Gwenvs Ambessa
Gwen vs Ambessa is a decisive matchup in LoL patch 26.11. Gwen wins with a 57.7% win rate (+15.4%) over Ambessa based on 26 games. Gwen holds the advantage in both the early and late game. Below you'll find the best Gwen build, runes, laning stats, and strategies for the Gwen vs Ambessa matchup.
Gwen Matchup Breakdown
Use the dropdown to select an opponent and see a detailed breakdown of how Gwen performs against them. You'll get head-to-head win rates, laning stats, the best build and runes for the matchup, and early vs late game analysis — all based on real ranked data.
Who Wins the Gwen vs Ambessa Matchup?
Gwen vs Ambessa Matchup Summary
The Gwen vs Ambessa matchup is a decisive matchup in League of Legends ranked play. Based on 26 recent matches analyzed, Gwen wins with a 57.7% win rate compared to Ambessa's 42.3%, giving Gwen a 15.4 percentage point advantage. Gwen dominates at every stage — from early laning through late game team fights. This consistent advantage makes it difficult for Ambessa players to find favorable windows, so team-dependent strategies and avoiding solo confrontations are essential. The most significant statistical gap is in crowd control, where Ambessa leads by 0.2s CC/min — a difference that heavily influences the outcome of trades and skirmishes. Gwen players can confidently pick into Ambessa and play aggressively from level 1. Look to establish lane dominance early through favorable trades and zone Ambessa away from CS whenever possible. Understanding these matchup dynamics is essential for champion select decisions and in-game strategy when facing this lane opponent.
Gwen vs Ambessa Laning Phase Breakdown
Ambessa is favored during the laning phase against Gwen, winning 3 out of 5 key stat categories. Ambessa holds advantages in damage, crowd control and sustain, making them the stronger laner in this matchup.
Best Gwen Build Against Ambessa
Sorcerer's Shoes is the optimal boots choice against Ambessa, providing the mobility and stats Gwen needs most in this matchup. The top-performing core items for Gwen against Ambessa are Shadowflame, Nashor's Tooth and Dusk and Dawn. This combination gives Gwen an effective balance of damage, survivability, and utility for the matchup. This build performs exceptionally well, achieving a 100.0% win rate across 2 games — well above average and making it the top item path against Ambessa. Adjustments may be needed based on team compositions and game state, but this build provides the strongest foundation for the Gwen vs Ambessa matchup.
Early Game vs Late Game
Gwen50.0%
Ambessa50.0%Gwen64.3%Ambessa35.7%The early game (first 15 minutes) is a toss-up between Gwen and Ambessa, with Gwen holding a razor-thin 50.0% win rate edge (+0.0%). Individual skill and jungle proximity will matter more than champion advantage in the early laning phase.
Gwen is far superior in the late game (25+ minutes), boasting a 64.3% win rate — 28.6 points above Ambessa. Extended games heavily favor Gwen, whose kit and scaling make them a dominant force in team fights and objective control.
Gwen holds the advantage at every stage of the game, making this a consistently favorable matchup from lane through late game team fights. Ambessa players should look for outplays, team-dependent strategies, and picks rather than relying on scaling to win this matchup.
Best Gwen Runes Against Ambessa
Precision
Resolve
Running Precision primary with Resolve secondary allows Gwen to press their advantage against Ambessa, amplifying the strengths that make this a favorable matchup.
Gwen matchup data for League of Legends patch 26.11. The table below shows Gwen's win rate, gold difference, and performance stats against every champion in the current meta. Click any champion name to see a detailed head-to-head breakdown including the best Gwen build, runes, laning stats, and early vs late game analysis for that specific matchup.
Opponent | Win Rate | Matches | CS/min | DMG/min | Gold/game | Early WR | Late WR |
|---|---|---|---|---|---|---|---|
| 50.54% | 93 | 6.3 | 1,321 | 11,434 | 53.2% | 47.8% | |
| 52.75% | 91 | 5.9 | 813 | 11,315 | 52.2% | 53.3% | |
| 53.41% | 88 | 6.3 | 789 | 12,846 | 55.2% | 52.5% | |
| 51.16% | 86 | 6.4 | 966 | 12,469 | 51.3% | 51.1% | |
| 44.05% | 84 | 6.1 | 843 | 12,140 | 42.1% | 45.6% | |
| 35.80% | 81 | 6.4 | 857 | 12,089 | 33.3% | 37.3% | |
| 45.95% | 74 | 7.0 | 1,198 | 13,793 | 52.0% | 42.9% | |
| 34.25% | 73 | 5.6 | 729 | 12,730 | 26.3% | 37.0% | |
| 39.39% | 66 | 6.0 | 815 | 11,896 | 38.2% | 40.6% | |
| 44.62% | 65 | 5.8 | 832 | 11,961 | 48.1% | 42.1% | |
| 47.54% | 61 | 5.8 | 837 | 12,398 | 46.4% | 48.5% | |
| 44.83% | 58 | 6.7 | 830 | 12,290 | 22.7% | 58.3% | |
| 48.15% | 54 | 6.5 | 897 | 10,663 | 53.6% | 42.3% | |
| 56.25% | 48 | 6.1 | 947 | 12,741 | 55.6% | 56.7% | |
| 54.17% | 48 | 6.1 | 1,031 | 11,330 | 56.0% | 52.2% | |
| 32.61% | 46 | 2.1 | 707 | 12,620 | 38.1% | 28.0% | |
| 43.48% | 46 | 6.4 | 1,054 | 13,119 | 40.0% | 45.2% | |
| 55.56% | 45 | 1.2 | 815 | 13,219 | 43.5% | 68.2% | |
| 63.64% | 44 | 6.2 | 887 | 12,947 | 52.6% | 72.0% | |
| 50.00% | 40 | 3.5 | 792 | 13,143 | 37.5% | 58.3% | |
| 50.00% | 40 | 5.8 | 738 | 12,125 | 50.0% | 50.0% | |
| 47.50% | 40 | 5.9 | 768 | 10,767 | 38.1% | 57.9% | |
| 50.00% | 40 | 1.8 | 765 | 12,660 | 50.0% | 50.0% | |
| 58.97% | 39 | 3.1 | 782 | 13,232 | 62.5% | 56.5% | |
| 62.16% | 37 | 4.0 | 920 | 14,183 | 50.0% | 69.6% | |
| 59.46% | 37 | 6.4 | 914 | 11,468 | 47.4% | 72.2% | |
| 57.14% | 35 | 6.4 | 771 | 11,879 | 53.3% | 60.0% | |
| 37.14% | 35 | 5.8 | 1,055 | 12,256 | 21.4% | 47.6% | |
| 45.71% | 35 | 4.4 | 973 | 12,693 | 40.0% | 50.0% | |
| 54.55% | 33 | 6.8 | 829 | 12,296 | 73.3% | 38.9% | |
| 34.38% | 32 | 6.6 | 699 | 11,760 | 25.0% | 50.0% | |
| 37.50% | 32 | 6.3 | 991 | 13,087 | 41.7% | 35.0% | |
| 40.63% | 32 | 6.8 | 787 | 12,264 | 35.7% | 44.4% | |
| 32.26% | 31 | 6.4 | 751 | 11,855 | 44.4% | 27.3% | |
| 54.84% | 31 | 6.5 | 853 | 13,850 | 27.3% | 70.0% | |
| 56.67% | 30 | 6.2 | 817 | 13,025 | 53.9% | 58.8% | |
| 56.67% | 30 | 6.0 | 857 | 10,960 | 52.9% | 61.5% | |
| 51.72% | 29 | 6.3 | 838 | 13,080 | 41.7% | 58.8% | |
| 37.93% | 29 | 6.7 | 836 | 12,930 | 40.0% | 36.8% | |
| 41.38% | 29 | 1.1 | 672 | 13,782 | 33.3% | 45.0% | |
| 65.52% | 29 | 2.1 | 791 | 13,905 | 54.5% | 72.2% | |
| 39.29% | 28 | 5.6 | 923 | 13,661 | 22.2% | 47.4% | |
| 39.29% | 28 | 3.4 | 804 | 12,726 | 46.1% | 33.3% | |
| 44.44% | 27 | 6.5 | 719 | 12,490 | 37.5% | 47.4% | |
| 44.44% | 27 | 5.9 | 922 | 12,311 | 50.0% | 40.0% | |
| 34.62% | 26 | 6.0 | 764 | 11,390 | 38.5% | 30.8% | |
| 42.31% | 26 | 2.1 | 780 | 14,686 | 60.0% | 38.1% | |
| 57.69% | 26 | 5.3 | 781 | 12,218 | 50.0% | 64.3% | |
| 32.00% | 25 | 6.7 | 816 | 11,795 | 27.3% | 35.7% | |
| 64.00% | 25 | 6.5 | 808 | 11,872 | 76.9% | 50.0% | |
| 58.33% | 24 | 2.4 | 755 | 13,826 | 60.0% | 57.1% | |
| 34.78% | 23 | 5.9 | 874 | 11,394 | 38.5% | 30.0% | |
| 39.13% | 23 | 6.6 | 920 | 11,969 | 27.3% | 50.0% | |
| 40.91% | 22 | 6.0 | 775 | 12,054 | 11.1% | 61.5% | |
| 13.64% | 22 | 4.0 | 709 | 11,936 | 10.0% | 16.7% | |
| 45.00% | 20 | 2.6 | 740 | 12,482 | 50.0% | 37.5% | |
| 57.89% | 19 | 4.2 | 920 | 11,660 | 63.6% | 50.0% | |
| 42.11% | 19 | 6.3 | 919 | 11,993 | 54.5% | 25.0% | |
| 66.67% | 18 | 4.4 | 798 | 13,508 | 77.8% | 55.6% | |
| 77.78% | 18 | 6.6 | 848 | 13,724 | 75.0% | 78.6% | |
| 50.00% | 18 | 6.2 | 700 | 12,114 | 66.7% | 33.3% | |
| 44.44% | 18 | 1.7 | 817 | 12,468 | 14.3% | 63.6% | |
| 52.94% | 17 | 6.9 | 980 | 15,351 | 50.0% | 54.5% | |
| 17.65% | 17 | 1.3 | 720 | 13,809 | 20.0% | 16.7% | |
| 62.50% | 16 | 4.1 | 833 | 15,513 | 60.0% | 63.6% | |
| 56.25% | 16 | 6.6 | 853 | 9,927 | 58.3% | 50.0% | |
| 62.50% | 16 | 6.5 | 900 | 13,772 | 57.1% | 66.7% | |
| 53.33% | 15 | 7.0 | 1,048 | 12,566 | 66.7% | 33.3% | |
| 53.33% | 15 | 1.4 | 689 | 13,098 | 42.9% | 62.5% | |
| 66.67% | 15 | 6.7 | 916 | 13,997 | 66.7% | 66.7% | |
| 53.33% | 15 | 6.6 | 924 | 14,647 | 40.0% | 60.0% | |
| 73.33% | 15 | 6.5 | 990 | 12,903 | 66.7% | 77.8% | |
| 33.33% | 15 | 2.9 | 894 | 13,166 | 60.0% | 20.0% | |
| 64.29% | 14 | 7.2 | 961 | 13,249 | 80.0% | 25.0% | |
| 42.86% | 14 | 6.4 | 898 | 11,821 | 33.3% | 50.0% | |
| 61.54% | 13 | 1.1 | 741 | 12,882 | 50.0% | 66.7% | |
| 41.67% | 12 | 2.8 | 1,073 | 14,665 | 50.0% | 37.5% | |
| 25.00% | 12 | 4.9 | 981 | 13,051 | 20.0% | 28.6% | |
| 66.67% | 12 | 1.1 | 820 | 11,138 | 50.0% | 100.0% | |
| 75.00% | 12 | 4.5 | 817 | 11,035 | 77.8% | 66.7% | |
| 41.67% | 12 | 6.4 | 774 | 11,959 | 33.3% | 50.0% | |
| 41.67% | 12 | 1.5 | 738 | 13,531 | 42.9% | 40.0% | |
| 54.55% | 11 | 6.3 | 1,047 | 13,557 | 60.0% | 50.0% | |
| 36.36% | 11 | 0.9 | 647 | 11,169 | 50.0% | 20.0% | |
| 54.55% | 11 | 7.0 | 1,055 | 17,134 | 25.0% | 71.4% | |
| 45.45% | 11 | 1.4 | 891 | 15,988 | 100.0% | 33.3% | |
| 36.36% | 11 | 1.2 | 872 | 13,126 | 33.3% | 40.0% | |
| 72.73% | 11 | 2.0 | 765 | 13,577 | 80.0% | 66.7% | |
| 30.00% | 10 | 6.0 | 830 | 10,221 | 40.0% | 20.0% | |
| 50.00% | 10 | 6.8 | 1,058 | 14,431 | 50.0% | 50.0% | |
| 40.00% | 10 | 6.0 | 820 | 13,057 | 0.0% | 44.4% | |
| 60.00% | 10 | 5.8 | 862 | 14,716 | 50.0% | 62.5% | |
| 60.00% | 10 | 5.8 | 1,187 | 15,518 | 33.3% | 71.4% | |
| 44.44% | 9 | 6.5 | 790 | 12,980 | 25.0% | 60.0% | |
| 77.78% | 9 | 1.1 | 805 | 13,364 | 80.0% | 75.0% | |
| 55.56% | 9 | 7.0 | 1,056 | 15,411 | 50.0% | 57.1% | |
| 33.33% | 9 | 6.2 | 723 | 11,873 | 25.0% | 40.0% | |
| 77.78% | 9 | 2.6 | 989 | 13,532 | 66.7% | 83.3% | |
| 55.56% | 9 | 6.7 | 787 | 13,543 | 50.0% | 57.1% | |
| 66.67% | 9 | 5.2 | 824 | 10,152 | 100.0% | 25.0% | |
| 50.00% | 8 | 1.9 | 919 | 15,668 | 50.0% | 50.0% | |
| 62.50% | 8 | 5.5 | 584 | 10,335 | 75.0% | 50.0% | |
| 50.00% | 8 | 6.6 | 814 | 13,269 | 50.0% | 50.0% | |
| 87.50% | 8 | 6.5 | 898 | 11,704 | 100.0% | 50.0% | |
| 66.67% | 6 | 6.5 | 789 | 13,805 | 100.0% | 50.0% | |
| 66.67% | 6 | 1.8 | 639 | 14,055 | 50.0% | 75.0% | |
| 50.00% | 6 | 5.7 | 919 | 16,427 | 0.0% | 60.0% | |
| 66.67% | 6 | 6.3 | 800 | 12,250 | 100.0% | 33.3% | |
| 83.33% | 6 | 6.4 | 963 | 17,372 | 0.0% | 83.3% | |
| 33.33% | 6 | 7.0 | 667 | 8,344 | 33.3% | 33.3% | |
| 60.00% | 5 | 6.2 | 895 | 14,181 | 50.0% | 66.7% | |
| 60.00% | 5 | 4.6 | 962 | 16,261 | 100.0% | 50.0% | |
| 0.00% | 5 | 5.4 | 491 | 9,891 | 0.0% | 0.0% | |
| 100.00% | 5 | 2.0 | 734 | 16,628 | 100.0% | 100.0% | |
| 40.00% | 5 | 7.2 | 954 | 15,738 | 50.0% | 33.3% | |
| 0.00% | 5 | 0.9 | 629 | 9,016 | 0.0% | 0.0% | |
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Gwen vs Ambessa - Frequently Asked Questions
How does Gwen do against Ambessa in League of Legends?
Gwen wins the Gwen vs Ambessa matchup with a 57.7% win rate compared to Ambessa's 42.3%, a 15.4 percentage point difference. This data is based on 26 recent ranked games in patch 26.11.
How does Gwen do against Ambessa in the early game?
In the early game, Gwen has the advantage against Ambessa with a 50.0% win rate versus 50.0%. Gwen players should look to press their lane advantage through aggressive trades and wave control during the first 15 minutes.
How does Gwen do against Ambessa in the late game?
In the late game, Gwen takes over the Gwen vs Ambessa matchup with a 64.3% win rate compared to 35.7%. Gwen scales better into team fights and objective contests after 25 minutes.
Who wins the Gwen vs Ambessa matchup?
Gwen wins the matchup against Ambessa with a 57.7% win rate in League of Legends patch 26.11. The 15.4 percentage point advantage means Gwen is significantly favored in this lane matchup based on 26 games analyzed.
What is the best Gwen build against Ambessa?
The best Gwen build against Ambessa includes Shadowflame, Nashor's Tooth, Dusk and Dawn with Sorcerer's Shoes. This build achieves a 100.0% win rate in the matchup. Check the matchup breakdown above for the full item path and build order.
What are the best Gwen runes against Ambessa?
The best Gwen runes against Ambessa use the Precision primary tree with Resolve secondary. This rune setup achieves a 100.0% win rate in the Gwen vs Ambessa matchup. See the full rune breakdown in the matchup comparison above.
Does Gwen counter Ambessa?
Yes, Gwen has a favorable matchup against Ambessa with a 57.7% win rate. Gwen strongly counters Ambessa in lane based on current patch 26.11 data.
How do I play Gwen against Ambessa?
When playing Gwen against Ambessa, leverage your statistical advantages by trading aggressively during favorable windows. You have early game priority — look for kills and zone control before first recall. Build the recommended items and runes for this specific matchup for the best results.