Red Sox vs San Francisco Giants Match Player Stats
The red sox vs san francisco giants match player stats provide a useful way to understand the August 22, 2026 MLB matchup at Fenway Park beyond the basic win-loss record. The supplied ESPN data shows two teams with identical .249 batting averages, but very different offensive and pitching profiles. Boston enters the matchup at 67-58 with a 3.50 team ERA, while San Francisco sits at 51-73 with a 4.36 ERA. The Giants are expected to send Logan Webb to the mound, while Boston is projected to start Jake Bennett.
This matchup is particularly interesting because the overall batting averages are the same, yet Boston has scored 560 runs compared with San Francisco’s 509. The Red Sox also have a major advantage in team WHIP, 1.22 compared with 1.35, and team on-base percentage, .321 compared with .307. San Francisco, however, has hit more home runs, 137 to Boston’s 126.
The numbers suggest that this is not simply a matchup between a stronger and weaker offense. It is a contrast between different ways of producing runs, preventing runs, and controlling innings.
Red Sox vs San Francisco Giants Match Player Stats: Match Overview
The first game of the series is scheduled for August 22, 2026, at Fenway Park in Boston. The supplied information lists a 4:10 AM game time and MLB.TV coverage.
Here are the key matchup details:
| Category | San Francisco Giants | Boston Red Sox |
| Overall Record | 51-73 | 67-58 |
| Home/Away Record | 22-40 away | 30-31 home |
| Team Batting Average | .249 | .249 |
| Runs | 509 | 560 |
| Hits | 1,048 | 1,042 |
| Home Runs | 137 | 126 |
| OBP | .307 | .321 |
| SLG | .407 | .403 |
| ERA | 4.36 | 3.50 |
| WHIP | 1.35 | 1.22 |
| Walks | 467 | 349 |
| Strikeouts | 937 | 1,067 |
| Opponent Average | .246 | .239 |
| Night Record | 30-45 | 44-31 |
The matchup predictor gives Boston a 54.5% chance compared with 45.5% for San Francisco. That is not an overwhelming difference. It suggests that while Boston has the statistical edge, the game remains competitive on paper.
One of the most important observations is the difference between batting average and run production. Both clubs are hitting .249, but Boston has produced 51 more runs. That gap indicates that batting average alone does not explain offensive performance.
How the Giants and Red Sox Compare Offensively
At first glance, the two teams appear almost identical because both have a .249 batting average.
Looking deeper reveals a more complicated picture.
San Francisco has collected 1,048 hits, six more than Boston’s 1,042. The Giants have also hit 137 home runs, 11 more than the Red Sox. Yet Boston has scored 560 runs, 51 more than San Francisco.
That difference is one of the most valuable statistics in this matchup.
San Francisco Giants Offensive Profile
The Giants’ offensive leaders in the supplied data are:
- Willson Contreras: 25 home runs
- Willson Contreras: 73 RBI
- Jung Hoo Lee: .292 batting average
- Team batting average: .249
- Team runs: 509
- Team home runs: 137
- Team OBP: .307
- Team SLG: .407
Contreras is especially important because his 25 home runs lead the club, while his 73 RBI also lead the Giants.
Jung Hoo Lee provides a different type of offensive value. His .292 batting average is substantially higher than the team average of .249. That makes him one of the most important contact-oriented hitters to watch when evaluating San Francisco’s lineup.
The Giants’ .407 slugging percentage is also higher than Boston’s .403. That supports the idea that San Francisco can create damage through extra-base hits and home runs even though Boston has produced more total runs.
Boston Red Sox Offensive Profile
Boston’s supplied offensive leaders include:
- Rafael Devers: 25 home runs
- Rafael Devers: 69 RBI
- Ceddanne Rafaela: .288 batting average
- Team batting average: .249
- Team runs: 560
- Team home runs: 126
- Team OBP: .321
- Team SLG: .403
Rafael Devers matches San Francisco’s Contreras with 25 home runs. His 69 RBI are also among the most important run-producing numbers on the Boston side.
Ceddanne Rafaela leads the listed Boston players in batting average at .288.
The biggest difference between the offenses is on-base percentage. Boston’s .321 OBP is 14 points higher than San Francisco’s .307. Over a full game, reaching base more often creates additional opportunities for the middle of the order to drive runners home.
Why the Identical .249 Batting Average Matters
A common mistake when analyzing baseball is treating batting average as a complete measure of offensive strength.
It is not.
Both teams have a .249 batting average, yet Boston has scored 560 runs and San Francisco has scored 509. This is a clear example of why run production must be examined alongside batting average.
Boston’s .321 OBP indicates that its hitters are reaching base more frequently. The Red Sox have also drawn 349 walks. San Francisco has drawn 467 walks, which is actually 118 more than Boston.
That creates an interesting statistical contradiction.
Despite San Francisco drawing substantially more walks, Boston has the higher OBP. This means the Red Sox’s overall ability to reach base is being supported strongly by their hitting results and other offensive contributions.
San Francisco, meanwhile, has a higher slugging percentage and more home runs.
The result is two different offensive profiles:
San Francisco: More home-run power, more walks, slightly higher slugging percentage.
Boston: More runs, higher OBP, and a much better overall team record.
That distinction could become important in a close game.
Logan Webb vs Jake Bennett
Starting pitching is one of the clearest statistical storylines in this matchup.
The supplied data lists Logan Webb as the Giants’ probable starter and Jake Bennett as Boston’s projected starter.
Logan Webb’s Numbers
Webb enters the matchup with:
| Statistic | Logan Webb |
| Record | 8-7 |
| ERA | 3.50 |
| WHIP | 1.06 |
| Innings | 139.0 |
| Hits Allowed | 116 |
| Strikeouts | 110 |
| Walks | 32 |
| Home Runs Allowed | 9 |
The strongest number here may be the 1.06 WHIP.
WHIP measures walks and hits allowed per inning, so a figure around 1.06 indicates that Webb has generally limited baserunners effectively according to the supplied season data.
His 3.50 ERA also matches Boston’s team ERA of 3.50.
Webb has thrown 139 innings, giving him a significantly larger workload than Bennett’s 80.2 innings. That workload matters when considering experience and the ability to work deep into games.
His 110 strikeouts against 32 walks also show a favorable balance between missing bats and limiting free passes.
Jake Bennett’s Numbers
Bennett’s supplied numbers are:
| Statistic | Jake Bennett |
| Record | 7-6 |
| ERA | 3.46 |
| WHIP | 1.07 |
| Innings | 80.2 |
| Hits Allowed | 69 |
| Strikeouts | 61 |
| Walks | 17 |
| Home Runs Allowed | 6 |
His 3.46 ERA is slightly better than Webb’s 3.50.
His WHIP of 1.07 is also only one hundredth higher than Webb’s 1.06.
Bennett has allowed six home runs in 80.2 innings, while Webb has allowed nine in 139 innings. Neither figure should be evaluated in isolation, but both pitchers have limited home-run damage reasonably well within the supplied numbers.
The most notable difference is workload.
Webb has already thrown 139 innings, compared with 80.2 for Bennett. That does not automatically make Webb the better pitcher in this particular game, but it does provide useful context when comparing the two statistical profiles.
What the Starting Pitching Suggests
The pitching matchup is closer than the teams’ records might suggest.
Boston’s team ERA is 3.50, while San Francisco’s is 4.36. That is a meaningful 0.86-run difference in ERA.
Boston also has a 1.22 team WHIP compared with 1.35 for the Giants.
The Red Sox have also limited opposing hitters to a .239 average, while San Francisco’s opponents are hitting .246.
These numbers point toward Boston having the stronger overall pitching staff based on the supplied statistics.
However, Webb’s individual numbers are considerably better than the Giants’ overall team ERA. His 3.50 ERA is exactly the same as Boston’s team ERA.
That is why evaluating the starting pitchers separately from their clubs is important.
The game may begin with a pitching matchup that is much more balanced than the overall team records imply.
Red Sox Pitching Advantage
Boston’s pitching statistics deserve particular attention.
The Red Sox have:
- 3.50 team ERA
- 1.22 WHIP
- .239 opponent batting average
- 1,067 strikeouts
- 349 walks
The combination of a low opponent batting average and low WHIP suggests that Boston has generally done a good job of preventing opposing hitters from reaching base.
The strikeout total is also higher than San Francisco’s, despite the Red Sox having played fewer games based on the supplied records.
That gives Boston another potential advantage in situations where putting the ball in play becomes risky.
Giants Pitching Profile
San Francisco’s pitching numbers are:
- 4.36 ERA
- 1.35 WHIP
- .246 opponent batting average
- 937 strikeouts
- 467 walks
The 467 walks stand out.
Free passes can create innings where a pitcher is forced to work from the stretch and eventually face additional run-scoring pressure. The Giants’ higher WHIP also suggests more baserunners are being allowed overall.
The challenge for San Francisco is that its starting pitcher, Webb, has much stronger individual numbers than the team pitching line.
If Webb is able to provide a deep outing, the Giants can potentially keep Boston’s offense from exploiting the broader weaknesses shown in the team statistics.
Home and Away Context
Location matters in this series because the Giants are traveling to Fenway Park.
San Francisco’s away record is 22-40, while Boston’s home record is 30-31.
Neither record should be interpreted as a guarantee of what happens in this game.
However, the difference does provide context.
The Giants have struggled significantly on the road according to the supplied record. Boston’s home record is much closer to even, so Fenway has not been an automatic advantage for the Red Sox either.
That makes the matchup more nuanced than simply saying Boston is at home and therefore favored.
The supplied matchup predictor gives Boston a 54.5% probability, which fits the broader statistical picture. Boston has the better record, stronger team pitching numbers, higher run total, and home-field advantage. San Francisco still has enough power and a strong enough starting pitcher to make the contest competitive.
Recent Form Before the Matchup
Recent results provide another layer of context.
Giants Last Five Games
San Francisco is listed at 2-3 over its last five games:
- Loss, 13-7 vs Colorado
- Win, 7-1 vs Colorado
- Loss, 5-2 vs Colorado
- Loss, 2-1 vs Houston
- Win, 4-1 vs Houston
The Giants have therefore experienced both offensive highs and lows during this stretch.
The 13-7 loss demonstrates that their offense can score in volume, but the 2-1 and 5-2 defeats show how difficult it can be when the lineup is unable to generate enough runs.
Red Sox Last Five Games
Boston is listed at 3-2 over its last five:
- Win, 11-1 vs Arizona
- Loss, 8-3 at Pittsburgh
- Win, 4-0 at Pittsburgh
- Loss, 8-4 at Pittsburgh
- Win, 7-0 at Toronto
Boston’s recent run differential also contains some impressive performances.
The 11-1 win over Arizona and 7-0 win over Toronto show that the Red Sox can dominate when both their pitching and offense are functioning well.
Their recent form is not perfect, though. The three-game Pittsburgh portion included two losses.
That matters because it prevents the recent record from being interpreted too simplistically.
Key Players to Watch
Willson Contreras
Contreras is the Giants’ listed home-run and RBI leader.
His 25 home runs and 73 RBI make him the most obvious run-producing threat in the supplied San Francisco data.
Against a Boston pitching staff with a 3.50 ERA, his ability to create extra-base damage could be important.
Jung Hoo Lee
Lee’s .292 batting average leads the listed Giants hitters.
His value is different from Contreras’ power profile. A high batting average can help create baserunners ahead of the middle of the order.
If Lee reaches base consistently, the Giants can create situations where their power hitters have runners available to drive in.
Rafael Devers
Devers has 25 home runs and 69 RBI.
His home-run total matches Contreras, making the power matchup particularly easy to identify.
Boston’s higher run total also means Devers’ production exists within a lineup that has produced more total runs than San Francisco.
Ceddanne Rafaela
Rafaela’s listed .288 batting average makes him another important Boston hitter to monitor.
He is only four points behind Lee’s .292 mark in the supplied player data.
That suggests Boston also has a high-average hitter capable of contributing to the lineup without relying solely on home-run production.
The Most Important Statistical Battle
The most important battle may not be home runs.
It may be baserunners.
Boston has a .321 OBP and San Francisco has a .307 OBP.
That 14-point difference is meaningful because every additional baserunner can change the value of a single, double, sacrifice fly, or home run.
At the same time, San Francisco has 137 home runs compared with Boston’s 126.
This creates an interesting strategic contrast.
If the Giants are able to use their power efficiently, they can score quickly. If Boston consistently creates traffic on the bases, it may generate runs through a wider variety of offensive events.
The starting pitchers can influence which approach wins.
Webb’s 1.06 WHIP suggests that Boston could have difficulty generating large numbers of baserunners against him.
Bennett’s 1.07 WHIP suggests the same challenge for San Francisco.
That is one reason the opening innings could be especially important.
What the Team Statistics Say About Run Prevention
The Red Sox have a clear advantage in the supplied run-prevention numbers.
Boston’s 3.50 ERA is significantly lower than San Francisco’s 4.36.
Its 1.22 WHIP is also lower than the Giants’ 1.35.
Most importantly, Boston’s opponents are hitting .239 compared with .246 against San Francisco.
The differences are not enormous in batting average, but the cumulative effect is visible in the overall run totals.
Boston has scored 560 runs while allowing a pitching profile that has generally been more efficient.
San Francisco has scored 509 runs while carrying a higher team ERA.
This combination helps explain the 16-game difference between the clubs’ win totals.
Why the Giants Can Still Win
The statistics do not make San Francisco irrelevant.
There are several reasons the Giants remain dangerous.
First, they have more home runs.
Second, Contreras leads the team with both 25 home runs and 73 RBI.
Third, Webb’s individual pitching statistics are strong.
Fourth, San Francisco has drawn 467 walks, which is substantially more than Boston’s 349.
That ability to draw walks can become valuable if the Giants force Boston’s pitchers into extended counts.
The Giants also have a .407 slugging percentage, slightly above Boston’s .403.
So although Boston has the better overall statistical profile, San Francisco has enough power and plate-discipline indicators to produce a different type of offensive threat.
Why the Red Sox Have the Statistical Edge
Boston’s advantage comes from balance.
The Red Sox do not lead the Giants in every offensive category. In fact, San Francisco has more hits, home runs, walks, and a slightly higher slugging percentage.
Boston’s advantage is that its numbers combine more effectively.
The Red Sox have:
- A 67-58 record
- 560 runs
- .321 OBP
- 3.50 team ERA
- 1.22 WHIP
- .239 opponent batting average
- 1,067 strikeouts
- A 44-31 night record
That combination points to a club that has been more effective at both scoring and preventing runs.
The 54.5% matchup projection for Boston is therefore consistent with the broader data.
Injury Context
The supplied information lists several injuries on both sides.
Giants Injuries
The Giants’ injury list includes:
- Willy Adames, day-to-day
- Marcelo Mayer, 10-day injured list
- Logan Webb, day-to-day
- Jesus Rodriguez, 10-day injured list
- Joel Peguero, 60-day injured list
Webb’s day-to-day designation is particularly important because he is also listed as the probable starter.
That means his status should be verified close to game time before treating the projected pitching matchup as confirmed.
Red Sox Injuries
Boston’s listed injuries include:
- Jahmai Jones, day-to-day
- Isiah Kiner-Falefa, 60-day injured list
- Trevor Story, 60-day injured list
- Roman Anthony, 60-day injured list
- Garrett Whitlock, 15-day injured list
These absences can affect lineup depth and pitching options.
Because injury statuses can change, the supplied list should be treated as a pregame snapshot rather than a permanent statement about player availability.
Night-Game Records
The supplied data lists:
- Giants night record: 30-45
- Red Sox night record: 44-31
The difference is substantial.
Boston has won 44 of its 75 listed night games, while San Francisco has won 30 of 75.
Because this game is listed with an early-morning time in the supplied information, the exact local interpretation of the game time should be checked before using the night-record statistic as a direct prediction.
Still, the records provide another indication that Boston has performed better under the relevant conditions represented in the supplied data.
Understanding the Matchup Through Advanced Team Indicators
For readers who want more than batting average and ERA, several secondary numbers stand out.
Boston’s OBP is .321 compared with San Francisco’s .307.
Boston’s SLG is .403 compared with San Francisco’s .407.
This means the Giants have a slight advantage in total bases per at-bat, while Boston has a stronger ability to get on base overall.
The teams’ opponent batting averages are also close:
- Giants: .246
- Red Sox: .239
The seven-point difference favors Boston.
The pitching WHIP gap is larger:
- Giants: 1.35
- Red Sox: 1.22
That 0.13 difference indicates a more noticeable separation in baserunner prevention.
Taken together, the statistics suggest that Boston’s advantage is built more around preventing traffic and converting offensive opportunities, while San Francisco’s strength is more visible in power and walks.
A Practical Way to Read the Box Score
When the game is played, readers looking up the red sox vs san francisco giants match player stats should not focus on only one column.
A useful approach is to check the box score in this order:
1. Starting Pitching
Look at innings, hits, walks, strikeouts, and earned runs.
This shows whether Webb and Bennett performed close to their season profiles.
2. Extra-Base Hits
Check doubles, triples, and home runs.
San Francisco’s season-long home-run advantage makes this especially relevant.
3. Runners in Scoring Position
A team can collect plenty of hits without producing many runs if it fails to capitalize with runners in scoring position.
4. Walks
Walks matter because they create baserunners without requiring a hit.
This is particularly relevant for San Francisco, which has drawn 467 walks according to the supplied team data.
5. Bullpen Performance
Even a strong starting pitching performance can be overturned late.
Boston’s lower team ERA makes its overall pitching staff worth watching beyond the starter.
What a Strong Giants Performance Would Look Like
A statistically convincing Giants performance would probably involve several things happening together.
Webb would need to limit Boston’s ability to get runners on base.
The Giants’ lineup would need to turn its home-run power into actual runs.
Lee’s contact ability could help create opportunities for Contreras and other power hitters.
San Francisco would also benefit from avoiding excessive free baserunners on defense.
If the Giants combine Webb’s 1.06 WHIP profile with their .407 slugging percentage, the matchup could become much closer than the overall records suggest.
What a Strong Red Sox Performance Would Look Like
Boston’s ideal game would revolve around its existing strengths.
Bennett would need to keep San Francisco’s power hitters from producing early damage.
The Boston lineup would need to maintain its .321 OBP profile and force Webb into difficult situations.
Devers would be an obvious power threat, while Rafaela’s .288 batting average represents another important contact element.
If Boston creates enough baserunners and prevents the Giants from turning their 137 home runs into immediate scoring opportunities, the Red Sox’s broader statistical advantage should become more visible.
Projecting the Shape of the Game
Based strictly on the supplied data, the game looks relatively balanced at the starting-pitcher level but favors Boston when the entire roster is considered.
Webb’s 3.50 ERA and 1.06 WHIP make him a serious challenge for the Red Sox.
Bennett’s 3.46 ERA and 1.07 WHIP give Boston a similarly credible starting option.
The larger difference comes from the teams behind those starters.
Boston has the better record, lower team ERA, lower WHIP, lower opponent batting average, higher OBP, and more total runs.
San Francisco has more home runs, more walks, and a slightly higher slugging percentage.
That makes the matchup especially dependent on whether power or overall run creation becomes the dominant factor.
What the Records Tell Us
The Giants’ 51-73 record puts them fourth in the supplied National League West standings.
The Dodgers are listed first at 75-51.
Boston’s 67-58 record puts the Red Sox third in the American League East, behind the Tampa Bay Rays at 75-49.
These standings provide important context.
Neither club enters this matchup as the leader of its division.
However, Boston has a substantially stronger winning percentage than San Francisco.
Boston’s .536 mark compares with San Francisco’s .411.
That difference is consistent with the pitching and run-production statistics.
Important Limitations of the Data
The statistics supplied for this analysis represent a pregame snapshot.
That distinction matters.
The game is scheduled for August 22, 2026, while the current date is August 18, 2026. Therefore, the numbers should be treated as the information available for the upcoming matchup rather than a final game box score.
The probable starters can also change.
The injury report can change.
Lineups can change.
Weather conditions can change.
For that reason, readers should distinguish between projected matchup information and confirmed game-day results.
This is particularly important with Webb because he is simultaneously listed as the probable starter and day-to-day.
Frequently Asked Questions
What are the key Red Sox vs San Francisco Giants match player stats?
The most important supplied statistics include Boston’s 67-58 record, .249 batting average, 560 runs, 3.50 ERA, and 1.22 WHIP. San Francisco is listed at 51-73 with a .249 batting average, 509 runs, 4.36 ERA, and 1.35 WHIP.
Who are the leading home-run hitters in this matchup?
Willson Contreras leads the Giants with 25 home runs, while Rafael Devers leads Boston with 25 home runs. Their identical home-run totals make power one of the clearest statistical similarities between the teams.
Who are the probable starting pitchers?
The supplied data lists Logan Webb as the Giants’ probable starter and Jake Bennett as Boston’s probable starter. Webb has a 3.50 ERA and 1.06 WHIP, while Bennett has a 3.46 ERA and 1.07 WHIP.
Which team has the better pitching statistics?
Boston has the stronger overall team pitching profile in the supplied data. The Red Sox have a 3.50 ERA and 1.22 WHIP compared with San Francisco’s 4.36 ERA and 1.35 WHIP.
Which team has the better offensive statistics?
It depends on the metric. Boston has scored more runs and has a higher OBP, while San Francisco has more home runs and a slightly higher slugging percentage. Both teams have a .249 batting average.
When is the Giants vs Red Sox game scheduled?
The supplied information lists the first game of the series for August 22, 2026, at Fenway Park. The series is scheduled to continue with games on August 23 and August 24.
Conclusion
The red sox vs san francisco giants match player stats point to a matchup in which Boston has the stronger overall statistical profile, but San Francisco has several clear strengths that could keep the game competitive.
Boston enters with a 67-58 record compared with San Francisco’s 51-73 mark. The Red Sox have scored 560 runs, maintain a .321 OBP, and own a 3.50 team ERA with a 1.22 WHIP. Their .239 opponent batting average is also better than San Francisco’s .246 mark.
The Giants counter with 137 home runs, 467 walks, a .407 slugging percentage, and a powerful offensive leader in Willson Contreras. Jung Hoo Lee’s .292 batting average adds another important dimension to the lineup.
The starting pitching matchup is particularly close. Logan Webb has a 3.50 ERA and 1.06 WHIP over 139 innings, while Jake Bennett has a 3.46 ERA and 1.07 WHIP across 80.2 innings. Those numbers suggest that the game could begin with two capable starters rather than a clear pitching mismatch.
The biggest statistical question is whether San Francisco’s power can overcome Boston’s advantages in overall run production and run prevention. The Giants have hit more home runs, but Boston has scored more runs. San Francisco has drawn more walks, but Boston has the higher OBP. Those differences make this matchup more interesting than the records alone suggest.
Based on the supplied pregame data, Boston holds the statistical edge, which is also reflected in the 54.5% matchup projection compared with 45.5% for San Francisco. Still, the gap is not large enough to treat the game as predetermined.
The most useful way to evaluate the matchup is to combine starting-pitcher performance, baserunner creation, power hitting, defensive run prevention, and bullpen results rather than relying on one headline statistic.
