Which BWF Players Have the Best Win Rate at Super 1000 Tournaments?
Super 1000 tournaments represent the most competitive regular events on the BWF World Tour calendar — four events per year where the full top-32 field competes and every round presents a potential top-10 opponent. The win rates players post at this tier are a more stringent test of quality than overall tour win rates, because Super 1000 draws offer no easy early-round byes and no field depth gaps to exploit. In our dataset of 1,515 BWF Super 1000 matches from 2018 to early 2021, Kento Momota leads men’s singles at 88.0% (22 wins from 25 matches), with Viktor Axelsen close behind at 84.8% (28 from 33). Here is the full picture of who performs best at the tour’s hardest tier and what that means for assessing player quality.
- Super 1000 events generate 1,515 matches in our dataset — the most competitive tier where all top-32 players are present from R32.
- Kento Momota leads MS Super 1000 win rate at 88.0% across 25 matches; Axelsen is second at 84.8% across 33 matches.
- Yuqi Shi (China) is third at 82.4% from 17 matches — a smaller sample but notably close to the top two.
- Both Momota and Axelsen post higher win rates at Super 1000 than their overall tour rates — suggesting they elevate at the biggest events.
- The gap between Super 1000 win rate and overall win rate is the clearest indicator of whether a player is a “big event” performer or a general tour accumulator.
Why Super 1000 Win Rate Is the Hardest Metric to Fake
At a Super 100 or Super 300 event, the top seed enters at the quarterfinal or round of 16 after a guaranteed bye from the first round or two. Their early opponents are ranked 50 to 150 in the world — meaningful competition, but not the elite-level matchups that define a career. Super 1000 events have no such structure. Every player in the 32-player draw has won at least one qualifying or pre-qualifying match, and the top seeds face competitive opponents from R32 onwards.
The Field Depth Difference at Super 1000
In our Super 1000 match data, the average world ranking of players appearing in the Round of 32 is significantly higher than at lower-tier events. A top-5 seed at a Super 1000 cannot rely on a comfortable first or second round — their R32 opponent might be ranked 20th in the world with their own strong record at the same tier. This means a player who wins 5 or 6 consecutive Super 1000 matches has beaten opponents at World Ranking positions 15 to 30, then 8 to 15, then the top 4 — a genuine gauntlet. By contrast, a player accumulating a high win rate across Super 100 events is beating a far more varied quality of opposition across those same rounds.
Super 1000 win rate is, in this sense, a compression of what overall win rate spread across the full tour cannot capture. It strips away the easiest matches and measures only performance in the most competitive context. It is the metric most aligned with what analysts and fans actually mean when they ask “who is the best player right now.” Understanding how BWF tournament tiers differ is essential for interpreting why Super 1000 performance stands apart.
Momota and Axelsen: Both Elevate at the Biggest Events
The most analytically striking finding in our Super 1000 data is that both Momota and Axelsen perform better at Super 1000 than their overall tour win rates suggest. Momota’s overall MS win rate is 86.6%; his Super 1000 rate is 88.0% — a positive 1.4-point differential. Axelsen’s overall rate is 77.3% with a Super 1000 rate of 84.8% — a positive 7.5-point differential. In other words, both players are more dominant at the hardest tier than across all tiers combined. This pattern characterises the genuine elite: their level rises when the field quality rises.
The contrasting pattern — lower Super 1000 win rate than overall — would indicate a player who accumulates wins at weaker events but struggles at the top. In our dataset, several players show this profile, with a 5-to-15 percentage point drop from overall to Super 1000 win rate. For those players, overall tour win rate overstates their competitiveness at the events that matter most for BWF ranking points.
The Super 1000 Win Rate Rankings: Men’s Singles
In our Super 1000 dataset, which covers events including the Indonesia Open, Japan Open, Malaysia Open, China Open, and Denmark Open from 2018 to early 2021, the following men’s singles ranking emerges among players with at least 8 Super 1000 matches.
The Top Three: Momota, Axelsen, and Shi Yuqi
Kento Momota leads the Super 1000 table at 88.0% from 25 matches and 14 career titles. His 22 wins from 25 Super 1000 matches represent the most efficient record at this tier in our dataset, achieved across multiple editions of the Indonesia Open (where he won repeatedly), Japan Open, and other marquee events. His three losses in Super 1000 matches are what make the 88.0% figure meaningful — they represent the rare occasions when a top opponent on form could stop him at the highest tier.
Viktor Axelsen is second with 84.8% from 33 Super 1000 matches — the largest sample of any player in this tier in our dataset. With 28 wins and 8 titles overall, his Super 1000 record reflects years of consistently competing at the top level across Indonesia, China, Japan, Denmark, and Malaysia. His larger match count at this tier (33 vs. Momota’s 25) gives his 84.8% rate extra statistical weight.
Yuqi Shi (China) is third with 82.4% from 17 Super 1000 matches. His smaller sample warrants some caution, but the rate itself is close to the top two — indicating a player whose Super 1000 performance places him firmly in the elite tier even if his overall tour record and titles count (3) suggest a secondary standing in the field.
The Middle Tier: Chou, Zii Jia Lee, and Ginting
Tien Chen Chou (Chinese Taipei) is fourth with 69.0% from 29 Super 1000 matches — the second-largest sample in the dataset behind Axelsen. His 20 wins from 29 matches at Super 1000 events translate into a rate meaningfully below Momota and Axelsen but well above the field median. His record of 6 titles overall is consistent with a player who can win Super 1000 events but does so less frequently than the top two.
Zii Jia Lee (Malaysia) sits fifth with 68.8% from 16 Super 1000 matches and 2 career titles — a rate competitive with Chou despite fewer total matches. Anthony Ginting (Indonesia) is sixth at 65.2% from 23 Super 1000 matches, placing him below Chou and Lee despite having a comparable overall win rate. Ginting’s Super 1000 rate (65.2%) is only 3.4 points below his overall rate (61.8%) — wait, his overall rate is 61.8% while his Super 1000 is 65.2%, meaning he actually performs better at Super 1000 than across all tiers, similar to Axelsen and Momota but with a smaller absolute differential.
Players Whose Super 1000 Rate Trails Their Overall Rate
Below the top six, several players show a more mixed Super 1000 record. Anders Antonsen (Denmark) posts 53.8% at Super 1000 (14 wins from 26 matches) compared to his overall rate of 60.2% — a 6.4-point drop indicating that Super 1000 fields consistently challenge him beyond what the average BWF draw does. Jonatan Christie (Indonesia) shows a similar pattern at 47.1% Super 1000 from 17 matches, compared to his overall rate of 63.7% — a 16.6-point gap that is significant. This tells a clear story: Christie is a strong tour performer who is below his best when specifically facing the Super 1000 field.
How to Use Super 1000 Win Rate in Player Analysis
The Super 1000 win rate has two practical applications in player analysis that overall win rate cannot replicate.
The “Big Event Lift” Indicator
Calculate a player’s Super 1000 differential: (Super 1000 win rate) minus (overall win rate). A positive differential — like Axelsen’s +7.5 or Momota’s +1.4 — indicates a player who elevates at major events. A negative differential — like Antonsen’s -6.4 or Christie’s -16.6 — indicates a player whose game does not consistently translate to the hardest tier. This single number is faster than reading through a full round performance breakdown when the question is specifically about a player’s elite-event credentials.
Minimum Sample Requirements for Super 1000 Rate
Given that Super 1000 events offer at most 5 to 7 matches per tournament and there are only 4 Super 1000 events per year, even a full season at this tier generates only 10 to 30 Super 1000 matches for the most active players. In our dataset, the players with the most Super 1000 matches are Axelsen (33) and Tien Chen Chou (29) — both figures representing roughly 2.5 to 3 years of sustained top-tier competition. Treat any Super 1000 rate below 15 matches with caution; below 8, the rate is directional only. The minimum threshold for treating a Super 1000 win rate as a stable performance indicator is approximately 12 to 15 matches.
Frequently Asked Questions
Which BWF player has the highest win rate at Super 1000 tournaments?
In our database of 14,918 BWF World Tour matches from 2018 to early 2021, Kento Momota (Japan) leads men’s singles at Super 1000 events with an 88.0% win rate (22 wins from 25 matches). Viktor Axelsen is second at 84.8% (28 from 33), and Yuqi Shi of China is third at 82.4% from 17 matches.
How many BWF Super 1000 tournaments are held per year?
The BWF World Tour includes four Super 1000 events per year in the standard calendar: the Indonesia Open, Japan Open, Denmark Open, and China Open (or Malaysia Open in some years). Each event offers the maximum BWF ranking points available at a regular tour event, second only to the World Championships and BWF World Tour Finals.
What is the difference between Super 1000 and Super 100 win rates?
Super 1000 win rates reflect performance against the world’s top 32 players in full-field draws, where even early rounds present top-20 opponents. Super 100 win rates include matches against players ranked 50 to 200, with lower-ranked fields especially in early rounds. A player’s Super 1000 win rate is typically 5 to 15 percentage points lower than their Super 100 rate, because the field quality is substantially higher at every round.