KSplit | Strikeout Analytics

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KSplit | Strikeout Analytics

KSplit | Strikeout Analytics

@KSplitAnalytics

MLB strikeout distributions | Lineup-specific, split-driven modeling | Measuring strikeout risk, stability, and upside | Full Access below

Se unió Mart 2023
46 Siguiendo121 Seguidores
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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
KSplit is live. Most strikeout projections stop at a single number. That’s not how this market behaves. In my modeling, strikeouts are driven by matchup probability and plate appearance volume. The distribution is where the signal shows up. KSplit builds the full distribution from the game specific lineup. You can see how the tail forms, where volatility enters, and which ladders are actually reachable vs just priced to look attractive. The dashboard is fully interactive. Filter, sort, and isolate the exact components you care about depending on how you approach the market. Every projection is logged, with an extensive diagnostics page for consistent and clear model evaluation. Full access free for 2 weeks. ksplitanalytics.com
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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
@IIPatll Best feeling ever lol. I went to a Braves Cubs game last year. Had Sale ladder and he K’d like 7 of the first 9 he faced. Electric.
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Pat 🧘‍♂️⚾️
@KSplitAnalytics Yes!!! He's been relying on the knuckle curve which is great against lefties. Would like to see him use the change up more too. Had 8 Ks vs this Guards team last time he faced them (fun fact: I happened to be there and was on his over lol)
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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
I don’t know where I saw it, but somebody sent out a Cease/Luz ladder tweet and the analysis was “Cease has 27(?) Ks in 3 starts and Luzardo has historically dominated the Cubs” with the ladder starting at 8/8 with a couple thousand views/likes. Please for the love of God do not tail these plays if that’s the reasoning. BvP has 0 bearing, also Cubs lineup changes year to year, as to specific player tendencies. Cease’s first 3 starts of the year could not be more irrelevant to how he is going to perform TONIGHT against this specific Brewers lineup. Not saying I’m perfect, nobody ever is, but come on.
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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
Couple longshots from the board today LAA not confirmed; but love Gil as he has traditional K splits and will more than likely be getting 6+ strikeout-prone RHH Dustin May getting 8 LHH which plays heavily into his reverse K splits, we’ll see if he can finally settle in. Bradish and Ed both neutral split influence with means +1 from their main lines.
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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
Some early games today so here's how the splits lineup with confirmed lineups. One thing to note; if the pitcher has strong K% vs both LHH and RHH there are limitations as to how much a dampener can impact the split influence level. Boost Dustin May vs CLE Slight Boost Simeon Woods-Richardson vs BOS Neutral Ed R vs BAL Bradish vs ARI Slade vs STL Slight Damp Connelly Early vs MIN
KSplit | Strikeout Analytics@KSplitAnalytics

Split Influence Cheat Sheet 4/15/26 Lineups are projected. Labels update when confirmed lineups lock @ KSplitAnalytics.com This is one of the inputs that feeds each pitcher's full K distribution. When a meaningful difference exists between a pitcher's K% vs LHB and K% vs RHB, the actual handedness composition of the opposing lineup shifts the projection. More hitters on the advantaged side pushes the distribution right (Boost). More on the disadvantaged side compresses it (Damp). Today's (projected) slate leans damp-heavy. 21 of 28 pitchers carry an active split influence, and 16 of those are on the damp side. Only three pitchers (May, Kochanowicz, Gil) carry a full Boost. Quintana is the lone Max Damp, facing a Houston lineup stacked against his weaker split.

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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
Handful of median exact hits from yesterday (22.2% of projections) Yoshi 7 (o6.5) ✅ King 5 (u5.5) ✅ Springs 5 (o5.5) ❌ Colton Gordon 5 (o4.5)✅ Max Meyer 5 (o4.5) ✅ Robbie Ray 6 (u6.5) ✅ Best edge signal was consistent with the result in relation to the line on all except Springs.
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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
Split Influence Cheat Sheet 4/15/26 Lineups are projected. Labels update when confirmed lineups lock @ KSplitAnalytics.com This is one of the inputs that feeds each pitcher's full K distribution. When a meaningful difference exists between a pitcher's K% vs LHB and K% vs RHB, the actual handedness composition of the opposing lineup shifts the projection. More hitters on the advantaged side pushes the distribution right (Boost). More on the disadvantaged side compresses it (Damp). Today's (projected) slate leans damp-heavy. 21 of 28 pitchers carry an active split influence, and 16 of those are on the damp side. Only three pitchers (May, Kochanowicz, Gil) carry a full Boost. Quintana is the lone Max Damp, facing a Houston lineup stacked against his weaker split.
KSplit | Strikeout Analytics tweet media
KSplit | Strikeout Analytics@KSplitAnalytics

Split Influence Cheat Sheet 4/14/2025 All lineups are projected. Confirmed lineups update live on the dashboard at KSplitAnalytics.com Every pitcher strikes out lefties and righties at different rates. When that gap is meaningful, the composition of the lineup they're facing shifts the entire K distribution. Today, Cole Ragans (L) has 6+ hitters projected on his advantaged side (RHH) against Detroit. The distribution shifts toward more strikeouts. Mitch Keller faces the opposite problem against Washington, with 6+ hitters stacked on his disadvantaged side. His distribution compresses. Split Influence is one of several inputs that shape the full strikeout probability curve before the model prices an Over or Under. It's not a bet signal on its own. It's a structural modifier built into every projection on the board.

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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
@BallparkPal ~7.0 mean outputs on Cease Ohtani and Luz are consistent with what I got, would push back on May a bit as his reverse K% splits are going to bode well for him against the (projected) CLE lineup, lot of LHH, though 2 of those are Kwan and jRam
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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
4/14 Slate Recap 12-16, -5.93u. A left-tail day across the board. Before diving in, would like to reiterate that the goal here is to carve out a slice of the model that is consistently profitable and run with it... so far that has been the under signals. Unders 5-3, +1.02u. Couple notable hits Misiorowski u6.5 (actual 5) Ragans u6.5 (actual 1, wow) King u5.5 (actual 5) The distribution engine saw compressed ceilings on all three and the results confirmed it. Overs went 7-12, -6.95u. The model projected over on 20 of 28 profiles and the slate pushed back hard. Framber (actual 1), Singer (actual 1), and Sonny (actual 1), all collapsed well short of their lines. The highest-edge Overs on the board, McGreevy Over 2.5 (16.6% edge, actual 2), Bryan Woo Over 5.5 (16.5%, actual 3), and Lorenzen Over 3.5 (17.4%, actual 3), all lost. When every high-conviction Over misses, the slate is going to bleed. Nola Over 4.5 (13.2% edge, actual 5) and Lopez Over 4.5 (16.4%, actual 6) were the only high-edge Overs that came through. The rest of the green came from low-edge spots that quietly cleared. One day variance. The model builds full distributions and some days the mass lands left. Onto today.
KSplit | Strikeout Analytics@KSplitAnalytics

4/13 KSplit recap: 11-9 on the slate, +0.24u. Overs went 8-8, -1.35u. Volume was heavy with 16 Over plays but the juice worked against the margin. Filtering to 3% or greater best edge tightened it to 6-5, +0.43u. Kirby, Nelson, Kremer, Sanchez, Eovaldi, and Peterson all cleared. The losses came from high-edge plays where the model built aggressive tail distributions that never showed up. Unders went 3-1, +1.59u and carried the day. Kikuchi held NYY to 4 on a 5.5 line. ATL held Eury to 2 on a 5.5. Crochet's line was 7.5 and he recorded zero strikeouts and was probably tipping pitches? Insane game there. The only Under loss was Severino, who gave up 7 against a projection of 4; albeit being the highest edge of all the unders. Huge slate today with a lot of marquee names

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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
@EvilBellyLint I agree. Especially for somebody who is not super analytical it will streamline the betting process tenfold. I have a couple methods I’m tracking at the moment.
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EBL
EBL@EvilBellyLint·
@KSplitAnalytics "Once a significant amount of games have been logged I will be releasing a few methods on how to use the model most efficiently" I think this will be a huge help in getting people to try out the model
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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
Top 10 edges with projected lineups As you can see split influence level is not directly correlated with edge % as the market does also include this in their calculations; albeit I feel it is very undervalued. Once a significant amount of games have been logged I will be releasing a few methods on how to use the model most efficiently as well as their ROI per bet in addition (i.e. Unders with an edge greater than or equal to 3%, or Overs with a "boost" split influence level and X% edge threshold) The board automatically updates itself once confirmed lineups are released for the true analysis before first pitch. KSplitAnalytics.com
KSplit | Strikeout Analytics tweet media
KSplit | Strikeout Analytics@KSplitAnalytics

Split Influence Cheat Sheet 4/14/2025 All lineups are projected. Confirmed lineups update live on the dashboard at KSplitAnalytics.com Every pitcher strikes out lefties and righties at different rates. When that gap is meaningful, the composition of the lineup they're facing shifts the entire K distribution. Today, Cole Ragans (L) has 6+ hitters projected on his advantaged side (RHH) against Detroit. The distribution shifts toward more strikeouts. Mitch Keller faces the opposite problem against Washington, with 6+ hitters stacked on his disadvantaged side. His distribution compresses. Split Influence is one of several inputs that shape the full strikeout probability curve before the model prices an Over or Under. It's not a bet signal on its own. It's a structural modifier built into every projection on the board.

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Green Means Go!
Green Means Go!@GMGoBetting·
I liked Nolan McLean over 5.5ks today - but not at -130 (where Fanduel was..) or -122 (where DraftKings was) I went to Novig and did a make order at a price I liked: over 5.5 at -102. It was filled in under 10 minutes. Novig allows users to set their own prices on lines, and as long as another user take the other side (someone took McLean U5.5 at +102) then my make order is good to go. Not only does Novig typically have the best prices - they also allow users to attempt to get even better pricing across all markets with make orders. To help you visualize why -102 is significantly better than -122 and -130, I charted 10,000 simulations of a 1,000 bet sample at a 53% win rate. (I think McLean gets 6Ks 53% of the time vs LAD in this situation) So to me, -113 is fair. -122 and -130 are rip offs. And -102 gives me a small edge. TLDR - get @Novig and start doing make orders.
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KSplit | Strikeout Analytics retuiteado
j
j@Jferrie23·
Today's Pitching Matchups (Working on the suggested additions)
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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
Split Influence Cheat Sheet 4/14/2025 All lineups are projected. Confirmed lineups update live on the dashboard at KSplitAnalytics.com Every pitcher strikes out lefties and righties at different rates. When that gap is meaningful, the composition of the lineup they're facing shifts the entire K distribution. Today, Cole Ragans (L) has 6+ hitters projected on his advantaged side (RHH) against Detroit. The distribution shifts toward more strikeouts. Mitch Keller faces the opposite problem against Washington, with 6+ hitters stacked on his disadvantaged side. His distribution compresses. Split Influence is one of several inputs that shape the full strikeout probability curve before the model prices an Over or Under. It's not a bet signal on its own. It's a structural modifier built into every projection on the board.
KSplit | Strikeout Analytics tweet media
KSplit | Strikeout Analytics@KSplitAnalytics

Split Influence Board | 4/13/26 (projected lineups) Isolated how lineup handedness is shifting each pitcher’s strikeout distribution before first pitch. Pitchers not listed have a "neutral" split influence Boosts and damps aren’t "one size fits all". Skenes is a reverse split arm, Warren is traditional. Splits do not get weighted more or less based off if it is a traditional or reverse split, but reverse K splits goes against traditional thinking and is worth noting. Kirby, Skenes, Warren all getting a boost from matchup composition Cavalli, Crochet in slight boost environments Burrows, Nelson, Holmes dealing with dampened conditions This will be posted daily moving forward. Not the end all be all; but another layer into how the distribution actually forms.

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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
4/13 KSplit recap: 11-9 on the slate, +0.24u. Overs went 8-8, -1.35u. Volume was heavy with 16 Over plays but the juice worked against the margin. Filtering to 3% or greater best edge tightened it to 6-5, +0.43u. Kirby, Nelson, Kremer, Sanchez, Eovaldi, and Peterson all cleared. The losses came from high-edge plays where the model built aggressive tail distributions that never showed up. Unders went 3-1, +1.59u and carried the day. Kikuchi held NYY to 4 on a 5.5 line. ATL held Eury to 2 on a 5.5. Crochet's line was 7.5 and he recorded zero strikeouts and was probably tipping pitches? Insane game there. The only Under loss was Severino, who gave up 7 against a projection of 4; albeit being the highest edge of all the unders. Huge slate today with a lot of marquee names
KSplit | Strikeout Analytics@KSplitAnalytics

KSplit | 4/5–4/12 recap Betting to win 1u on negative odds, wagering 1u on positive odds Unders: 30-19, +9.70u, +19.8% ROI ✅ Overs: 56-65, -16.67u, -13.8% ROI ❌ Filter to unders with 4% or greater model edge: 21-8. +12.71u. +43.8% ROI Couple notable signals include Skubal vs MIN u7.5 Ks @ -137 ✅ Skubal vs MIA u7.5 Ks @ -138 ✅ Peralta vs ATH u6.5 @ -153 ✅ Eury Perez vs MIA u6.5 Ks @ -130✅ Great week for unders as that has held true since the beginning of the season. ksplitanalytics.com

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Kentown
Kentown@TheSharpBros·
These charts made me $14,000 yesterday. They saying $20,000 today 👀 Sorry in advance to FanDuel
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KSplit | Strikeout Analytics
KSplit | Strikeout Analytics@KSplitAnalytics·
Kirby finishes right on the median of 6 Ks Burrows struggled quite a bit Only a 1.00% edge on the over for Burrows so nothing concerning there with that not hitting Kirby comes through to cash the 8.43% edge on the over Onto tonight
KSplit | Strikeout Analytics@KSplitAnalytics

Lineups confirmed for both HOU and SEA Mike Burrows - Split influence level shifted to "neutral" from "slight damp" after confirmed lineup - o4.5 Ks @ -148; 1.00% edge - Mean of 5.09 Ks George Kirby - Split influence level remained "boost" after confirmed lineup - o5.5 Ks @ -122; 8.43% edge - Mean of 6.32 Ks KSplitanalytics.com

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