researching dodgers vs san francisco giants match player stats, the best method is to organize the information into four categories.

1. Individual production

Look at:

• Batting average
• Home runs
• RBIs
• Hits
• OBP
• SLG

These numbers help identify who is generating offense.

2. Pitching quality

Look at:

• ERA
• WHIP
• Strikeouts
• Walks
• Hits allowed
• Home runs allowed

These figures help explain how pitchers are limiting opposing offenses.

3. Team context

Look at:

• Overall record
• Home and road record
• Runs scored
• Opponent batting average
• Recent form
• Series record

These numbers show how individual performances fit into the broader season.

4. Game-day context

Finally, verify:

• Starting lineups
• Confirmed pitchers
• Injury status
• Game location
• Official start time

This last step is essential because season statistics can become outdated when players are unavailable.

Statistical Summary

The supplied 2026 numbers present a clear statistical contrast.

The Dodgers have the stronger overall record at 96-60, compared with 64-92 for the Giants.

Los Angeles has scored 780 runs to San Francisco’s 656.

The Dodgers have also produced 197 home runs compared with 177.

Their .257 batting average is higher than San Francisco’s .247, while their .339 OBP and .426 SLG are also higher than the Giants’ .308 and .405 marks.

Pitching shows an even larger separation.

The Dodgers have a 3.62 ERA, 1.15 WHIP, and .219 opponent batting average.

The Giants have a 4.39 ERA, 1.37 WHIP, and .249 opponent batting average.

At the individual level, Glasnow provides Los Angeles with a starter who has posted a 3.46 ERA, 0.96 WHIP, and 87 strikeouts across 67.2 innings in the supplied data.

For San Francisco, Devers stands out with 37 home runs and 98 RBIs.

Freeman leads the Dodgers in batting average at .292, while Lee leads the Giants at .276, although Lee’s listed injury status means his availability should be confirmed.

FAQs

What are the Dodgers vs San Francisco Giants match player stats for September 26, 2026?

The Dodgers enter at 96-60, while the Giants are 64-92. Los Angeles has a .257 team batting average, 780 runs, 197 home runs, 3.62 ERA, and 1.15 WHIP. San Francisco has a .247 average, 656 runs, 177 home runs, 4.39 ERA, and 1.37 WHIP.

Who is the Dodgers’ probable pitcher?

Tyler Glasnow is listed as the Dodgers’ probable starter. The supplied statistics show him at 5-1 with a 3.46 ERA, 0.96 WHIP, 67.2 innings, 87 strikeouts, 23 walks, and seven home runs allowed.

Who leads the Giants in home runs?

Rafael Devers leads the Giants in the supplied 2026 statistics with 37 home runs. He also leads the team with 98 RBIs.

Who leads the Dodgers in home runs and RBIs?

Shohei Ohtani leads the Dodgers in the supplied data in both categories, with 30 home runs and 80 RBIs.

What is the 2026 Dodgers vs Giants series record?

The Dodgers lead the regular season series 6-4 according to the supplied matchup data.

Where is the Dodgers vs Giants game being played?

The game is scheduled for Oracle Park in San Francisco, California. The official MLB schedule lists the September 26 game for 1:05 PM PDT.

Conclusion

The dodgers vs san francisco giants match player stats show a matchup between two teams with significantly different season profiles.

Los Angeles has the stronger overall record, higher run production, better team batting average, higher OBP, higher SLG, more home runs, lower ERA, lower WHIP, more strikeouts, and lower opponent batting average.

San Francisco still has individual offensive threats capable of changing a game. Rafael Devers’ 37 home runs and 98 RBIs give the Giants a proven run-producing presence, while Jung Hoo Lee’s .276 batting average represents the team’s leading mark in the supplied data, subject to his listed injury status.

For Los Angeles, Shohei Ohtani’s 30 home runs and 80 RBIs, Freddie Freeman’s .292 batting average, and Tyler Glasnow’s 3.46 ERA and 0.96 WHIP form the most prominent statistical pieces of the matchup.

The most useful way to understand this game is therefore not to rely on a single number. Batting average explains contact, OBP explains how often hitters reach base, SLG provides context about power, ERA measures earned runs allowed, and WHIP helps show how frequently pitchers allow hits and walks.

Taken together, those figures provide a much clearer picture of how the Dodgers and Giants have performed throughout the 2026 season and what statistical factors deserve attention when the teams meet at Oracle Park.