Edit 7 April 2025 : this blog post statistical validation part has been removed, because part of the validation data was in the training set. Corrected version coming soon.
When it comes to League of Legends draft analysis tools, not all are created equal. In this detailed comparison, we'll examine how LoLDraftAI stacks up against DraftGap, another popular draft analysis tool.
DraftGap shortcomings
In their own FAQ section, DraftGap explicitly acknowledges their limitations:
Does DraftGap have any shortcomings? DraftGap is not perfect, and there are several things to keep in mind. The overall team comp identity is not taken into account. The synergy of duos within a team are used in the calculations, but the tool does not know about team comp identity like 'engage' or 'poke'. Damage composition is also not used in the calculation (but it is shown, above the team winrate), so you need to keep this in mind on your own. These shortcomings result from the fact that there is not enough data to make a perfect prediction. And we do not want to incorporate opinions like 'malphite is an engage champion' into the tool, as using just data is the most objective way to make a decision.
As we'll demonstrate in this article, LoLDraftAI has overcome these limitations through its advanced machine learning approach, which can identify complex team compositions and their interactions. We will see some examples of when the statistical approach of DraftGap falls short.
DraftGap shortcoming example: full AP draft
Because DraftGap only uses champion pair statistics, it is totally unaware of the draft as a whole. For this reason, it will not understand when a draft only has AP Damage. This can be showcased by creating a full AP Draft with one team having the following champions from top to bot:
- Top: Vladimir
- Jungle: Fiddlesticks
- Middle: Kennen
- Bottom: Heimerdinger
- Support: Taric
When inputting this draft into DraftGap, it predicts a 62.62% win chance. LoLDraftAI on the other hand, understands that this is a full AP Draft, and predicts a win chance of 40.4%.
DraftGap prediction:
LoLDraftAI prediction:
Importantly, this not only impacts analysis but also champion suggestions. For example, against this full AP Draft, LoLDraftAI suggests Ornn as the best toplane champion. DraftGap, on the other hand, thinks that the team with Ornn top against a full AP Draft only has 40% win chance. Obviously Ornn would just be unkillable against a full AP Draft, this is a glaring example of how DraftGap's statistical approach is limited.
Shortcomings conclusion
This full AP draft just serves as a simple illustration, but it also will impact more nuanced situations. DraftGap will not understand:
- Blue vs Red side differences
- When a team has only one or multiple carries
- When a team has no CC
- When a team has low total damage
- When a team only has late game champions
When you add up all these small subtleties, this just makes DraftGap not a very accurate tool, and this is what we will see in the next section that compares the accuracy of DraftGap to LoLDraftAI.
Statistical accuracy comparison
Edit 7 April 2025 : this blog post statistical validation part has been removed, because part of the validation data was in the training set. Corrected version coming soon.
Try LoLDraftAI Today
Experience the advanced draft analysis capabilities of LoLDraftAI yourself:
- Use the web version for analysis
- Download the desktop app for live draft tracking
Appendix A: Dataset Verification
The results for DraftGap were obtained by using their source code available here: https://github.com/vigovlugt/draftgap. All results can be manually verified by using their websites and the match id. Example verification for the first match of the dataset: Match results: https://www.leagueofgraphs.com/match/EUW/7298239127
DraftGap prediction:
LoLDraftAI prediction:
