Last updated: October 2026
This October 2026 ranking of the best LoL tipsters and prediction sites for League of Legends esports asks a simple question: who actually beat the market? The leader, individual tipster Kiril Batulin, posted an adjusted ROI of +0.9% (raw +2.7%), the only positive return among all 14 ranked sources. Regional playoffs set the international field in September, and those matches are now part of the record.
Always backing the favorite returned -4.2% over the full window, while the median ranked source managed -7.4%, and only 1 of the 14 ranked sources beat that baseline by at least one point. Losing less than the favorite is not the same as making a profit.
Best LoL Tipsters by ROI: Full Ranking
| Rank | Tipster | Source | Type | Picks | Win rate | Avg odds | ROI | Adj. ROI | vs. favorite | On favorite | Change |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Kiril Batulin | EGamersWorld | Tipster | 94 | 70.2% | 1.56 | +2.7% | +0.9% | +6.9 | 83.0% | — |
| 2 | Mark Prezelj | EsportsBet | Tipster | 95 | 60.0% | 1.84 | −3.5% | −1.1% | +0.7 | 60.0% | — |
| 3 | Deffy | bo3.gg | Tipster | 84 | 54.8% | 1.88 | −5.8% | −1.7% | −1.6 | 65.5% | — |
| 4 | Thorin | X (Twitter), YouTube | Tipster | 83 | 62.7% | 1.58 | −10.0% | −2.9% | −5.8 | 84.3% | — |
| 5 | SportsGambler | SportsGambler | Prediction site | 974 | 64.5% | 1.79 | −4.1% | −3.4% | +0.1 | 73.8% | — |
| 6 | Kalshi | Kalshi | Prediction market | 1,041 | 70.6% | 1.43 | −4.5% | −3.8% | −0.3 | 94.4% | — |
| 7 | Tit Krajnik | FreeTips | Tipster | 76 | 53.9% | 1.70 | −16.9% | −4.7% | −12.7 | 65.8% | — |
| 8 | 2ez.bet Community Voting | 2ez.bet | Community vote | 723 | 68.6% | 1.40 | −7.0% | −5.5% | −2.8 | 96.0% | — |
| 9 | OP.GG Community Voting | OP.GG | Community vote | 100 | 59.0% | 1.47 | −17.1% | −5.7% | −12.9 | 82.0% | — |
| 10 | bo3.gg | bo3.gg | Prediction site | 2,052 | 61.0% | 1.97 | −6.5% | −5.9% | −2.3 | 70.1% | — |
| 11 | EGWxxxBOT | EGamersWorld | Algorithm | 647 | 67.5% | 1.43 | −9.0% | −6.9% | −4.8 | 92.3% | — |
| 12 | Strafe Community Voting | Strafe | Community vote | 2,236 | 62.5% | 1.86 | −7.8% | −7.2% | −3.6 | 73.5% | — |
| 13 | Sofascore Community Voting | Sofascore | Community vote | 2,282 | 66.6% | 1.57 | −7.9% | −7.3% | −3.7 | 85.9% | — |
| 14 | Feedinco | Feedinco | Prediction site | 1,630 | 57.1% | 2.19 | −10.8% | −9.6% | −6.6 | 64.7% | — |
Baseline over the same period: always backing the favorite won 71.7% of 2,533 matches for −4.2% ROI. Median ROI across all 14 ranked sources: −7.4%. "vs. favorite" is a source’s ROI minus that baseline, in percentage points. Avg odds covers all picks, not just winners.
Ranked by Adj. ROI: raw ROI × picks ÷ (picks + 200), which pulls small samples toward zero so a short lucky run cannot top the table. Over a few hundred picks, ROI gaps of a few points are mostly variance, so treat neighboring ranks as roughly equal.
Top 3 LoL Tipsters for October 2026
#1 Kiril Batulin – Tipster
Adj. ROI +0.9% · ROI +2.7% · +6.9 pts vs. favorite · 94 picks · 66-28 · win rate 70.2% · avg odds 1.56
Kiril Batulin is the leader this month, with an adjusted ROI of +0.9% (raw +2.7%), 6.9 points above the favorite baseline. Across 94 picks they went 66-28 (70.2%) at average odds of 1.56, backing favorites 83.0% of the time. The sample is still modest, but the margin over the baseline is the notable part of this record.
#2 Mark Prezelj – Tipster
Adj. ROI −1.1% · ROI −3.5% · +0.7 pts vs. favorite · 95 picks · 57-38 · win rate 60.0% · avg odds 1.84
Mark Prezelj ranks second with an adjusted ROI of -1.1% (raw -3.5%), just 0.7 points above the favorite baseline across 95 picks. A 60.0% win rate at average odds of 1.84, with favorites backed only 60.0% of the time, is a more balanced approach than Batulin’s, but it still left bettors following every pick with a loss.
#3 Deffy – Tipster
Adj. ROI −1.7% · ROI −5.8% · −1.6 pts vs. favorite · 84 picks · 46-38 · win rate 54.8% · avg odds 1.88
Deffy rounds out the top three with an adjusted ROI of -1.7% (raw -5.8%), 1.6 points below the favorite baseline. A 54.8% win rate at average odds of 1.88, with favorites backed 65.5% of the time, earns third place only because the small 84-pick sample is pulled toward zero; on raw ROI Deffy ranks fifth, with a bigger loss than simply backing favorites.
Who Beat the Favorite?
Always backing the favorite returned −4.2% over the last 12 months (71.7% win rate across 2,533 matches). We count a source as beating it only if its ROI is at least 1 point higher. Only 1 of the 14 ranked sources managed that:
Kiril Batulin – tipster (#1)
ROI +2.7% from 94 picks, +6.9 pts vs. the favorite baseline; backed the favorite 83.0% of the time at average odds of 1.56.
How We Rank LoL Tipsters
- Source. Every figure on this page is calculated by tips.gg. We track every League of Legends pick from 150 tipsters and sites (individual tipsters, prediction sites, algorithms, community votes and prediction markets) across 20 platforms and settle each one ourselves; no self-reported records are used.
- Scope. All LoL esports tournaments we cover, from the LCK, LPL and LEC to international events and regional leagues; every pick is scored as a match-winner bet on the team the source backed, even when the original tip was a handicap or exact-score bet; the last 12 months to Sep 30, 2026.
- Minimum sample. At least 50 graded picks in the window, and a pick within 45 days of the last LoL match.
- Metric. ROI at average market odds across bookmakers for a 1-unit stake: (profit ÷ picks) × 100. The table is ordered by sample-adjusted ROI (Adj. ROI = ROI × picks ÷ (picks + 200)). We also compare every source with the simplest strategy there is: always backing the favorite (−4.2% ROI). Avg odds is the average price across all of a source’s picks, winning and losing. Win rate × average odds is not the same as ROI: favorites win more often at shorter prices, so winning picks usually carry lower odds than losing ones.
- Ties and updates. Larger samples win ties. The ranking refreshes monthly.
Tipsters, Sites, Bots and Community Votes: Who’s Who
The table mixes several kinds of sources, and the Type column tells you which is which. Tipsters are individual analysts posting their own LoL picks. Prediction sites publish picks from an editorial team or a model. Algorithms are automated bots. Community votes are the majority pick of a site’s users, and a prediction market reflects the side its traders price as more likely. We rank them on one scale because the question for a bettor is the same: did following these picks make money?
Read this ranking as a filter, not a forecast. Over a few hundred LoL picks, ROI gaps of a few points are mostly noise, a high win rate usually just means backing favorites, and beating the always-favorite baseline (−4.2%) is the real test. For match-by-match analysis, see our LoL predictions for today. The table refreshes monthly.
LoL Tipster FAQ
Who are the best LoL tipsters right now?
Over the last 12 months, Kiril Batulin tops our sample-adjusted ranking with an adjusted ROI of +0.9% (raw +2.7%) from 94 League of Legends picks. Measured against the always-favorite baseline of −4.2%, only 1 of the 14 ranked sources did at least one point better.
Can you make money betting on League of Legends?
It is possible but uncommon. Of the 14 sources we rank, 1 finished the last 12 months in profit, and the median ROI was −7.4%. Even always backing the favorite returned −4.2% once bookmaker margins were priced in.
How is a tipster’s ROI calculated?
ROI (return on investment) is total profit divided by the number of picks, times 100, assuming a flat 1-unit stake on each pick. A winning pick at odds of 1.80 adds 0.80 units; a loss costs 1 unit. We use average market odds, so the figure reflects the price a typical bettor could get.
Why do most LoL tipsters lose money?
Bookmakers build a margin into every LoL price, and most picks follow the favorite: the median source in our ranking backed it 77.9% of the time. Favorites won 71.7% of matches, yet always backing them returned −4.2%. To profit, a tipster has to find prices that are wrong, not just pick winners.
How often is this LoL tipster ranking updated?
Monthly. Each update re-runs the full 12-month window, so new picks come in and the oldest month drops out. We calculate every number ourselves. tips.gg tracks each League of Legends pick from 150 tipsters, prediction sites, algorithms, community votes and prediction markets across 20 platforms, settles it against the final result and the average market odds, and works out ROI on a flat 1-unit stake. No self-reported records or screenshots are used. We rank by sample-adjusted ROI (ROI × picks ÷ (picks + 200)), require at least 50 graded picks in the last 12 months plus recent activity, and refresh the table monthly.
Bet Responsibly
Betting involves risk. This page is for information only, and past performance does not guarantee future results. You must be of legal age to bet: 21+ in most US states and 18+ in the UK; check your local laws. If gambling stops being fun, get help: 1-800-GAMBLER (US) or BeGambleAware.org (UK).