The green bay packers vs minnesota vikings match player stats provide a detailed look at how Minnesota secured a 39-22 victory over Green Bay on September 14, 2026. The game featured a productive passing performance from Jordan Love, two receiving touchdowns from Christian Watson, an efficient scoring display from Justin Jefferson, and a decisive fourth-quarter surge by the Vikings. Minnesota scored 22 points in the final quarter, turning a competitive contest into a 17-point win.

The final score tells only part of the story. Green Bay produced substantial passing yardage and connected on several explosive plays, but Minnesota finished more effectively in the red zone and applied consistent pressure on the quarterback. The Vikings also established a stronger rushing presence, giving their offense another way to sustain drives and control important moments.

This breakdown examines the supplied box-score figures, including passing, rushing, receiving, defensive production, turnovers, special teams, and the most important statistical differences between the two teams. Some figures in the supplied data do not reconcile across individual and team totals, so those discrepancies are identified rather than silently corrected.

Green Bay Packers vs Minnesota Vikings Match Player Stats: Final Score and Quarter-by-Quarter Results

The Minnesota Vikings defeated the Green Bay Packers 39-22 on September 14, 2026, according to the supplied ESPN game data. Minnesota’s biggest advantage came in the fourth quarter, when the team scored 22 unanswered points according to the listed scoring breakdown.

Final Score

Team	Q1	Q2	Q3	Q4	Final
Green Bay Packers	9	10	3	0	22
Minnesota Vikings	3	7	7	22	39

Green Bay entered halftime with a 19-10 lead. The Packers added three more points in the third quarter, while Minnesota scored a touchdown to reduce the deficit to 22-17.

The final quarter completely changed the result. Green Bay failed to add to its score, while Minnesota recorded 22 points to finish the game with a comfortable margin.

What the Scoring Pattern Reveals

Three observations stand out from the quarter-by-quarter results.

• Green Bay started more effectively. The Packers scored 19 points in the first half and held a nine-point halftime advantage.
• Minnesota remained within reach. The Vikings scored in both the second and third quarters, keeping the deficit manageable before the final period.
• The fourth quarter decided the contest. Minnesota’s 22-point finish was the defining statistical development of the game.

A team can lead in passing yardage and still lose when it struggles to finish possessions. Green Bay’s inability to score in the fourth quarter, combined with Minnesota’s late scoring burst, was central to the final outcome.

Jordan Love Player Stats: Passing Performance for Green Bay

Jordan Love was Green Bay’s leading passer in the supplied statistics. His 387 passing yards and two touchdown passes demonstrated the offense’s ability to create significant gains through the air. However, his completion percentage, interception, and reported fumbles provide a more complete picture of the performance.

Statistic	Jordan Love
Completions	21
Pass attempts	42
Completion percentage	50.0%
Passing yards	387
Yards per attempt	9.2
Passing touchdowns	2
Interceptions	1
Sacks taken	4
Sack yards lost	34
Passer rating	88.1
QBR	68.8

Love completed half of his 42 attempts. That completion rate was modest, but his reported 9.2 yards per attempt points to an offense seeking substantial gains rather than relying exclusively on short passes.

The difference between completion percentage and yards per attempt is important. A quarterback can complete a relatively low share of passes while generating strong yardage if several successful throws travel far downfield. The challenge is maintaining that explosive production without giving away possessions or allowing negative plays to end drives.

Passing Efficiency Versus Passing Volume

Love’s 387 passing yards were a major individual achievement within the supplied figures. Nevertheless, total yardage alone does not measure offensive efficiency.

Consider three parts of his statistical line:

1. Passing production: Two touchdowns and 387 reported yards show that Green Bay generated meaningful offensive output.
2. Accuracy: A 50.0% completion rate indicates that many attempts did not produce completed passes.
3. Negative plays: Four sacks for 34 yards and one interception created opportunities for Minnesota’s defense to disrupt drives.

The Packers’ offense needed to turn its explosive passing ability into more consistent scoring. Long completions can move a team quickly, but unsuccessful attempts, sacks, and turnovers can erase the value of those gains.

What the Interception and Sacks Mean

Love’s interception was one of the most important entries in the turnover statistics. An interception ends an offensive possession and gives the opposing team an opportunity to take control of field position.

The four recorded sacks also matter. Sacks can push an offense out of field-goal range, create difficult third-down situations, and increase the pressure on the quarterback to attempt longer passes on later downs.

The Vikings recorded four sacks in their defensive team statistics, matching Love’s reported total of four sacks taken. Minnesota also recorded 15 quarterback hits, compared with six listed for Green Bay’s defense. These numbers suggest a substantial difference in the pressure each defense generated, although quarterback hits are not equivalent to sacks and do not establish exactly when each play occurred.

Love’s performance therefore combined explosive passing production with problems that made it harder for Green Bay to sustain control.

Carson Wentz Player Stats: Minnesota’s Passing Leader

Carson Wentz led Minnesota’s passing production in the supplied player statistics. His line shows fewer passing yards than Love’s, but he recorded three passing touchdowns without an interception.

Statistic	Carson Wentz
Completions	12
Pass attempts	19
Completion percentage	63.2%
Passing yards	133
Yards per attempt	7.0
Passing touchdowns	3
Interceptions	0
Sacks taken	3
Sack yards lost	19
Passer rating	123.5
QBR	70.0

Wentz completed 63.2% of his attempts and threw three touchdown passes. His reported passer rating of 123.5 reflects the combination of touchdown production, completion rate, and the absence of an interception in the listed passing line.

The most revealing difference between Wentz and Love is the relationship between passing yardage and scoring. Love’s supplied line contains 387 yards and two touchdown passes, while Wentz’s contains 133 yards and three touchdown passes.

That contrast illustrates why passing yardage should never be used as the sole measure of quarterback performance. A quarterback can accumulate substantial yardage between the 20-yard lines, while another can finish possessions more successfully.

Why Wentz’s Touchdown Production Matters

Three touchdown passes on 19 attempts represent a touchdown on approximately 15.8% of his passing attempts. Love’s two touchdowns on 42 attempts represent approximately 4.8%.

These calculations use the individual passing figures supplied for each quarterback. They should not be interpreted as proof that Wentz was better in every aspect of quarterback play. The sample is one game, and the supplied data contains inconsistencies elsewhere in the box score.

Still, the touchdown figures offer a useful explanation for Minnesota’s scoring advantage. Wentz produced more passing touchdowns despite recording far fewer passing yards.

Kyler Murray’s Listed Contribution

The supplied data also lists Kyler Murray as a Minnesota quarterback.

Statistic	Kyler Murray
Completions	3
Pass attempts	5
Completion percentage	60.0%
Passing yards	18
Yards per attempt	3.6
Passing touchdowns	0
Interceptions	1
Sacks taken	0
Passer rating	27.5
QBR	2.3

Murray’s listed line includes one interception on five attempts. Because the supplied material does not establish the circumstances of his appearance, the figures should be treated as reported statistics rather than used to infer the precise offensive plan or reason for his involvement.

The team passing totals and individual quarterback figures also do not reconcile perfectly. The passing statistics should therefore be checked against the official game record before being republished as independently verified totals.

Rushing Stats: Jordan Mason Leads Minnesota’s Ground Game

Minnesota recorded 107 team rushing yards on 34 attempts, while Green Bay recorded 66 yards on 21 attempts in the supplied data. Both teams averaged 3.1 yards per carry, but the Vikings had a clear advantage in rushing volume and rushing touchdowns.

Minnesota Vikings Rushing Statistics

Player	Carries	Yards	Average	TDs	Longest
Jordan Mason	15	59	3.9	1	28
Aaron Jones Sr.	12	40	3.3	1	8
Kyler Murray	2	9	4.5	0	7
Carson Wentz	5	-1	-0.2	0	1
Team total	34	107	3.1	2	28

Jordan Mason led Minnesota with 59 rushing yards on 15 carries. He averaged 3.9 yards per attempt and recorded the longest listed run of the game for the Vikings, a gain of 28 yards.

Aaron Jones Sr. added 40 yards and a rushing touchdown on 12 attempts. His contribution gave Minnesota another runner capable of handling a meaningful share of the workload.

Together, Mason and Jones accounted for 99 rushing yards and both of the Vikings’ listed rushing touchdowns. That combination helped Minnesota maintain a balanced offensive profile.

Jordan Mason’s Statistical Impact

Mason’s 28-yard run was significant because one explosive rushing play can change the structure of a drive. A long run can move the offense closer to the end zone, reduce the number of first downs needed, and force the defense to respond to the possibility of further runs.

His 59 yards were not an overwhelming individual total, but his touchdown and longest run gave him a meaningful role in the team’s ground production.

The value of a running back also depends on context that a basic box score cannot fully show. Blocking quality, yards after contact, missed tackles forced, and performance on short-yardage plays would provide additional insight if verified play-by-play or advanced statistics were available.

Green Bay Packers Rushing Statistics

Player	Carries	Yards	Average	TDs	Longest
MarShawn Lloyd	13	37	2.8	0	12
Chris Brooks	7	29	4.1	0	14
Jordan Love	1	0	0.0	0	0
Team total	21	66	3.1	0	14

MarShawn Lloyd led Green Bay with 37 rushing yards on 13 attempts. Chris Brooks averaged 4.1 yards per carry and contributed 29 yards on seven attempts.

Brooks was more productive on a per-carry basis, while Lloyd received the larger workload. Neither player recorded a rushing touchdown in the supplied statistics.

The key distinction between the teams was not their rounded yards-per-carry average. Both were listed at 3.1. Minnesota generated more total rushing yards, recorded two rushing touchdowns, and had a longer run.

Why the Rushing Difference Matters

The Vikings’ 34 rushing attempts compared with Green Bay’s 21 created a difference in how each offense could approach the game.

A productive running game can help an offense:

• Keep the defense honest against play-action passes.
• Create manageable down-and-distance situations.
• Reduce dependence on repeated high-risk passing attempts.
• Finish drives with short-yardage touchdowns.
• Maintain possession when the passing game is less productive.

Minnesota’s rushing touchdowns complemented its three listed passing touchdowns. Green Bay, by contrast, had to depend more heavily on passing production and field goals to build its score.

This does not mean rushing volume alone decided the game. The fourth-quarter scoring split, defensive pressure, and turnover opportunities were also important parts of the statistical picture.

Receiving Stats: Christian Watson and Justin Jefferson Lead Their Teams

The receiving numbers feature two standout performances. Christian Watson led Green Bay with 147 receiving yards and two touchdowns, while Justin Jefferson led Minnesota with 92 yards and two touchdowns.

Watson’s greater yardage total points to a more explosive receiving performance. Jefferson’s production, meanwhile, formed a central part of Minnesota’s touchdown scoring.

Green Bay Packers Receiving Statistics

Player	Receptions	Targets	Yards	Average	TDs	Longest
Christian Watson	6	8	147	24.5	2	81
Matthew Golden	6	12	95	15.8	0	42
Tucker Kraft	3	6	65	21.7	0	30
Jonnu Smith	2	3	50	25.0	0	43
Jayden Reed	3	7	20	6.7	0	7
Bo Melton	1	1	10	10.0	0	10

Christian Watson’s six catches for 147 yards worked out to 24.5 yards per reception. That is an explosive average, particularly when combined with two receiving touchdowns and a longest catch of 81 yards.

Matthew Golden also caught six passes, finishing with 95 yards. His 12 targets were the highest listed total among the Packers’ receivers in the supplied figures.

Tucker Kraft added 65 yards on three receptions, while Jonnu Smith averaged 25.0 yards per catch on two receptions. Their figures suggest that Green Bay’s listed passing production was spread across several players rather than concentrated entirely in one receiver.

Christian Watson’s Explosive Production

Watson’s 147 yards represented a substantial contribution to Green Bay’s passing attack. His longest reception of 81 yards accounted for a large portion of his total yardage, illustrating how a single explosive play can shape an individual box-score line.

His two touchdowns were equally important. Receiving yardage measures the distance gained through catches, while touchdowns measure how often those plays finish in the end zone. Watson delivered in both categories.

His eight targets and six receptions also produce a 75% catch rate. That is a useful descriptive measure of his listed opportunities, although it does not account for pass difficulty, defensive coverage, or the exact location of each target.

The contrast between Watson and Golden is instructive. Both caught six passes, but Watson gained 52 more yards and scored twice. Golden received four additional targets but did not record a touchdown in the supplied figures.

This shows why receptions alone are not enough to evaluate receiving performance. Yardage, target volume, explosive gains, and touchdowns all contribute different information.

Minnesota Vikings Receiving Statistics

Player	Receptions	Targets	Yards	Average	TDs	Longest
Justin Jefferson	8	9	92	11.5	2	39
T.J. Hockenson	4	5	36	9.0	1	16
Josh Oliver	2	4	22	11.0	0	13
DeeJay Dallas	1	1	1	1.0	0	1

Justin Jefferson led Minnesota with eight receptions for 92 yards and two touchdowns. He caught eight of nine listed targets, giving him a catch rate of approximately 88.9%.

Jefferson’s 39-yard longest reception was shorter than Watson’s 81-yard gain. However, his two touchdown receptions show that Minnesota’s leading receiver converted his opportunities into scoring production.

T.J. Hockenson added four catches for 36 yards and one touchdown. His contribution gave Minnesota a second listed receiving threat with a touchdown, while Josh Oliver recorded 22 yards on two catches.

Justin Jefferson’s Role in the Vikings’ Scoring

Jefferson’s eight receptions accounted for more than half of Minnesota’s 15 listed team receptions. His two touchdowns made him one of the team’s principal scoring contributors.

His performance also demonstrates the difference between explosive yardage and scoring efficiency. Watson produced more receiving yards, but Jefferson matched him in receiving touchdowns. The two receivers had different statistical profiles, yet both delivered important end-zone production.

Jefferson’s nine targets and eight catches suggest that Minnesota completed a high share of its listed attempts directed toward him. Target location, coverage assignments, and yards after the catch would be needed to explain how those opportunities developed.

Comparing the Receiving Groups

The supplied team receiving figures list Green Bay with 387 receiving yards and Minnesota with 151. They also list two receiving touchdowns for the Packers and three for the Vikings.

These numbers favor Green Bay in total receiving yardage but Minnesota in receiving touchdowns. However, the figures are internally inconsistent with the passing totals and require verification before being treated as a definitive statistical comparison.

The broad analytical lesson remains useful: greater yardage does not guarantee more points. Teams must convert passing gains into touchdowns, protect possession, and maintain production throughout all four quarters.

Defensive Player Stats: Pressure, Tackles, and Turnovers

The defensive statistics help explain why Minnesota finished with a 17-point victory despite Green Bay’s impressive passing-yard figures. The supplied team totals show that both defenses recorded 59 tackles, but Minnesota generated more sacks, tackles for loss, passes defended, and quarterback hits.

Team Defensive Comparison

Defensive statistic	Packers	Vikings
Total tackles	59	59
Solo tackles	46	48
Sacks	3	4
Tackles for loss	4	7
Passes defended	2	4
Quarterback hits	6	15
Defensive touchdowns	0	0
Interceptions	1	1

The Vikings recorded four sacks compared with three for Green Bay. Minnesota also registered seven tackles for loss, three more than the Packers, and 15 quarterback hits compared with Green Bay’s six.

These differences are important because defensive effectiveness is not measured by tackles alone. Tackles show how frequently defenders finish plays, but sacks, tackles for loss, and quarterback hits provide additional information about how often a defense disrupts the offense before it can execute its intended play.

Minnesota’s Pass Rush

Minnesota’s 15 quarterback hits were the most striking figure in the defensive comparison. Repeated pressure can force a quarterback to throw earlier than planned, abandon a passing progression, or attempt a difficult pass under pressure.

The Vikings also recorded four sacks in the supplied team totals. Sacks can lead to substantial losses in field position and create long third-down situations that make sustained drives more difficult.

Green Bay’s defense also produced three sacks, so the Packers were not entirely without a pass rush. However, the difference in reported quarterback hits suggests that Minnesota generated more frequent disruption.

A more complete assessment would require play-by-play data showing when the pressure occurred, which defenders generated it, and whether those plays led directly to punts, turnovers, or failed scoring opportunities.

Tackles for Loss and Defensive Discipline

Minnesota’s seven tackles for loss compared with Green Bay’s four indicate that the Vikings more frequently stopped plays behind the line of scrimmage.

These plays can have a wider impact than their immediate yardage suggests. A loss on first down can force an offense to recover the lost distance on later downs. A negative run can also make play-action less effective by preventing the offense from establishing a reliable ground threat.

The Packers’ 59 tackles show that their defense remained active throughout the contest. Yet the higher Minnesota totals for tackles for loss and quarterback hits point to greater disruption in the supplied statistical record.

Interceptions and Defensive Opportunities

Both teams were credited with one interception.

Team	Player	Interceptions	Return yards	Defensive TDs
Packers	Keisean Nixon	1	11	0
Vikings	James Pierre	1	28	0

Keisean Nixon recorded an interception for Green Bay and returned it 11 yards. James Pierre recorded Minnesota’s interception and returned it 28 yards.

An interception can influence a game in several ways. It ends the opponent’s possession, can improve the intercepting team’s starting field position, and may change the risk tolerance of the opposing offense.

Neither listed interception resulted in a defensive touchdown. The value of each turnover therefore depended on what followed, including the resulting field position and subsequent offensive performance. The supplied statistics do not establish the exact scoring outcome of either interception, so a more detailed claim would require the play-by-play record.

Turnovers and Ball Security: A Crucial Part of the Game

Turnovers are among the most important statistics to examine when a team loses despite recording substantial passing production. The supplied figures show one interception for each team, but they also list two Green Bay fumbles, with one lost.

Packers Fumble Statistics

Player or team	Fumbles	Fumbles lost	Recoveries
Jordan Love	2	1	Not listed
Zach Bako-Bewele	0	0	1
Packers team total	2	1	1

The supplied data attributes two fumbles to Love, with one lost. It also lists one recovery by Zach Bako-Bewele.

Because fumble totals and recoveries can be presented differently across statistical feeds, these entries should be checked against the official box score before drawing conclusions about exactly how each loose ball occurred.

The central lesson is that ball security matters even when a quarterback produces strong passing yardage. An offense that gives the ball away loses opportunities to score and can place its defense under additional pressure.

Minnesota’s Fumble Record

Minnesota’s supplied defensive and team statistics list Andrew Van Ginkel with one recovery. The Vikings’ team totals show zero fumbles, zero fumbles lost, and one recovery.

That combination is not sufficiently clear to establish the full sequence of the play. A recovery may be recorded as a defensive statistic when an opponent loses possession, while team fumble summaries may distinguish offensive fumbles from defensive recoveries.

For that reason, the recovery should be reported as supplied without assuming that Minnesota committed a fumble or that the play resulted in a particular scoring opportunity.

Why Turnover Context Matters More Than a Simple Count

A turnover count does not capture every important detail. Analysts should consider:

• Field position: A turnover near the opponent’s end zone offers a different scoring opportunity from one deep in a team’s own territory.
• Timing: A turnover late in a close game can have a greater immediate impact than one early in the first quarter.
• Points after the turnover: The possession that follows determines whether the defense’s work produces points.
• Game situation: A trailing team may take more passing risks, increasing both its opportunity for explosive plays and its turnover exposure.

The Packers’ listed interception and lost fumble, combined with Minnesota’s interception, make ball security a relevant part of the comparison. However, the supplied figures do not provide enough verified play-by-play information to assign a precise number of points to those events.

Special Teams Stats: Kicking, Punting, and Returns

Special teams can influence field position and scoring opportunities without receiving the same attention as quarterback and receiving statistics. In this matchup, the supplied figures show contributions from both kickers, several returners, and both punters.

Kicking Statistics

Statistic	Trey Smack, Packers	Will Reichard, Vikings
Field goals made	3	1
Field goals attempted	3	1
Field-goal percentage	100%	100%
Longest field goal	59 yards	38 yards
Extra points made	1	4
Extra points attempted	2	4
Total points	10	7

Trey Smack is listed with three successful field goals from three attempts, including a longest kick of 59 yards. He also recorded one successful extra point from two attempts, for 10 total points.

Will Reichard is listed with one field goal from one attempt and four successful extra points, contributing seven points.

The figures suggest that Green Bay received more of its listed kicking production from field goals, while Minnesota’s listed kicking output included four extra points. However, the supplied kicking totals do not independently explain the entire final score. They should be interpreted alongside the scoring summary and verified against the official play-by-play record.

Packers Kick Returns

Player	Returns	Return yards	Average	Longest
Bo Melton	4	124	31.0	59
Kaleb Johnson	2	52	26.0	27
Team total	6	176	29.3	59

Bo Melton led the listed Packers kick-return group with 124 yards on four returns. His average was 31.0 yards, and his longest return covered 59 yards.

Kaleb Johnson added 52 yards on two returns. Green Bay’s team total was 176 yards across six returns, with an average of 29.3 yards.

These returns could have helped the Packers improve their starting field position. However, return yardage should not be confused with offensive scrimmage yards or added directly to receiving production when evaluating passing efficiency.

Vikings Kick Returns

Player	Returns	Return yards	Average	Longest
Myles Price	5	179	35.8	68

Myles Price recorded 179 yards on five kick returns, averaging 35.8 yards per return. His longest return was 68 yards.

His listed average exceeded Green Bay’s team kick-return average of 29.3 yards. A strong return average can shorten the distance an offense must travel to reach scoring range, potentially increasing the value of the next possession.

Nevertheless, return averages are most useful when combined with starting field position, return frequency, and the number of returns that produce unusually long gains. One long return can raise a player’s average substantially, so the average alone does not tell the whole story.

Punt Return Statistics

Team	Returner	Returns	Yards	Average	Longest
Packers	Skyy Moore	2	17	8.5	12
Vikings	Myles Price	1	13	13.0	13

Skyy Moore is listed with two punt returns for 17 yards. Myles Price recorded one return for 13 yards.

These totals are relatively small compared with the kick-return figures, but punt returns can still matter because they determine where an offense begins its next possession. The return yardage must be considered with the location of the punt and the resulting field position to measure its true value.

Punting Statistics

Statistic	Daniel Whelan, Packers	Brett Thorson, Vikings
Punts	3	4
Total punt yards	116	161
Average punt	38.7 yards	40.3 yards
Inside the 20	2	3
Touchbacks	0	0
Longest punt	49 yards	48 yards

Daniel Whelan averaged 38.7 yards on three punts, with two inside the opponent’s 20-yard line. Brett Thorson averaged 40.3 yards on four punts, with three inside the 20.

The Vikings’ punting figures show more punts and more attempts placed inside the 20. That can help a defense by forcing the opposing offense to cover more ground before reaching scoring range.

Punting statistics do not automatically indicate that one punter performed better. The location of each kick, hang time, return yardage, and the situation that forced the punt all affect its value. Those details are not available in the supplied summary.

Team Statistics Comparison: Where Minnesota Gained an Advantage

The broad statistical comparison shows an interesting contrast. Green Bay’s listed passing production was greater, but Minnesota’s rushing volume, rushing touchdowns, and defensive pressure figures were stronger.

Offensive and Defensive Overview

Category	Packers	Vikings
Final score	22	39
Passing touchdowns	2	3
Interceptions thrown	1	1
Team rushing yards	66	107
Rushing touchdowns	0	2
Team rushing attempts	21	34
Receiving touchdowns	2	3
Defensive sacks	3	4
Quarterback hits	6	15
Tackles for loss	4	7

These figures are drawn from the supplied dataset. Because several passing, receiving, and scoring totals conflict, this table should be treated as a transcription of the provided figures rather than a fully reconciled official statistical record.

1. Minnesota Had More Ways to Score

The Vikings’ listed offensive figures include three passing touchdowns and two rushing touchdowns. Green Bay’s figures show two passing touchdowns and no rushing touchdowns.

This difference indicates that Minnesota’s listed scoring production was spread across the passing and rushing games. An offense that can score through different methods is harder to defend because opponents cannot focus entirely on one type of play.

Green Bay’s two listed passing touchdowns show that its offense could finish through the air, but the lack of a listed rushing touchdown limited the variety of its scoring production.

2. Green Bay Generated Explosive Passing Plays

Watson’s 147 receiving yards and 81-yard longest catch highlight the Packers’ ability to gain substantial yardage quickly.

Matthew Golden’s 95 yards and Tucker Kraft’s 65 yards also contributed to the supplied receiving totals. These performances show that Green Bay’s passing production was not limited to one player.

However, explosive plays need to be supported by consistent drive execution. A team can gain large chunks of yardage and still struggle to convert possessions into touchdowns.

3. Minnesota’s Ground Game Provided Balance

The Vikings recorded 107 rushing yards and two rushing touchdowns, compared with Green Bay’s 66 rushing yards and zero rushing touchdowns.

Although the listed yards-per-carry averages were both 3.1, Minnesota had 13 more rushing attempts and 41 more rushing yards.

The two rushing touchdowns were particularly relevant because touchdowns convert possession into points. A running game does not need a high average on every carry to be valuable if it consistently finishes short-yardage situations.

4. Defensive Pressure Favored Minnesota

Minnesota recorded 15 quarterback hits, four sacks, and seven tackles for loss in the supplied totals. Green Bay was listed with six quarterback hits, three sacks, and four tackles for loss.

These differences suggest that the Vikings’ defense disrupted more plays. Pressure can make passing less predictable, interfere with timing, and increase the likelihood of hurried decisions.

The statistics do not establish the exact causal relationship between pressure and the final score, but they provide a plausible explanation for why the defensive comparison favors Minnesota.

5. The Fourth Quarter Was the Defining Period

Minnesota scored 22 points in the fourth quarter, while Green Bay scored none. This was the clearest difference in the scoring summary.

A strong finish requires more than one successful play. It can involve converting scoring opportunities, protecting the football, maintaining defensive pressure, and preventing the opponent from answering.

The supplied figures establish the scoring contrast but do not provide enough verified play-by-play information to identify every specific decision or play that produced it.

Statistical Limitations and Data Accuracy

Accurate football analysis requires more than repeating every number in a box score. Individual and team statistics must agree, and scoring totals should reconcile with touchdowns, field goals, extra points, and other scoring plays.

The supplied data explicitly warns of inconsistencies. Several deserve attention before publication.

Passing Yards Do Not Fully Reconcile

The supplied data lists Love with 387 passing yards and the Packers with 353 team passing yards. It also lists Green Bay’s team receiving total as 387 yards.

For Minnesota, Wentz is listed with 133 passing yards, Murray with 18, and the team with 132 passing yards. The team receiving total is listed as 151 yards.

These numbers cannot all be interpreted as equivalent net or gross passing totals without additional context. In American football, passing yards, team net passing yards, and receiving yards can differ because sacks and statistical conventions affect the figures. Even so, the individual and team values provided here require confirmation.

Receiving Totals Need Verification

The individual Packers receiving figures add up to 387 yards across the six listed players. That matches the supplied team receiving total, but it conflicts with the listed team passing total of 353 yards.

Minnesota’s four listed receivers add up to 151 receiving yards, while the team passing total is listed as 132 yards. The individual quarterback figures also do not align cleanly with that team passing total.

These discrepancies could reflect different statistical definitions, omitted entries, or transcription errors. The available information does not establish which explanation is correct.

Scoring Totals Should Be Checked Against the Play-by-Play

The supplied quarter-by-quarter scores add up to the reported final score of 22-39. However, the listed kicking and touchdown summaries do not independently reconcile all scoring details.

A reliable published analysis should verify the scoring plays, extra-point attempts, field goals, and any two-point conversions against the official game record.

How Readers Should Interpret the Numbers

The safest approach is to distinguish between reported statistics and verified conclusions.

• Treat the final score and quarter-by-quarter breakdown as the supplied game summary.
• Use individual player figures with a clear indication that they are transcribed from the supplied dataset.
• Avoid presenting conflicting passing totals as unquestionably correct.
• Confirm any statistic used in a historical comparison, season record, or advanced metric.
• Do not infer a specific play sequence or coaching decision without supporting play-by-play evidence.

For reference, the supplied source identifies the ESPN Packers vs. Vikings box score as the relevant game record. Checking that page and its associated scoring details is advisable before treating every number in the supplied dataset as independently verified.

What These Player Stats Mean for Understanding the Game

Player statistics are most useful when they answer a clear question. A passing table shows production and efficiency. A rushing table explains how an offense distributes carries and finishes ground-based drives. Receiving statistics identify who creates yardage and scores touchdowns. Defensive totals help explain how often a team disrupts the opponent.

In this matchup, four conclusions emerge from the supplied figures.

First, Green Bay’s passing game produced substantial yardage, particularly through Watson. Second, Minnesota’s listed offense recorded more rushing attempts and rushing touchdowns. Third, the Vikings produced more quarterback hits, sacks, and tackles for loss. Fourth, Minnesota’s 22-point fourth quarter transformed the scoring result.

The distinction between statistical volume and game outcome is central. A team can lead in an individual category without controlling the contest overall. The most useful analysis examines how the different categories interact and whether the numbers agree with the scoring record.

For fantasy football readers, Watson and Jefferson would stand out because of their receiving touchdowns and yardage. Mason and Jones would interest readers tracking rushing production. For team analysis, Love’s yardage should be considered alongside his completion rate, sacks, and turnovers, while Wentz’s touchdown production should be evaluated in the context of his smaller passing-yard total.

These interpretations remain descriptive rather than predictive. One game’s statistics cannot establish how either team will perform in future matchups, and the inconsistencies in the supplied data make verification especially important.

Frequently Asked Questions

1. What was the final score of the Packers vs Vikings game on September 14, 2026?

According to the supplied game data, the Minnesota Vikings defeated the Green Bay Packers 39-22. Minnesota scored 22 points in the fourth quarter, while Green Bay was held scoreless in the final period.

2. Who was the leading passer in the game?

Jordan Love was listed as Green Bay’s leading passer with 387 passing yards, two touchdowns, and one interception. Carson Wentz led Minnesota’s passing statistics with 133 yards and three touchdowns. These individual figures come from the supplied dataset and should be checked against the official box score.

3. Which player recorded the most receiving yards?

Christian Watson led the supplied receiving statistics with 147 yards on six receptions, including two touchdowns. His longest reception was listed as 81 yards, making him Green Bay’s leading receiver by yardage.

4. How did Justin Jefferson perform against Green Bay?

Justin Jefferson recorded eight receptions for 92 yards and two touchdowns in the supplied statistics. He was Minnesota’s leading receiver and matched Watson’s listed receiving touchdown total.

5. Which team had the better rushing performance?

Minnesota had the stronger rushing totals, with 107 yards on 34 carries and two touchdowns. Green Bay recorded 66 yards on 21 carries and no rushing touchdowns. Both teams were listed at an average of 3.1 yards per carry.

6. Why did Minnesota win despite Green Bay’s passing production?

The supplied statistics point to Minnesota’s three passing touchdowns, two rushing touchdowns, stronger defensive pressure figures, and 22-point fourth quarter as important differences. However, the available data does not establish the precise cause of every scoring play, and some passing totals require verification.

Conclusion

The green bay packers vs minnesota vikings match player stats illustrate the difference between generating offensive yardage and converting that production into a winning score. Green Bay’s passing game showed explosive potential through Jordan Love and Christian Watson, with Watson recording 147 receiving yards and two touchdowns in the supplied figures. Matthew Golden and Tucker Kraft also contributed to the Packers’ listed receiving production.

Minnesota’s statistical profile was more balanced. Carson Wentz was credited with three passing touchdowns, Justin Jefferson recorded two receiving touchdowns, and Jordan Mason and Aaron Jones Sr. contributed rushing touchdowns. The Vikings also recorded more rushing yards, sacks, tackles for loss, and quarterback hits in the supplied team statistics.

The decisive feature of the reported result was the fourth quarter. Minnesota scored 22 points while Green Bay failed to score, producing the final 39-22 margin. That scoring pattern provides the clearest explanation of the difference between the teams in this dataset.

The numbers should nevertheless be read carefully. Several individual and team passing figures conflict, and the kicking statistics do not independently establish every scoring detail. Verifying those entries against the official game record is necessary before using them as definitive historical statistics.

Taken together, the supplied figures provide a useful framework for examining quarterback efficiency, receiving production, rushing balance, defensive pressure, and scoring distribution. They also reinforce an important principle of football analysis: individual yardage totals are most informative when considered alongside touchdowns, turnovers, field position, defensive performance, and the timing of scoring plays.