
Pantheonvs Olaf
Pantheon vs Olaf is a decisive matchup in LoL patch 26.7. Olaf wins with a 56.0% win rate (+12.0%) over Pantheon based on 25 games. Olaf wins the early laning phase while Pantheon scales better into the late game. Below you'll find the best Pantheon build, runes, laning stats, and strategies for the Pantheon vs Olaf matchup.
Pantheon Matchup Breakdown
Use the dropdown to select an opponent and see a detailed breakdown of how Pantheon 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 Pantheon vs Olaf Matchup?

Pantheon vs Olaf Matchup Summary
The Pantheon vs Olaf matchup is a decisive matchup in League of Legends ranked play. Based on 25 recent matches analyzed, Olaf wins with a 56.0% win rate compared to Pantheon's 44.0%, giving Olaf a 12.0 percentage point advantage. Game phase dynamics play a critical role here: Olaf controls the early laning stage, but Pantheon outscales as the game goes longer. The matchup shifts dramatically depending on game length — Olaf needs to press advantages before Pantheon reaches their power spikes, while Pantheon should focus on safe farming and hitting key item breakpoints. The most significant statistical gap is in sustain, where Olaf leads by 813 HP/min — a difference that heavily influences the outcome of trades and skirmishes. Olaf has a strong advantage in this matchup. Pantheon players should play defensively, prioritize safe farming under tower, and look for opportunities created by jungle pressure or Olaf overextending. Avoid prolonged trades and wait for team fights where positioning and coordination matter more. Understanding these matchup dynamics is essential for champion select decisions and in-game strategy when facing this lane opponent.
Pantheon vs Olaf Laning Phase Breakdown
Olaf is favored during the laning phase against Pantheon, winning 3 out of 5 key stat categories. Olaf holds advantages in farming, gold income and sustain, making them the stronger laner in this matchup.
Best Pantheon Build Against Olaf
Mercury's Treads is the optimal boots choice against Olaf, providing the mobility and stats Pantheon needs most in this matchup. The top-performing core items for Pantheon against Olaf are Eclipse, Sundered Sky and Black Cleaver. This combination gives Pantheon an effective balance of damage, survivability, and utility for the matchup. This build performs exceptionally well, achieving a 66.7% win rate across 3 games — well above average and making it the top item path against Olaf. Adjustments may be needed based on team compositions and game state, but this build provides the strongest foundation for the Pantheon vs Olaf matchup.
Early Game vs Late Game
Olaf dominates the early game (first 15 minutes) with a commanding 66.7% win rate — a 33.3 percentage point lead over Pantheon. This lopsided early game means Olaf can dictate the pace of the lane from level 1, controlling trades, wave state, and river priority.
Late game (25+ minutes) is equally balanced, with Pantheon at 50.0% win rate — only 0.0 points ahead of Olaf. Team fight execution and macro play determine the winner at this stage, not champion matchup advantage.
The power dynamics shift as the game progresses — Olaf has the edge early, but Pantheon gradually takes over. However, the margins are slim enough that either champion can win at any stage with the right plays. Focus on taking advantages when you have them rather than waiting for a specific game phase.
Best Pantheon Runes Against Olaf
The Precision and Sorcery rune setup gives Pantheon the best tools to compete against Olaf in this difficult matchup, compensating for the statistical disadvantages with optimal rune synergies.
Pantheon matchup data for League of Legends patch 26.7. The table below shows Pantheon'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 Pantheon 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 |
|---|---|---|---|---|---|---|---|
| 58.41% | 113 | 5.7 | 924 | 12,052 | 59.6% | 57.4% | |
| 55.45% | 101 | 2.2 | 666 | 10,636 | 58.7% | 52.7% | |
| 53.26% | 92 | 1.5 | 647 | 9,840 | 44.9% | 62.8% | |
| 46.67% | 75 | 1.5 | 652 | 10,931 | 46.4% | 46.8% | |
| 41.67% | 72 | 1.6 | 649 | 9,780 | 33.3% | 47.6% | |
| 50.00% | 70 | 1.7 | 710 | 10,581 | 50.0% | 50.0% | |
| 42.42% | 66 | 5.6 | 902 | 12,135 | 54.8% | 31.4% | |
| 43.94% | 66 | 1.5 | 671 | 11,038 | 44.0% | 43.9% | |
| 49.21% | 63 | 5.4 | 857 | 11,606 | 48.0% | 50.0% | |
| 49.12% | 57 | 1.6 | 704 | 10,807 | 47.8% | 50.0% | |
| 47.37% | 57 | 1.5 | 703 | 10,353 | 43.5% | 50.0% | |
| 50.00% | 56 | 2.0 | 778 | 11,169 | 56.5% | 45.5% | |
| 44.44% | 54 | 1.6 | 704 | 9,865 | 44.4% | 44.4% | |
| 34.62% | 53 | 2.6 | 837 | 10,601 | 31.8% | 36.7% | |
| 46.15% | 52 | 5.1 | 1,010 | 11,321 | 53.9% | 38.5% | |
| 55.77% | 52 | 1.9 | 698 | 11,149 | 47.8% | 62.1% | |
| 54.90% | 51 | 4.5 | 753 | 10,225 | 57.1% | 52.2% | |
| 52.00% | 50 | 1.4 | 754 | 10,299 | 50.0% | 53.9% | |
| 44.90% | 49 | 3.5 | 993 | 12,725 | 50.0% | 41.4% | |
| 54.17% | 48 | 1.6 | 698 | 10,330 | 44.8% | 68.4% | |
| 51.06% | 47 | 1.4 | 638 | 10,347 | 40.0% | 59.3% | |
| 44.68% | 47 | 1.5 | 667 | 10,840 | 41.2% | 46.7% | |
| 44.68% | 47 | 3.1 | 834 | 12,340 | 25.0% | 54.8% | |
| 62.22% | 45 | 5.7 | 908 | 12,112 | 76.2% | 50.0% | |
| 53.33% | 45 | 5.2 | 832 | 10,866 | 54.5% | 52.2% | |
| 43.18% | 44 | 3.9 | 823 | 11,884 | 59.1% | 27.3% | |
| 60.00% | 40 | 4.8 | 881 | 12,239 | 61.1% | 59.1% | |
| 38.46% | 39 | 4.8 | 820 | 10,683 | 41.7% | 33.3% | |
| 46.15% | 39 | 1.4 | 643 | 10,298 | 58.8% | 36.4% | |
| 48.65% | 37 | 6.0 | 883 | 10,817 | 55.0% | 41.2% | |
| 48.65% | 37 | 1.4 | 626 | 9,622 | 57.9% | 38.9% | |
| 64.86% | 37 | 1.4 | 676 | 10,130 | 60.0% | 70.6% | |
| 61.11% | 36 | 1.5 | 719 | 11,895 | 41.7% | 70.8% | |
| 55.56% | 36 | 1.6 | 652 | 10,262 | 63.2% | 47.1% | |
| 44.44% | 36 | 1.6 | 707 | 11,963 | 45.5% | 44.0% | |
| 44.12% | 34 | 1.7 | 795 | 12,153 | 44.4% | 43.8% | |
| 55.88% | 34 | 5.8 | 902 | 11,588 | 50.0% | 62.5% | |
| 58.82% | 34 | 4.3 | 724 | 11,542 | 60.0% | 57.9% | |
| 48.48% | 33 | 4.3 | 970 | 12,375 | 46.1% | 50.0% | |
| 36.36% | 33 | 1.3 | 706 | 12,117 | 37.5% | 35.3% | |
| 48.48% | 33 | 1.2 | 730 | 10,880 | 63.6% | 40.9% | |
| 50.00% | 32 | 2.6 | 619 | 10,711 | 50.0% | 50.0% | |
| 50.00% | 32 | 1.4 | 705 | 12,152 | 42.9% | 55.6% | |
| 41.94% | 31 | 4.1 | 831 | 11,039 | 47.1% | 35.7% | |
| 41.94% | 31 | 1.1 | 630 | 11,813 | 43.8% | 40.0% | |
| 43.33% | 30 | 0.8 | 719 | 11,885 | 50.0% | 37.5% | |
| 60.00% | 30 | 4.2 | 826 | 10,992 | 47.6% | 88.9% | |
| 58.62% | 29 | 6.0 | 817 | 11,366 | 56.3% | 61.5% | |
| 37.93% | 29 | 3.6 | 904 | 12,396 | 30.8% | 43.8% | |
| 64.29% | 28 | 1.4 | 656 | 11,342 | 58.8% | 72.7% | |
| 28.57% | 28 | 1.3 | 645 | 10,297 | 23.1% | 33.3% | |
| 53.57% | 28 | 3.5 | 959 | 12,667 | 46.7% | 61.5% | |
| 35.71% | 28 | 2.8 | 795 | 11,272 | 36.4% | 35.3% | |
| 67.86% | 28 | 3.3 | 852 | 12,311 | 91.7% | 50.0% | |
| 71.43% | 28 | 5.4 | 934 | 10,332 | 58.8% | 90.9% | |
| 40.74% | 27 | 2.4 | 674 | 10,074 | 50.0% | 30.8% | |
| 44.44% | 27 | 1.3 | 788 | 13,065 | 50.0% | 42.1% | |
| 59.26% | 27 | 5.8 | 978 | 13,284 | 63.6% | 56.3% | |
| 34.62% | 26 | 5.2 | 802 | 11,231 | 27.3% | 40.0% | |
| 61.54% | 26 | 4.7 | 942 | 12,052 | 50.0% | 68.8% | |
| 36.00% | 25 | 5.5 | 806 | 11,629 | 35.7% | 36.4% | |
| 40.00% | 25 | 4.7 | 860 | 12,902 | 22.2% | 50.0% | |
| 44.00% | 25 | 5.4 | 947 | 12,170 | 33.3% | 50.0% | |
| 48.00% | 25 | 1.5 | 754 | 10,784 | 46.7% | 50.0% | |
| 50.00% | 24 | 3.6 | 884 | 12,433 | 60.0% | 42.9% | |
| 62.50% | 24 | 5.2 | 1,054 | 11,773 | 69.2% | 54.5% | |
| 78.26% | 23 | 5.3 | 874 | 12,150 | 66.7% | 85.7% | |
| 65.22% | 23 | 1.6 | 729 | 10,824 | 42.9% | 75.0% | |
| 52.17% | 23 | 3.2 | 764 | 11,687 | 58.3% | 45.5% | |
| 47.83% | 23 | 5.6 | 1,008 | 12,815 | 71.4% | 37.5% | |
| 43.48% | 23 | 4.6 | 817 | 10,086 | 53.9% | 30.0% | |
| 50.00% | 22 | 2.8 | 766 | 12,878 | 33.3% | 56.3% | |
| 68.18% | 22 | 1.3 | 737 | 12,612 | 57.1% | 73.3% | |
| 31.82% | 22 | 0.9 | 576 | 10,805 | 28.6% | 37.5% | |
| 68.18% | 22 | 5.8 | 930 | 11,313 | 75.0% | 64.3% | |
| 36.36% | 22 | 5.5 | 923 | 10,310 | 38.5% | 33.3% | |
| 52.38% | 21 | 5.3 | 863 | 11,603 | 66.7% | 46.7% | |
| 61.90% | 21 | 0.9 | 769 | 13,778 | 100.0% | 50.0% | |
| 50.00% | 20 | 4.6 | 792 | 10,435 | 60.0% | 40.0% | |
| 45.00% | 20 | 0.9 | 651 | 11,609 | 40.0% | 50.0% | |
| 65.00% | 20 | 1.6 | 690 | 11,349 | 70.0% | 60.0% | |
| 60.00% | 20 | 4.4 | 869 | 12,855 | 50.0% | 64.3% | |
| 45.00% | 20 | 4.5 | 892 | 11,050 | 11.1% | 72.7% | |
| 31.58% | 19 | 1.7 | 706 | 9,047 | 33.3% | 28.6% | |
| 15.79% | 19 | 1.5 | 672 | 12,011 | 0.0% | 21.4% | |
| 61.11% | 18 | 0.8 | 841 | 12,796 | 55.6% | 66.7% | |
| 44.44% | 18 | 3.2 | 852 | 11,575 | 66.7% | 33.3% | |
| 52.94% | 17 | 1.4 | 746 | 10,749 | 50.0% | 55.6% | |
| 47.06% | 17 | 2.1 | 743 | 12,928 | 50.0% | 45.5% | |
| 52.94% | 17 | 5.8 | 896 | 10,114 | 55.6% | 50.0% | |
| 41.18% | 17 | 0.8 | 784 | 12,294 | 42.9% | 40.0% | |
| 56.25% | 16 | 5.4 | 876 | 12,951 | 80.0% | 45.5% | |
| 37.50% | 16 | 5.6 | 751 | 11,859 | 37.5% | 37.5% | |
| 37.50% | 16 | 2.6 | 921 | 11,553 | 25.0% | 50.0% | |
| 43.75% | 16 | 5.8 | 930 | 11,762 | 37.5% | 50.0% | |
| 56.25% | 16 | 0.8 | 752 | 13,671 | 50.0% | 58.3% | |
| 31.25% | 16 | 5.4 | 961 | 13,863 | 60.0% | 18.2% | |
| 53.33% | 15 | 4.3 | 749 | 9,873 | 55.6% | 50.0% | |
| 53.33% | 15 | 3.5 | 855 | 12,535 | 25.0% | 63.6% | |
| 60.00% | 15 | 5.4 | 850 | 13,569 | 75.0% | 54.5% | |
| 78.57% | 14 | 5.6 | 998 | 12,482 | 60.0% | 88.9% | |
| 50.00% | 14 | 5.5 | 778 | 10,388 | 83.3% | 25.0% | |
| 64.29% | 14 | 1.4 | 617 | 9,827 | 62.5% | 66.7% | |
| 35.71% | 14 | 3.3 | 712 | 10,502 | 50.0% | 16.7% | |
| 57.14% | 14 | 5.2 | 1,095 | 12,669 | 60.0% | 55.6% | |
| 35.71% | 14 | 1.4 | 696 | 12,148 | 66.7% | 12.5% | |
| 21.43% | 14 | 4.4 | 590 | 10,073 | 20.0% | 22.2% | |
| 28.57% | 14 | 4.6 | 897 | 13,670 | 16.7% | 37.5% | |
| 38.46% | 13 | 1.0 | 691 | 12,328 | 33.3% | 42.9% | |
| 53.85% | 13 | 0.9 | 793 | 13,163 | 50.0% | 57.1% | |
| 38.46% | 13 | 2.2 | 606 | 9,513 | 33.3% | 50.0% | |
| 30.77% | 13 | 4.9 | 859 | 12,269 | 40.0% | 25.0% | |
| 53.85% | 13 | 4.3 | 748 | 10,894 | 62.5% | 40.0% | |
| 16.67% | 12 | 4.8 | 804 | 11,728 | 25.0% | 12.5% | |
| 72.73% | 11 | 4.3 | 793 | 11,725 | 62.5% | 100.0% | |
| 27.27% | 11 | 3.1 | 792 | 12,111 | 50.0% | 14.3% | |
| 54.55% | 11 | 0.8 | 599 | 11,124 | 75.0% | 42.9% | |
| 50.00% | 10 | 3.7 | 825 | 13,043 | 66.7% | 42.9% | |
| 20.00% | 10 | 1.8 | 630 | 9,686 | 16.7% | 25.0% | |
| 50.00% | 10 | 4.7 | 955 | 12,059 | 20.0% | 80.0% | |
| 60.00% | 10 | 5.0 | 799 | 11,788 | 33.3% | 71.4% | |
| 50.00% | 10 | 5.9 | 1,110 | 13,423 | 25.0% | 66.7% | |
| 40.00% | 10 | 6.0 | 945 | 12,694 | 50.0% | 33.3% | |
| 60.00% | 10 | 5.0 | 802 | 8,262 | 60.0% | 60.0% | |
| 55.56% | 9 | 5.0 | 796 | 12,028 | 66.7% | 50.0% | |
| 55.56% | 9 | 5.1 | 909 | 10,911 | 57.1% | 50.0% | |
| 44.44% | 9 | 5.4 | 908 | 11,481 | 33.3% | 50.0% | |
| 44.44% | 9 | 5.5 | 736 | 11,743 | 33.3% | 66.7% | |
| 62.50% | 8 | 5.2 | 917 | 13,959 | 0.0% | 71.4% | |
| 62.50% | 8 | 0.9 | 686 | 12,333 | 60.0% | 66.7% | |
| 50.00% | 8 | 5.7 | 1,065 | 10,839 | 50.0% | 50.0% | |
| 50.00% | 8 | 1.2 | 745 | 13,606 | 0.0% | 66.7% | |
| 62.50% | 8 | 2.8 | 828 | 11,415 | 100.0% | 50.0% | |
| 57.14% | 7 | 4.4 | 722 | 9,133 | 40.0% | 100.0% | |
| 57.14% | 7 | 1.3 | 884 | 11,114 | 25.0% | 100.0% | |
| 57.14% | 7 | 3.2 | 726 | 11,822 | 50.0% | 66.7% | |
| 85.71% | 7 | 2.2 | 758 | 12,017 | 75.0% | 100.0% | |
| 42.86% | 7 | 2.8 | 951 | 14,458 | 50.0% | 40.0% | |
| 42.86% | 7 | 4.3 | 917 | 14,113 | 0.0% | 50.0% | |
| 57.14% | 7 | 0.7 | 746 | 13,019 | 50.0% | 60.0% | |
| 42.86% | 7 | 1.7 | 779 | 12,464 | 50.0% | 40.0% | |
| 33.33% | 6 | 3.7 | 899 | 12,433 | 50.0% | 0.0% | |
| 50.00% | 6 | 4.4 | 774 | 12,326 | 50.0% | 50.0% | |
| 50.00% | 6 | 4.8 | 683 | 12,816 | 100.0% | 25.0% | |
| 50.00% | 6 | 0.8 | 793 | 12,589 | 66.7% | 33.3% | |
| 33.33% | 6 | 5.0 | 667 | 11,572 | 50.0% | 25.0% | |
| 33.33% | 6 | 0.9 | 750 | 11,658 | 0.0% | 50.0% | |
| 83.33% | 6 | 0.6 | 796 | 13,334 | 0.0% | 100.0% | |
| 100.00% | 5 | 2.4 | 902 | 12,862 | 100.0% | 100.0% | |
| 40.00% | 5 | 1.9 | 640 | 13,356 | 0.0% | 50.0% | |
| 40.00% | 5 | 4.1 | 710 | 12,557 | 66.7% | 0.0% | |
| 80.00% | 5 | 4.4 | 757 | 8,943 | 66.7% | 100.0% | |
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Pantheon vs Olaf - Frequently Asked Questions
How does Pantheon do against Olaf in League of Legends?
Olaf wins the Pantheon vs Olaf matchup with a 56.0% win rate compared to Pantheon's 44.0%, a 12.0 percentage point difference. This data is based on 25 recent ranked games in patch 26.7.
How does Pantheon do against Olaf in the early game?
In the early game, Olaf has the advantage against Pantheon with a 66.7% win rate versus 33.3%. Olaf players should look to press their lane advantage through aggressive trades and wave control during the first 15 minutes.
How does Pantheon do against Olaf in the late game?
In the late game, Pantheon takes over the Pantheon vs Olaf matchup with a 50.0% win rate compared to 50.0%. Pantheon scales better into team fights and objective contests after 25 minutes.
Who wins the Pantheon vs Olaf matchup?
Olaf wins the matchup against Pantheon with a 56.0% win rate in League of Legends patch 26.7. The 12.0 percentage point advantage means Olaf is significantly favored in this lane matchup based on 25 games analyzed.
What is the best Pantheon build against Olaf?
The best Pantheon build against Olaf includes Eclipse, Sundered Sky, Black Cleaver with Mercury's Treads. This build achieves a 66.7% win rate in the matchup. Check the matchup breakdown above for the full item path and build order.
What are the best Pantheon runes against Olaf?
The best Pantheon runes against Olaf use the Precision primary tree with Sorcery secondary. This rune setup achieves a 50.0% win rate in the Pantheon vs Olaf matchup. See the full rune breakdown in the matchup comparison above.
Does Pantheon counter Olaf?
No, Pantheon struggles against Olaf with only a 44.0% win rate. Olaf has the advantage in this matchup. Pantheon players should focus on safe farming and avoiding extended trades to minimize Olaf's lead.
How do I play Pantheon against Olaf?
When playing Pantheon against Olaf, play cautiously and avoid Olaf's power spikes. Focus on safe farming — you outscale Olaf in the late game. Use the matchup-specific build and runes above to optimize your chances.