The milwaukee bucks vs oklahoma city thunder match player stats from the October 8, 2026, NBA preseason game reveal a close contest decided by just two points. The Milwaukee Bucks defeated the Oklahoma City Thunder 128-126 at Paycom Center in Oklahoma City. Milwaukee finished strongly after trailing by 18 points at halftime, turning a difficult first half into a narrow victory. Myles Turner scored 19 points for Milwaukee, while Kel’el Ware added 18 points and grabbed 12 rebounds. For Oklahoma City, Aday Mara delivered an outstanding performance with 22 points on a perfect 10-for-10 shooting night. The final score tells only part of the story, however. Rebounding, second-chance opportunities, turnovers, and the contrasting performances across the four quarters help explain how Milwaukee secured the win.

This article breaks down the final score, team statistics, leading players, starting lineups, bench contributions, and the most important statistical differences. It also explains how to interpret these numbers in the context of a preseason game, when player development, lineup experimentation, and individual efficiency can matter as much as the result.

Data note: The analysis below uses the supplied ESPN box-score data for the October 8, 2026, preseason matchup. Individual statistics are included where the supplied data identifies them. No unprovided player statistics or quotations are invented.

Game Overview: Milwaukee Bucks vs Oklahoma City Thunder

Milwaukee Bucks

Away team

128

Oklahoma City Thunder

Home team

126

Date

October 8, 2026

Competition

NBA preseason

Venue

Paycom Center

Location

Oklahoma City, Oklahoma

Final margin: Milwaukee won by 2 points.

Source: ESPN official box score

The matchup produced 254 combined points, with both teams showing an ability to score efficiently in stretches. Oklahoma City recorded the higher field-goal percentage and made more three-pointers, but Milwaukee dominated the rebounding battle and collected significantly more offensive rebounds.

Those differences are important because shooting percentages alone do not determine a basketball game’s outcome. A team can shoot more accurately yet lose if it gives up too many second chances, struggles to finish possessions, or allows the opponent to create additional scoring opportunities.

For Milwaukee, the decisive statistical advantage was on the glass. For Oklahoma City, the central question was how a productive first half gave way to a much less effective third quarter.

milwaukee bucks vs oklahoma city thunder match player stats: Complete Team Box Score

The team statistics show why this game was much closer than the final margin might suggest. Oklahoma City was more accurate from the field and beyond the three-point line, but Milwaukee created substantially more opportunities through offensive rebounding.

Team statistic	Milwaukee Bucks	Oklahoma City Thunder
Final score	128	126
Field goals	44/95	46/93
Field-goal percentage	46%	49%
Three-pointers	14/44	17/46
Three-point percentage	32%	37%
Free throws	26/35	17/26
Free-throw percentage	74%	65%
Total rebounds	59	39
Offensive rebounds	20	8
Defensive rebounds	39	31
Assists	31	34
Turnovers	17	14
Steals	8	8
Blocks	7	6
Personal fouls	26	24

Percentages are reported as supplied in the game data. Small differences can occur when percentages are rounded.

What the team numbers reveal

Three major differences stand out.

1. Milwaukee dominated the rebounding battle.

The Bucks collected 59 rebounds compared with 39 for the Thunder. That is a 20-rebound advantage, one of the clearest statistical differences in the game.

More importantly, Milwaukee secured 20 offensive rebounds. Oklahoma City recorded only eight. An offensive rebound allows a team to recover possession after a missed shot and potentially create another scoring opportunity without needing to force a turnover or defend a new possession.

Milwaukee attempted 95 field goals, two more than Oklahoma City, despite shooting less accurately overall. Its ability to recover missed shots helps explain how the Bucks remained productive.

2. Oklahoma City was more accurate from the field.

The Thunder made 46 of 93 field-goal attempts, compared with Milwaukee’s 44 of 95. Oklahoma City also converted 17 three-pointers, three more than the Bucks.

That shooting advantage was meaningful. The Thunder found scoring opportunities from the perimeter and finished with a higher overall field-goal percentage. However, superior shooting accuracy did not compensate fully for Milwaukee’s advantage in rebounding and free-throw scoring.

3. Milwaukee benefited from the free-throw line.

The Bucks attempted 35 free throws and made 26. Oklahoma City attempted 26 and made 17.

Milwaukee therefore scored nine more points from free throws than the Thunder. The difference in made free throws was almost as large as the final two-point margin, although that does not mean free throws alone determined the result. Rebounds, field goals, turnovers, and the timing of scoring all contributed to the final outcome.

The broader lesson is that a box score should be read as a collection of connected events. Shooting efficiency, possession control, and free-throw production interact to determine which team scores more.

Quarter-by-Quarter Score Breakdown

The scoring sequence offers one of the strongest explanations for the Bucks’ victory. Oklahoma City started exceptionally well, but its scoring output declined sharply after halftime.

Quarter	Milwaukee Bucks	Oklahoma City Thunder	Quarter winner
First quarter	35	44	Oklahoma City
Second quarter	29	38	Oklahoma City
Third quarter	33	20	Milwaukee
Fourth quarter	31	24	Milwaukee
Final score	128	126	Milwaukee

First quarter: Oklahoma City establishes control

Oklahoma City scored 44 points in the opening quarter, nine more than Milwaukee’s 35. That offensive output gave the home team an early advantage and established the high-scoring character of the contest.

The Thunder’s eventual total of 17 three-pointers and 46 made field goals suggests that perimeter shooting and overall shot conversion were important components of its scoring production. However, the supplied team totals do not establish exactly how many of those baskets came in the first quarter.

For Milwaukee, scoring 35 points in the same period kept the deficit manageable. The Bucks were not shut down offensively. They simply conceded more points than they produced.

Second quarter: The Thunder extends its lead

Oklahoma City added another 38 points in the second quarter, while Milwaukee scored 29.

Across the opening two periods, the Thunder scored 82 points and Milwaukee scored 64. That created an 18-point halftime advantage for Oklahoma City.

A lead of that size can look decisive, particularly in a preseason game. Yet the halftime score does not necessarily reflect how well each team controls every aspect of play. Oklahoma City was scoring at a high rate, but Milwaukee’s overall rebounding advantage indicates that the Bucks were capable of generating additional possessions.

The key question entering the second half was whether Oklahoma City could sustain its offensive production while limiting Milwaukee’s opportunities after missed shots.

Third quarter: Milwaukee changes the game’s direction

The third quarter produced the largest swing in the contest. Milwaukee scored 33 points, while Oklahoma City managed just 20.

That gave the Bucks a 13-point advantage for the period. The halftime deficit fell from 18 points to five.

The change is especially significant because Milwaukee did not need to produce an extraordinary scoring total to make the game competitive. Instead, the Bucks combined a strong quarter of their own with a substantial reduction in Oklahoma City’s output.

The team statistics provide possible context, including Milwaukee’s offensive rebounding and free-throw advantage. However, without a verified play-by-play breakdown, it would be inaccurate to attribute the third-quarter swing to one specific defensive adjustment or lineup change.

Fourth quarter: The comeback is completed

Milwaukee outscored Oklahoma City 31-24 in the final period. The seven-point advantage was enough to erase the remaining five-point deficit and finish two points ahead.

The Bucks scored 64 points after halftime, while the Thunder scored 44. That 20-point difference in second-half scoring exactly offset Oklahoma City’s 18-point halftime lead and left Milwaukee with a two-point victory.

The pattern is clear: Oklahoma City controlled the first half, while Milwaukee controlled the second.

For readers analyzing game results, quarter-by-quarter splits are often more informative than the final score alone. They reveal whether a team maintained its level, recovered from a poor stretch, or lost control as the game progressed.

Milwaukee Bucks Player Stats and Individual Standouts

Milwaukee’s strongest individual performances came from Myles Turner, Kel’el Ware, and Ryan Rollins. Their reported production highlights three different ways a player can influence a game: scoring, rebounding, and playmaking.

Myles Turner: Milwaukee’s leading scorer

Myles Turner

Milwaukee Bucks

19 points

Turner was Milwaukee’s leading scorer according to the supplied player statistics. His scoring output gave the Bucks an important source of offense in a game in which they needed to overcome a substantial halftime deficit.

Turner’s 19 points led Milwaukee, narrowly ahead of Ware’s 18. The one-point difference between the two players suggests that Milwaukee’s scoring was not entirely dependent on one standout performance.

For a center, scoring totals become more useful when considered alongside shooting attempts, rebounds, blocks, and minutes played. Those details help establish whether a player was efficient, productive over an extended stint, or effective in a particular matchup.

The supplied data does not include Turner’s complete individual shooting line or minutes, so his field-goal percentage and per-minute production cannot be calculated reliably here.

Even with that limitation, his position as the team’s leading scorer makes him one of the principal players to examine when assessing Milwaukee’s offensive output.

Kel’el Ware: A major presence on the boards

Kel’el Ware

Milwaukee Bucks

18 points, 12 rebounds

Ware finished with 18 points and a team-high 12 rebounds, according to the supplied data. His double-double in points and rebounds made him one of Milwaukee’s most productive players.

Ware’s contribution is particularly relevant when considered alongside Milwaukee’s 59 total rebounds.

Twelve rebounds represent a substantial individual contribution, although the team total cannot be attributed to one player. Rebounding depends on positioning, timing, box-outs, defensive rotations, and the work of teammates who prevent opponents from reaching the ball.

Offensive and defensive rebounds also have different purposes. Defensive rebounds finish an opponent’s possession, while offensive rebounds preserve the attacking team’s possession. The supplied data identifies Ware as the leading rebounder but does not separate his 12 rebounds into those two categories.

His 18 points also gave Milwaukee a second major scoring option alongside Turner. That balance can be valuable when a team needs to recover from a deficit because opponents cannot focus exclusively on limiting one scorer.

Ryan Rollins: The leading playmaker

Ryan Rollins

Milwaukee Bucks

7 assists

Rollins led Milwaukee in assists. His seven assists represented an important part of the team’s 31 total assists.

Assists provide a useful measure of how often a player’s pass directly leads to a made basket. They do not capture every good decision, but they can help identify players who contribute to team offense beyond their own scoring.

Rollins’ seven assists indicate a meaningful playmaking contribution. They do not, on their own, establish his total number of potential assists, his turnover rate, or how effectively he managed the offense in different quarters.

Milwaukee committed 17 turnovers as a team, so ball security remains a relevant part of the overall analysis. A full individual box score would be needed to determine Rollins’ personal turnover total and calculate his assist-to-turnover ratio.

Milwaukee’s starting lineup

The supplied game data lists the following Bucks starters:

Player	Jersey number	Statistical information supplied
Jaime Jaquez Jr.	24	Individual line not supplied
Myles Turner	3	19 points
Kel’el Ware	9	18 points, 12 rebounds
Tyler Herro	11	Individual line not supplied
Ryan Rollins	13	7 assists

These five players were listed as Milwaukee’s starters. Their listing should not be taken as proof of a particular minutes distribution or tactical assignment.

Turner’s scoring, Ware’s rebounding, and Rollins’ assists are the clearest individual statistical highlights available in the supplied data. Complete figures for Jaquez Jr. and Herro would be needed to compare their shooting, playmaking, and defensive contributions.

Milwaukee’s bench contributions

The listed Milwaukee bench included Pete Nance, Ousmane Dieng, Nate Ament, Bogoljub Markovic, Jericho Sims, Cormac Ryan, Kam Jones, Brayden Burries, Kasparas Jakucionis, John Butler Jr., Johni Broome, and Jake Stephens.

The supplied summary does not provide complete individual box-score lines for these players. It would therefore be misleading to assign them unverified point totals, rebound numbers, or minutes.

Nevertheless, bench participation matters when interpreting preseason basketball. Coaches often use these games to evaluate players in unfamiliar combinations, test offensive roles, and assess how reserves respond to different opponents.

The most useful next step in evaluating Milwaukee’s bench would be to compare each player’s minutes with points, rebounds, assists, turnovers, and shooting attempts. That would help distinguish a player who scored efficiently in a short stint from one who sustained productive play over a longer period.

Oklahoma City Thunder Player Stats and Individual Standouts

Oklahoma City’s leading statistical performer was Aday Mara, who scored 22 points and made all 10 of his field-goal attempts. Jalen Williams, Cason Wallace, Alex Caruso, and Shai Gilgeous-Alexander also feature in the supplied player highlights.

The Thunder’s individual statistics tell a story that differs from the final result. Oklahoma City had several productive offensive contributors, but its strong first half was followed by a second half in which Milwaukee outscored it by 20 points.

Aday Mara: The game’s leading scorer

Aday Mara

Oklahoma City Thunder

22 points

10-for-10 field goals

6 rebounds

Mara recorded 22 points, six rebounds, and a perfect 10-for-10 field-goal line in the supplied statistics. He was Oklahoma City’s leading scorer and the highest-scoring individual identified in the game summary.

His shooting performance deserves particular attention. A player who makes all 10 field-goal attempts has a 100% field-goal percentage for those attempts. That is an exceptional single-game result, although it should be understood in the context of shot selection and total volume.

Mara’s line also demonstrates why scoring efficiency and the final team result must be evaluated separately. He produced 22 points without missing a field goal, yet Oklahoma City still lost by two.

That does not mean his performance was ineffective. Basketball outcomes depend on the collective performance of all players and on how the team performs across different stretches of the game.

Six rebounds also contributed to Mara’s overall statistical output. However, the supplied information does not establish how many of those rebounds were offensive or defensive, or how many minutes he played.

Jalen Williams: A key passing contributor

Jalen Williams

Oklahoma City Thunder

6 assists

Williams shared the team lead in assists. His six assists contributed to Oklahoma City’s total of 34.

Williams’ six assists highlight a playmaking contribution that is not captured by points alone.

The Thunder recorded 34 assists, three more than Milwaukee. That suggests Oklahoma City generated a substantial amount of assisted scoring, although assists alone cannot reveal the quality of every possession or the amount of off-ball movement involved.

A more complete assessment would examine Williams’ turnovers, field-goal attempts, time on the court, and role in initiating offensive actions. Those details are not included in the supplied summary.

Cason Wallace: Another playmaking option

Cason Wallace

Oklahoma City Thunder

6 assists

Wallace matched Williams’ assist total, giving Oklahoma City another player identified as a leading facilitator.

Having multiple players record six assists each is a useful sign of distributed playmaking. It indicates that the team’s passing contribution was not limited to one individual.

However, the assist totals do not establish whether Williams and Wallace shared ball-handling responsibilities at the same time or operated in separate lineups. That would require substitution records and play-by-play information.

For a more detailed analysis, their individual turnovers and shot creation opportunities would help clarify how effectively they balanced passing and scoring.

Alex Caruso: Perimeter shooting highlight

Alex Caruso

Oklahoma City Thunder

4 of 6

Three-point field goals

Caruso made four of six three-point attempts, giving him a three-point percentage of 66.7% for the game.

His individual efficiency was considerably higher than Oklahoma City’s team three-point percentage of 37%. The difference illustrates why team averages can conceal strong individual performances.

Caruso’s four made three-pointers accounted for 12 points, assuming the supplied line represents his complete three-point production. His accuracy helped Oklahoma City maintain a perimeter threat, even though the team did not finish with the win.

Six attempts remain a relatively small sample. The performance is worth recognizing, but it cannot establish a player’s expected three-point percentage over a full season.

Shai Gilgeous-Alexander: Perfect at the free-throw line

Shai Gilgeous-Alexander

Oklahoma City Thunder

4-for-4

Free throws

Gilgeous-Alexander converted all four of his free-throw attempts. That produced a 100% free-throw percentage in the attempts recorded in the supplied summary.

The distinction between an individual player’s accuracy and the team’s accuracy matters here. Oklahoma City made 17 of 26 free throws overall, or approximately 65.4%, reported as 65% in the supplied data.

A perfect individual line can coexist with a lower team percentage because other players may miss their attempts. The available figures do not provide Gilgeous-Alexander’s complete scoring line, so his total points and overall shooting efficiency should not be inferred from his free throws alone.

Oklahoma City’s starting lineup

The supplied data lists these five Thunder starters:

Player	Jersey number	Statistical information supplied
Aday Mara	15	22 points, 6 rebounds, 10-for-10 shooting
Alex Caruso	9	4-for-6 from three-point range
Shai Gilgeous-Alexander	2	4-for-4 free throws
Jalen Williams	8	6 assists
Cason Wallace	22	6 assists

The table separates confirmed individual highlights from statistics that were not provided. It does not attempt to fill missing categories with estimates.

Oklahoma City’s bench players

The supplied bench list includes Brooks Barnhizer, Andrew Holifield, Christoph Tilly, Kenrich Williams, Jared McCain, Anthony Pritchard, Ajay Mitchell, Josh Dix, Otega Oweh, Bennett Stirtz, Zhaire Smith, and Robert McCray V.

Without their individual box-score lines, there is no reliable basis for ranking these players by scoring, efficiency, rebounding, or defensive production.

A bench analysis should consider more than points. Rebounds can reveal how well a reserve finishes possessions, assists can highlight passing responsibilities, and turnovers can indicate difficulties managing the ball. Shooting attempts and minutes are also essential for understanding context.

This is particularly important during preseason games, when players may receive different opportunities depending on their role, experience, and the lineup combinations being tested.

Bucks vs Thunder: Who Won the Statistical Battle?

Milwaukee won the game, but Oklahoma City led in several traditional shooting and playmaking categories. The comparison becomes more revealing when each statistical category is considered separately.

Category	Advantage	Difference
Final score	Milwaukee	2 points
Field goals made	Oklahoma City	2 more
Field-goal percentage	Oklahoma City	3 percentage points
Three-pointers made	Oklahoma City	3 more
Free throws made	Milwaukee	9 more
Total rebounds	Milwaukee	20 more
Offensive rebounds	Milwaukee	12 more
Assists	Oklahoma City	3 more
Turnovers	Oklahoma City	3 fewer
Steals	Tie	8 each
Blocks	Milwaukee	1 more

Shooting efficiency versus possession volume

Oklahoma City made two more field goals and shot three percentage points better from the field, according to the rounded figures supplied. It also converted three more three-pointers.

Those advantages helped the Thunder build their early lead. Yet shooting accuracy does not measure how many additional opportunities a team creates after missing a shot.

Milwaukee’s 20 offensive rebounds were particularly important in that respect. The Bucks recovered more missed shots and had more opportunities to extend possessions. Although the data does not give the exact number of points generated from those rebounds, the disparity shows that Milwaukee was more successful at recovering the ball on the offensive glass.

Free throws narrowed the gap

Milwaukee made 26 free throws compared with Oklahoma City’s 17. That nine-point difference provided a substantial contribution to the final margin.

The Bucks attempted nine more free throws as well, so the difference was not simply a matter of accuracy. Milwaukee also had more opportunities at the line.

Free-throw totals can reflect several factors, including drives, contact around the basket, shooting fouls, and late-game situations. The supplied summary does not identify which factors produced the difference in this matchup, so it would be speculative to assign a particular cause.

Turnovers gave Oklahoma City an advantage

The Thunder committed 14 turnovers, compared with 17 for Milwaukee.

Turnovers matter because they end possessions without a field-goal attempt. They can also create fast-break opportunities for the opposing team. Oklahoma City’s three-turnover advantage therefore represents another area in which it performed better.

However, the exact number of points scored off turnovers is not available in the supplied figures. It is also not possible to establish whether the turnovers occurred during the first half, second half, or final minutes.

The important conclusion is that Milwaukee overcame its turnover disadvantage through other areas of production, particularly rebounding and free throws.

Advanced Statistical Insights From the Game

Traditional statistics are useful, but a deeper analysis can reveal why certain advantages matter more than others.

The following calculations use the supplied team totals. They are derived metrics, not additional statistics reported in the provided box-score summary.

Effective field-goal percentage

Effective field-goal percentage, commonly abbreviated as eFG%, adjusts ordinary field-goal percentage to account for the additional point awarded for a made three-pointer.

The formula is:

\[ \text{eFG\%}=\frac{\text{FGM}+0.5(\text{3PM})}{\text{FGA}}\times100 \]

Using the supplied figures:

• Milwaukee: (44+0.514)/95, or approximately 53.7%.
• Oklahoma City: (46+0.517)/93, or approximately 58.6%.

Oklahoma City therefore held an effective field-goal percentage advantage of approximately 4.9 percentage points.

This result reinforces the shooting analysis. The Thunder’s edge was not limited to its ordinary field-goal percentage. Its additional three-point makes also increased the value of its converted shots.

Yet eFG% does not include free throws, turnovers, or offensive rebounds. It measures shooting efficiency rather than the entire offensive process.

Free-throw attempt rate

A simple free-throw attempt rate can be calculated by dividing free-throw attempts by field-goal attempts.

• Milwaukee: 35/95, or approximately 36.8%.
• Oklahoma City: 26/93, or approximately 28.0%.

Milwaukee attempted approximately 36.8 free throws per 100 field-goal attempts, compared with about 28 for Oklahoma City.

This calculation highlights the Bucks’ relative advantage in generating free-throw opportunities. It is a descriptive comparison, not proof of why those opportunities occurred.

Offensive rebounding share

One way to compare offensive rebounding is to divide a team’s offensive rebounds by its offensive rebounds plus its opponent’s defensive rebounds.

Using the supplied totals:

• Milwaukee: 20/(20+31), or approximately 39.2%.
• Oklahoma City: 8/(8+39), or approximately 17.0%.

These estimates suggest that Milwaukee recovered a much larger share of the available offensive rebounds represented by these team totals.

This is an important distinction from simply comparing total rebounds. Offensive rebounds preserve possession, whereas defensive rebounds generally finish an opponent’s possession. They serve different strategic purposes, so separating them makes the analysis more informative.

A limitation of advanced metrics

These calculations help explain the statistical contrast, but they do not establish a complete measure of team performance.

A full advanced analysis would also consider possessions, offensive rating, defensive rating, pace, points per possession, and lineup-level results. The official NBA statistics resources explain how advanced measures complement traditional box scores.

Without a verified possession count and full play-by-play data, it would be inappropriate to present precise offensive ratings or claim that a particular tactical adjustment caused Milwaukee’s comeback.

Why Milwaukee Won Despite Shooting Less Accurately

The central statistical question is how the Bucks won when the Thunder had the higher field-goal percentage, made more three-pointers, and recorded more assists.

The answer lies in the combined effects of rebounds, free throws, and scoring across the four quarters.

1. The Bucks created extra opportunities

Milwaukee’s 20 offensive rebounds compared with Oklahoma City’s eight gave the Bucks a major advantage in recovering missed shots.

A missed field goal does not always end an offensive possession. If the attacking team collects the rebound, it can continue its attack and attempt another shot. That can help compensate for a lower shooting percentage.

However, an offensive rebound does not automatically produce points. The next possession may still end in a missed shot, turnover, or defensive foul.

2. Free throws supplied additional scoring

Milwaukee converted nine more free throws than Oklahoma City. Those points helped offset the Thunder’s three-point advantage.

Free throws are also different from field goals because they generally do not require the same type of live-ball scoring possession. Their value becomes particularly clear when the final margin is narrow.

The data establishes the difference in attempts and makes, but it does not provide enough detail to determine the exact circumstances behind every trip to the line.

3. The second half changed the result

Oklahoma City’s 18-point halftime lead was built on a 44-point first quarter and a 38-point second quarter.

Milwaukee then outscored the Thunder 33-20 in the third and 31-24 in the fourth. The Bucks’ second-half scoring advantage was large enough to reverse the game.

This is the clearest explanation for the final result. A team can dominate two quarters and still lose if its opponent performs much better over the remaining two.

4. Both teams had different statistical strengths

The Thunder excelled in shooting efficiency and assists. Milwaukee led in rebounds, offensive rebounds, free throws made, and blocks.

Neither profile tells the whole story on its own. The final outcome reflects the interaction of all these categories rather than one isolated statistic.

For analysts, the most useful approach is to identify the advantages that directly influenced possession count and scoring, then compare them with the team’s performance over time.

What the Preseason Result Means for Both Teams

Preseason basketball is useful for evaluating player performances and lineup combinations, but its results require a different interpretation from regular-season or playoff games.

Coaches may prioritize experimentation, conditioning, player development, and role evaluation. Rotations may change more frequently, and individual workloads may not resemble those of a competitive regular-season matchup.

What Milwaukee can take from the performance

The most encouraging statistical indicators for Milwaukee were its rebounding advantage and its ability to recover from an 18-point halftime deficit.

The Bucks recorded 59 rebounds, including 20 offensive boards, and scored 26 free throws. Those numbers show how the team generated production beyond simply making shots at a high percentage.

The individual performances of Turner and Ware also stand out. Turner led Milwaukee with 19 points, while Ware recorded 18 points and 12 rebounds. Rollins contributed seven assists.

The available figures do not establish whether these performances will translate into the same roles or production during the regular season. That assessment would require further games, minutes data, lineup information, and a larger sample of shooting attempts.

What Oklahoma City can take from the performance

Oklahoma City’s 49% field-goal shooting, 17 made three-pointers, and 34 assists demonstrate strong offensive production in the supplied team statistics.

Mara’s 22 points on 10-for-10 shooting were the clearest individual highlight. Caruso also converted four of six three-point attempts, while Williams and Wallace each recorded six assists.

The primary statistical concern was the team’s rebounding disadvantage. Oklahoma City collected only eight offensive rebounds against Milwaukee’s 20.

Its second-half scoring decline is another area worth reviewing, although the available summary does not reveal whether that change resulted from defensive pressure, lineup changes, missed shots, or another factor.

Why one preseason game should not determine player evaluations

A single game can reveal useful details, but it cannot reliably predict a player’s entire season.

A player may have a highly efficient night on limited attempts. Another may contribute through defense, screening, or passing without accumulating a large scoring total. A third may have a quiet game because of limited minutes or a role that emphasizes other responsibilities.

For a fair evaluation, individual production should be considered alongside playing time, shot volume, turnovers, defensive contributions, and performance across multiple games.

This approach avoids overreacting to a single result and provides a stronger basis for understanding player development.

How to Read the Player Statistics Correctly

Understanding a box score helps readers separate confirmed results from assumptions about how a game unfolded.

The most useful categories in this matchup include:

• PTS (points): The total points a player scored.
• FGM/FGA: Field goals made and field goals attempted.
• FG%: The percentage of field-goal attempts converted into baskets.
• 3PM/3PA: Three-point shots made and attempted.
• FTM/FTA: Free throws made and attempted.
• REB: Total rebounds, including offensive and defensive rebounds.
• AST: Assists credited for passes leading directly to made baskets.
• TOV: Turnovers that end a team’s possession.
• STL: Steals credited when a defender takes possession from the opposing team.
• BLK: Shots blocked by a defender.
• PF: Personal fouls committed.
• Plus/minus: The team’s scoring margin while a particular player is on the court.

These categories provide different kinds of information. Points show scoring output, shooting percentages show conversion rates, and rebounds help explain possession control. Assists reveal one part of playmaking, while turnovers identify possessions lost before a shot can be attempted.

Plus/minus is particularly easy to misunderstand. It measures the difference between a team’s points scored and points allowed while a player is on the floor. It does not mean that the player personally scored or prevented that number of points.

Similarly, a player with a high rebound total may have played substantially more minutes than another player. Comparing raw totals without considering playing time can therefore produce misleading conclusions.

For this matchup, the supplied statistics are enough to identify the leading scorers, the rebounding gap, and the major team-level differences. They are not sufficient to reconstruct every player’s complete performance line.

Game Details, Officials, and Broadcast Information

The supplied game information identifies the following details for the matchup.

Detail	Information
Matchup	Milwaukee Bucks vs Oklahoma City Thunder
Date	October 8, 2026
Game type	NBA preseason
Venue	Paycom Center
Location	Oklahoma City, Oklahoma
Final result	Milwaukee Bucks 128, Oklahoma City Thunder 126
Officials	CJ Washington, Karl Lane, JD Ralls
Listed broadcast platforms	Thunder+ and Thunder App, with additional listings including MyMi and Bucks App

These details provide context for readers looking to identify the correct game rather than a regular-season meeting between the same teams.

The date and preseason designation are especially important because player roles and rotations can differ between preseason and competitive regular-season games. When comparing statistics across multiple matchups, readers should ensure they are comparing the same game type and the correct date.

Frequently Asked Questions

1. Who won the Milwaukee Bucks vs Oklahoma City Thunder game on October 8, 2026?

The Milwaukee Bucks defeated the Oklahoma City Thunder 128-126 in the preseason game at Paycom Center in Oklahoma City. Milwaukee won by two points after trailing 82-64 at halftime.

2. Who was the highest scorer in the matchup?

Aday Mara was the highest scorer identified in the supplied statistics, finishing with 22 points for Oklahoma City. He made all 10 of his field-goal attempts.

3. Which Milwaukee Bucks players led the team statistically?

Myles Turner led Milwaukee with 19 points. Kel’el Ware scored 18 points and collected 12 rebounds, while Ryan Rollins led the Bucks with seven assists.

4. Which team had more rebounds?

Milwaukee collected 59 total rebounds, while Oklahoma City recorded 39. The Bucks also led 20-8 in offensive rebounds, giving them a substantial advantage in recovering missed shots.

5. How did Milwaukee overcome Oklahoma City’s halftime lead?

Oklahoma City led 82-64 at halftime. Milwaukee then outscored the Thunder 33-20 in the third quarter and 31-24 in the fourth. The Bucks’ 20-point second-half scoring advantage was enough to overcome the 18-point deficit.

6. Did Oklahoma City shoot better than Milwaukee?

Yes. Oklahoma City made 46 of 93 field-goal attempts, approximately 49%, compared with Milwaukee’s 44 of 95, approximately 46%. The Thunder also made 17 three-pointers compared with Milwaukee’s 14, but the Bucks held significant advantages in rebounds and free throws.

Conclusion

The Milwaukee Bucks’ 128-126 preseason victory over the Oklahoma City Thunder was a game of contrasting strengths. Oklahoma City shot more accurately, made more three-pointers, and recorded more assists. Milwaukee, however, controlled the rebounding battle, created more second-chance opportunities, and converted nine more free throws.

The individual performances added another layer to the contest. Myles Turner led Milwaukee with 19 points, Kel’el Ware contributed 18 points and 12 rebounds, and Ryan Rollins recorded seven assists. For Oklahoma City, Aday Mara led all identified scorers with 22 points on perfect field-goal shooting, while Jalen Williams and Cason Wallace each recorded six assists.

The quarter-by-quarter breakdown ultimately explains the result. Oklahoma City’s 18-point halftime advantage disappeared as Milwaukee outscored the Thunder by 20 points in the second half.

The most important takeaway is that shooting percentages alone cannot explain a basketball result. Rebounding, free throws, turnovers, and performance across different stretches all contribute to the final score. Because this was a preseason matchup, the individual numbers are best treated as a snapshot of that game rather than a definitive prediction of regular-season performance.