Heist · Not in the current Ranked pool
Best Brawlers for Jedna
Which brawler should you pick on Jedna? These are the win rates BrawlPick observed for 99 brawlers on this Heist map, from about 3,880 battles. The most reliable strong performer was Gigi, winning 67.5% of 228 games.
Data last updated .
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Strongest observed brawlers on Jedna
Ordered by the low end of each brawler's 95% range, not by raw win rate, so a high number from a small sample doesn't jump to the top. The range shows how far the true win rate could plausibly be from the observed one.
| # | Brawler | Win rate | 95% range | Pick rate | Games |
|---|---|---|---|---|---|
| 1 | 67.5% | 61–73% | 5.9% | 228 | |
| 2 | 64.1% | 61–67% | 24.7% | 960 | |
| 3 | 76.5% | 60–88% | 0.9% | 34* | |
| 4 | 68.3% | 59–76% | 2.7% | 104* | |
| 5 | 62.5% | 59–66% | 16.6% | 643 | |
| 6 | 60.8% | 54–67% | 5.1% | 199 | |
| 7 | 67.3% | 54–78% | 1.3% | 52* | |
| 8 | 58.2% | 53–63% | 10.8% | 419 | |
| 9 | 57.2% | 53–61% | 16.1% | 626 | |
| 10 | 62% | 53–70% | 3.1% | 121* |
* Fewer than 150 games: a limited sample, so the range is wide.
What the data says about Jedna
- The most played brawler here, Jessie (1,478 games), ranks #15 by reliability — popular is not the same as strong on this map.
Classes are the official in-game classes. These are descriptions of the observed games, not causes.
Promising, but not enough games yet
These brawlers won often on Jedna but appear in fewer than 150 observed games, so their win rate is much less certain.
Most played on Jedna
Brawlers that appeared in the most observed games. Popular is not the same as strong — compare the win rates.
Lowest observed win rates
Brawlers whose win rate on Jedna was clearly below 50% in this sample, even allowing for its size. This can reflect the map, the drafts they were picked into, or who played them — not necessarily that the brawler can't work here.
All 99 brawlers on Jedna
| # | Brawler | Win rate | 95% range | Pick rate | Games |
|---|---|---|---|---|---|
| 1 | 67.5% | 61–73% | 5.9% | 228 | |
| 2 | 64.1% | 61–67% | 24.7% | 960 | |
| 3 | 76.5% | 60–88% | 0.9% | 34* | |
| 4 | 68.3% | 59–76% | 2.7% | 104* | |
| 5 | 62.5% | 59–66% | 16.6% | 643 | |
| 6 | 60.8% | 54–67% | 5.1% | 199 | |
| 7 | 67.3% | 54–78% | 1.3% | 52* | |
| 8 | 58.2% | 53–63% | 10.8% | 419 | |
| 9 | 57.2% | 53–61% | 16.1% | 626 | |
| 10 | 62% | 53–70% | 3.1% | 121* | |
| 11 | 64.4% | 53–74% | 1.9% | 73* | |
| 12 | 60.9% | 53–68% | 3.9% | 151 | |
| 13 | 55.7% | 53–59% | 27% | 1,048 | |
| 14 | 56.4% | 52–60% | 15.3% | 594 | |
| 15 | 54.5% | 52–57% | 38.1% | 1,478 | |
| 16 | 64.4% | 52–75% | 1.5% | 59* | |
| 17 | 54.7% | 51–58% | 17.6% | 684 | |
| 18 | 62.7% | 51–73% | 1.7% | 67* | |
| 19 | 56.8% | 50–63% | 5.1% | 199 | |
| 20 | 53.3% | 49–57% | 14.2% | 552 | |
| 21 | 53% | 49–57% | 13.9% | 540 | |
| 22 | 51.8% | 49–55% | 22.9% | 888 | |
| 23 | 52.5% | 48–57% | 13.5% | 522 | |
| 24 | 63.4% | 48–76% | 1.1% | 41* | |
| 25 | 50.8% | 47–54% | 22.4% | 868 | |
| 26 | 52.4% | 47–58% | 8.1% | 315 | |
| 27 | 57% | 46–67% | 2.2% | 86* | |
| 28 | 52.3% | 46–58% | 6.7% | 260 | |
| 29 | 49% | 46–52% | 25.8% | 1,002 | |
| 30 | 58.6% | 46–70% | 1.5% | 58* | |
| 31 | 50.4% | 46–55% | 11% | 427 | |
| 32 | 49.7% | 45–55% | 10.1% | 390 | |
| 33 | 56% | 45–67% | 1.9% | 75* | |
| 34 | 56.3% | 45–67% | 1.8% | 71* | |
| 35 | 54.8% | 45–65% | 2.4% | 93* | |
| 36 | 50.6% | 45–57% | 6.7% | 259 | |
| 37 | 48.7% | 44–53% | 12.1% | 470 | |
| 38 | 52.6% | 44–61% | 3% | 116* | |
| 39 | 55.4% | 43–67% | 1.7% | 65* | |
| 40 | 47.4% | 43–52% | 12.7% | 492 | |
| 41 | 52.9% | 43–63% | 2.2% | 87* | |
| 42 | 55.6% | 42–68% | 1.4% | 54* | |
| 43 | 56.5% | 42–70% | 1.2% | 46* | |
| 44 | 52.8% | 41–64% | 1.9% | 72* | |
| 45 | 48.5% | 41–56% | 4.3% | 167 | |
| 46 | 44.1% | 41–47% | 22.8% | 885 | |
| 47 | 57.6% | 41–73% | 0.9% | 33* | |
| 48 | 48% | 41–55% | 4.4% | 171 | |
| 49 | 51.6% | 39–64% | 1.6% | 62* | |
| 50 | 43.9% | 39–49% | 11.6% | 449 | |
| 51 | 47.2% | 39–55% | 3.7% | 144* | |
| 52 | 48.5% | 39–58% | 2.6% | 101* | |
| 53 | 45.9% | 38–54% | 3.8% | 146* | |
| 54 | 42.3% | 38–47% | 12.4% | 480 | |
| 55 | 41.5% | 38–46% | 15.1% | 586 | |
| 56 | 46.4% | 37–56% | 2.9% | 112* | |
| 57 | 41.6% | 37–47% | 9.1% | 353 | |
| 58 | 51.4% | 36–67% | 1% | 37* | |
| 59 | 44.9% | 36–54% | 2.8% | 107* | |
| 60 | 43% | 35–51% | 3.8% | 149* | |
| 61 | 48.1% | 35–61% | 1.3% | 52* | |
| 62 | 45.5% | 34–57% | 1.7% | 66* | |
| 63 | 41% | 34–48% | 4.5% | 173 | |
| 64 | 44.9% | 34–57% | 1.8% | 69* | |
| 65 | 46.9% | 34–61% | 1.3% | 49* | |
| 66 | 38.2% | 33–44% | 7.4% | 288 | |
| 67 | 39.5% | 32–47% | 4.2% | 162 | |
| 68 | 41.5% | 32–52% | 2.4% | 94* | |
| 69 | 39.7% | 31–49% | 3% | 116* | |
| 70 | 46% | 31–62% | 1% | 37* | |
| 71 | 42.9% | 31–56% | 1.4% | 56* | |
| 72 | 40.5% | 30–52% | 1.9% | 74* | |
| 73 | 40.5% | 30–52% | 1.9% | 74* | |
| 74 | 44.4% | 30–60% | 0.9% | 36* | |
| 75 | 37.5% | 29–47% | 2.9% | 112* | |
| 76 | 39.4% | 29–51% | 1.7% | 66* | |
| 77 | 38.4% | 28–50% | 1.9% | 73* | |
| 78 | 35.3% | 28–44% | 3.4% | 133* | |
| 79 | 33.5% | 27–40% | 5% | 194 | |
| 80 | 35.6% | 27–45% | 2.7% | 104* | |
| 81 | 33.5% | 27–41% | 4.5% | 173 | |
| 82 | 34.1% | 27–43% | 3.4% | 132* | |
| 83 | 34.7% | 26–44% | 2.6% | 101* | |
| 84 | 35.4% | 26–46% | 2.1% | 82* | |
| 85 | 39% | 26–54% | 1.1% | 41* | |
| 86 | 34.9% | 26–46% | 2.1% | 83* | |
| 87 | 37.5% | 25–52% | 1.2% | 48* | |
| 88 | 31.3% | 23–41% | 2.5% | 96* | |
| 89 | 30.2% | 22–41% | 2.2% | 86* | |
| 90 | 31% | 21–44% | 1.5% | 58* | |
| 91 | 27.5% | 20–36% | 3.1% | 120* | |
| 92 | 29% | 19–41% | 1.6% | 62* | |
| 93 | 24% | 17–32% | 3.1% | 121* | |
| 94 | 28.6% | 17–44% | 1.1% | 42* | |
| 95 | 25.5% | 16–39% | 1.3% | 51* | |
| 96 | 23.6% | 14–36% | 1.4% | 55* | |
| 97 | 21.4% | 13–32% | 1.8% | 70* | |
| 98 | 22.2% | 13–35% | 1.4% | 54* | |
| 99 | 18.4% | 10–31% | 1.3% | 49* |
8 more brawlers were seen on Jedna with fewer than 30 games and are not rated.
How to use these numbers
These are observed results, not a prediction. A win rate also reflects who played the brawler and the drafts it was picked into: a brawler that is usually chosen as a counter will look stronger than it would as a blind first pick.
Use the table to shortlist brawlers for Jedna, then decide from your draft: what was banned, what your team needs and what the enemy picked. That last step is what the BrawlPick picker does for you — it weighs these numbers together with counters, synergy and role balance, so its recommendation is not simply this table sorted by win rate.
About this data
- Source:
- battle logs from the official Brawl Stars API, collected by BrawlPick. Not copied from another site.
- Players:
- seeded from BrawlPick users, public leaderboards and top clubs, then widened to the players they met. Likely skewed toward more active, higher-skill players; not a random sample.
- Battles:
- every 3v3 battle with a win or loss (Ranked and regular matches), each counted once even if seen through several players. Mostly from the days before the update date.
- Win rate:
- share of a brawler's appearances where its team won. Both teams are counted, so the average is about 50%. "Games" is the number of appearances.
- Small samples:
- win rates are only shown from 30 games; the 95% range shows the remaining uncertainty, and lists are ordered by its low end.
- Game version:
- not recorded per battle. If a balance update landed during the collection period, the numbers mix battles from before and after it.
Full methodology: how BrawlPick works.
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