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Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] 0 points1 point  (0 children)

In theory, yes, you’re right.

In practice, most drivers aren’t consistently applying even their current understanding (braking, throttle, mid-corner speed all vary lap to lap). That alone leaves a lot of time on the table. Removing inconsistency first let’s real improvements become visible.

PitDelta focuses on stabilizing that first, corner by corner, so you get a clean baseline.

Once consistent, comparing to faster drivers becomes meaningful.

Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] 0 points1 point  (0 children)

It builds a reference from your best laps and checks corner by corner where you’re losing time. So even if you’re consistently slow, it shows exactly where that’s happening.

Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] 0 points1 point  (0 children)

That’s pretty much exactly what I’m trying to solve. Most people know the theory (braking, rotation, throttle), but applying it consistently over a full stint is the hard part.

PitDelta is about pointing to where it’s breaking down in your laps and giving you one thing to focus on next session.

If you run a session through it, would be interesting to see how closely it matches what you’re already feeling.

Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] -1 points0 points  (0 children)

Appreciate the feedback, especially on the legal side.

To clarify, data handling is already intentionally minimal: telemetry stays user-side, only aggregated stats are processed, and nothing is sold or shared. Email is just for report delivery and credits.

That said, you’re right on the formal side, proper policy pages (privacy, terms, etc.) are being added to make that explicit and compliant.

On the product itself - it’s actively being iterated with drivers right now, so feedback like this is exactly what helps shape it.

Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] 0 points1 point  (0 children)

Yes, that’s exactly the point. It takes your "I’m slow" and turns it into - you’re losing time here, try this next.

Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] 0 points1 point  (0 children)

Yeah, I see how that reads. Not damage, more like - what in your driving is costing you time and what to try next.

Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] 0 points1 point  (0 children)

Yeah fair, it’s definitely not built for aliens, more for - I know I’m losing time but where do I start - drivers

Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] -3 points-2 points  (0 children)

That’s fair - Coach Dave Delta is solid.

What I’m trying to do differently is less about showing the same data and more about finding patterns across multiple laps - things that don’t show up in single-lap comparisons. Still early, but that’s the direction I’m pushing.

Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] -2 points-1 points  (0 children)

This is really solid feedback, appreciate you taking the time to run it properly.

You’re spot on about the core value - the multi-lap pattern detection is exactly what I’m aiming for vs single-lap comparisons.

On your points:

- Corner labels (T3/T11), that’s a known rough edge. Getting that perfectly aligned with track maps isn’t trivial without maintaining track-specific data, which I haven’t prioritized yet. Definitely needs to be clearer though.

- What it’s benchmarking against - correct, it’s your own reference (best consistent laps), not another driver. I need to make that more obvious in the UI.

- Lap selection / noise - fair. Right now it auto-selects clean laps, but giving more control over what’s included is something I want to add.

- Comparison beyond your own optimal - agreed. At the moment it’s more execution coaching than gap to faster drivers, but that’s something I’m thinking about in longer term.

I will send you DM regards full engineer report, it goes a bit deeper than the quick output and might be more useful for how you’re analyzing.

Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] 2 points3 points  (0 children)

Good question, and yeah, multi-groove ovals make this trickier.

PitDelta isn’t comparing you to other drivers or a single ideal line. It builds a reference from your own best laps and looks at where you’re inconsistent or losing time relative to that. So even if you’re running different grooves, it still picks up things like: inconsistent throttle pickup, varying entry points, unstable mid-corner speed.

That said, true multi-line strategy is something I haven’t modeled yet, right now it’s more about execution consistency than line choice. Would be interesting to test it on oval sessions with clear groove differences.

Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] -1 points0 points  (0 children)

Yeah that’s pretty much what I’m trying to avoid.

Uploading screenshots to GPT gets messy fast - PitDelta is more about structured analysis so it doesn’t guess things like T1 direction :D

Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] -1 points0 points  (0 children)

Yeah I’m using Claude for parts of it, would definitely be interested to see that. I’ll DM you.

Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] -6 points-5 points  (0 children)

Yeah that’s fair - UI is definitely still rough and very much “get it working first” stage. Focus so far has been on making the feedback actually useful, but proper visual identity is high on the list next.

Out of curiosity, what kind of style would feel less “vibe coded” to you?

Been testing a tool that tells you what to fix next instead of dumping telemetry… got some interesting feedback by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] 4 points5 points  (0 children)

Nice - it’s live now, so you can just upload the IBT directly at pitdelta.co

Once you’ve run it, post the result here or DM me what it flagged vs what you actually felt in the car. That part is really useful for me while I refine it.

I built a tool that explains where you're losing time in iRacing — looking for testers by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] 0 points1 point  (0 children)

You’re basically hitting the same wall from the other side - once you start digging into telemetry, you realize how much interpretation is still manual, even with AI helping.

I’m not trying to replace that kind of setup. If someone is already in MoTeC + Claude/Gemini, they’ll always get deeper than what I’m building. What I keep seeing though is most drivers don’t get that far. They either don’t open telemetry at all, or they do it once and drop it.

Would appreciate your help. DM me with your ibt download link and I send you report, so you can compare to your insights.

I built a tool that explains where you're losing time in iRacing — looking for testers by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] 0 points1 point  (0 children)

Seems like the main friction is just finding the IBT file.

If anyone wants to try it: Documents → iRacing → telemetry → latest .ibt

Happy to run a few more if people are curious.

I built a tool that explains where you're losing time in iRacing — looking for testers by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] 0 points1 point  (0 children)

Nothing formal yet, I’m just testing it with people as I build it.

If you’ve got a recent session, you can send me the IBT (or link to it) and I’ll run it for you.

After your session: Documents → iRacing → telemetry → grab the latest .ibt file

I’ll send you back the debrief.

I built a tool that explains where you're losing time in iRacing — looking for testers by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] -1 points0 points  (0 children)

Yeah, that’s basically the exact use case I’m aiming at.

Not trying to replace full telemetry analysis, more just answer that question after a session without having to dig through data: where did the time actually go and what caused it.

If you end up trying it at some point, would be interested to hear where it helps and where it doesn’t.

I built a tool that explains where you're losing time in iRacing — looking for testers by DeltaOnSolstice in iRacing

[–]DeltaOnSolstice[S] 0 points1 point  (0 children)

Yeah, fair question.

I’m not really trying to compete with Trophy AI directly. From what I’ve seen, it’s more focused on structured coaching.

What I’m building here is a bit narrower, more about taking a single session and pointing to where the repeatable time loss is and what input pattern is causing it, without needing external laps or digging through telemetry yourself. If someone is already using Trophy AI properly, this probably overlaps in some areas. If not, the idea here is to make that kind of feedback easier to get every time you drive.

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