u/nrichardson5

r/sportsbetting r/u_nrichardson5 r/Sabermetrics r/sportsbettingzone r/test r/MLB_Bets

8/16 results and writeup

4-2 on legs. Ticket B went 3-for-3 at +500. Game totals swept 3-0.

+7.56u on the night — biggest result of this run so far.

50-43 on legs overall. +16.49u through ten days.

Date	Legs	Net
8/7	7-8	+6.18u
8/8	5-5	-7.10u
8/9	6-2	+8.58u
8/10	6-6	+2.72u
8/11	3-6	-1.83u
8/12	5-5	-4.33u
8/13	3-3	+0.88u
8/14	6-4	+3.85u
8/15	5-2	-0.02u
8/16	4-2	+7.56u
Total	50-43	+16.49u

Eleven units total — six individual legs, two tickets and three game totals, one unit each.

Segment	Record	Net
Individual legs	4-2	+0.84u
Tickets	1-1	+4.00u
Game totals	3-0	+2.72u
Night		+7.56u

The board, graded

Pitcher	Pick	Odds	Ticket	Proj	Actual	Error	Result
Logan Henderson	BB U1.5	-140	B	0.89	1 BB — 7.0 IP, 93 P	+0.11	✅
Lake Bachar	BB U1.5	-260	A	0.46	1 BB — 3.0 IP, 52 P	+0.54	✅
Michael Soroka	ER U2.5	-110	B	1.45	2 ER — 5.2 IP, 80 P	+0.55	✅
Drew Anderson	K U4.5	-135	A	3.37	5 K — 5.0 IP, 74 P	+1.63	❌
Hunter Dobbins	K O3.5	-120	B	4.78	7 K — 5.0 IP, 96 P	+2.22	✅
Blade Tidwell	ER U2.5	-160	A	0.86	6 ER — 4.1 IP, 5 BB	+5.14	❌

Tickets

Ticket	Legs	Odds	Model Est.	Implied Est.	Result	Net
A	Tidwell, Bachar, Anderson	+292	80.1%	25.5%	1-for-3	-1.00u
B	Soroka, Henderson, Dobbins	+500	58.4%	16.7%	3-for-3	+5.00u

Game totals — 3-0

Matchup	Line	Pick	Odds	Result
Rangers at Athletics	10.5	UNDER	-108	Rangers 2, Athletics 5 — 7 ✅
Orioles at Rays	7.5	OVER	-110	Orioles 10, Rays 2 — 12 ✅
Royals at Angels	9.5	UNDER	-113	Royals 3, Angels 0 — 3 ✅

Rangers at Athletics was the largest difference my totals model had produced so far: 1.48 runs against a listed 10.5.

The game finished with 7 runs.

That size of difference hadn't been tested yet, so it was encouraging to see it finish comfortably below the number.

Game totals are now:

9-4

That portion of the model has quietly been one of the better-performing pieces so far.

Every projection missed in the same direction

Look at the Error column.

Six legs.

Six projections.

And all six actual results finished above the projection:

+0.11
+0.54
+0.55
+1.63
+2.22
+5.14

Average error:

+1.70

Six-for-six in one direction can happen by chance, so I'm not calling this a model bias after one night.

But it is worth flagging.

If the model is systematically projecting too low, that would make unders look stronger than they really are and overs look weaker.

Four of the six legs were unders.

They still went 3-1, which is exactly the kind of result that can hide a calibration problem.

If the same pattern shows up again, I'll start digging into whether an adjustment is needed.

Blade Tidwell U2.5 ER — the 97% leg allowed six

Projection:

0.86 ER

Actual:

6 ER

Error:

5.14 runs

This was the highest model probability on yesterday's board at:

97%

He had also stayed below 2.5 earned runs in:

5 of his last 5

and

10 of his last 10

The important part is that I had already noted why the projection was so low.

The 0.86 number wasn't necessarily saying Tidwell was going to dominate.

It was partly saying he probably wouldn't pitch deep enough to allow much damage.

That part was actually close.

He only went:

4.1 innings

But he still allowed six earned runs because he walked:

5 hitters

So the failure wasn't workload.

It was a complete command collapse.

He entered with:

69% first-pitch strikes

27% behind in the count

Then walked five in 4.1 innings.

This is now the second straight night where an earned run projection missed by more than five runs.

Matthew Boyd: projected 1.88, allowed 7.

Blade Tidwell: projected 0.86, allowed 6.

The change I made yesterday — mixing different prop types together — limited the damage.

Ticket B wasn't affected by Tidwell and finished 3-for-3.

Ticket A still lost because Drew Anderson also missed.

Mixing different stat categories reduces concentration.

It doesn't rescue a ticket when two separate legs lose.

Drew Anderson U4.5 K

Projection:

3.37 K

Actual:

5 K

He entered having stayed below 4.5 in:

5 of 5

10 of 10

And his previous Detroit results averaged only:

1.33 strikeouts per game

His command numbers were also right around league average.

Nothing obvious in the pregame data pointed toward five strikeouts.

He went:

5 innings

74 pitches

and missed more bats than the recent numbers suggested.

Ticket B — three stat types, three wins

Michael Soroka U2.5 ER

Projection:

1.45

Actual:

2 ER in 5.2 innings on 80 pitches

Very close to the projection.

Logan Henderson U1.5 walks

Projection:

0.89

Actual:

1 walk in 7 innings

This one had a real concern coming in.

He walked 3 Dodgers in their previous meeting.

That was the only prior matchup result and it went directly against the under.

I still used Henderson because his broader command numbers were strong:

67% first-pitch strikes

25% behind in the count

The broader command data won out over the single previous meeting.

Seven innings.

One walk.

Hunter Dobbins O3.5 K

Projection:

4.78

Actual:

7 K

He had finished above 3.5 strikeouts in every start in the sample:

9 of 9

He made it:

10 of 10

This was also a good example of why I didn't automatically treat his below-average command numbers as negative for a strikeout over.

He worked deep counts and still generated seven strikeouts in five innings.

What I'd take from the night

The structural change helped, with an important caveat.

Ticket B had:

One earned run leg
One walks leg
One strikeout leg

Three different stat types with different ways to fail.

It went 3-for-3 at +500.

Ticket A had the same structure and still went 1-for-3 because two independent legs lost.

So mixing stat types helps reduce concentration.

It is not protection against simply getting multiple legs wrong.

The totals model also deserves attention.

Three games qualified.

All three finished on the expected side.

And the biggest difference of the night — Rangers at Athletics, 1.48 runs below the listed total — finished at only 7 runs against a line of 10.5.

I had nothing on totals the previous two nights because no game reached my 0.75-run threshold.

That's exactly how I want that portion to work: nothing forced when the numbers are close.

The thing I'm watching tonight

Every single projection yesterday finished low.

One night isn't enough to call that a trend.

But it's the most important model-level thing I saw despite the +7.56u result.

If it happens again, I'll start checking whether there is a systematic downward bias in the projections rather than dismissing it as random variation.

A winning night shouldn't stop me from looking for something that's wrong.

Overall results

Date	Legs	Net
8/7	7-8	+6.18u
8/8	5-5	-7.10u
8/9	6-2	+8.58u
8/10	6-6	+2.72u
8/11	3-6	-1.83u
8/12	5-5	-4.33u
8/13	3-3	+0.88u
8/14	6-4	+3.85u
8/15	5-2	-0.02u
8/16	4-2	+7.56u
Total	50-43	+16.49u

50-43 on individual legs.

+16.49u overall.

Game totals: 9-4.

Ten days is still a very small sample.

The +7.56u night is great, but the more useful takeaway may be that all six projections missed in the same direction.

That's what I'm watching next.

Results tomorrow — wins and losses both.

reddit.com

u/nrichardson5 — 3 days ago

▲ 7 r/sportsbetting+1 crossposts

8/16 picks, parlays and writeup

46-41 on legs. +8.93u through nine days.

Today's slate: 6 legs, 2 tickets, 3 game totals.

Fifteen-game slate.

Date	Legs	Net
8/7	7-8	+6.18u
8/8	5-5	-7.10u
8/9	6-2	+8.58u
8/10	6-6	+2.72u
8/11	3-6	-1.83u
8/12	5-5	-4.33u
8/13	3-3	+0.88u
8/14	6-4	+3.85u
8/15	5-2	-0.02u
Total	46-41	+8.93u

One rule changed after last night

I went 5-2 on individual legs — my best record of the run — and still finished essentially flat because both tickets missed by one leg.

Four of my seven legs were earned run unders, and I put three of them together on one ticket.

Two nights earlier I had already written that earned runs were producing some of the widest projection errors.

Last night showed it inside one slate:

Ryan Gusto
Projected: 1.88
Actual: 2

Eduardo Rodriguez
Projected: 2.35
Actual: 2

Troy Melton
Projected: 0.78
Actual: 3

Matthew Boyd
Projected: 1.88
Actual: 7

Two were nearly exact.

Two missed by more than seven runs combined.

So I'm changing the structure:

No ticket will contain three legs from the same prop type.

Tonight, each ticket contains:

One earned run leg
One walks leg
One strikeout leg

Three different statistical categories with different ways to fail.

One ugly inning shouldn't be able to wipe out an entire ticket built from the same stat.

The board

Pitcher	Pick	Odds	Proj	Prob	L5	L10	FPS	Behind	PPO	Game
Blade Tidwell	ER U2.5	-160	0.86	97%	5/5	10/10	69%	27%	5.91	COL at SF
Lake Bachar	BB U1.5	-260	0.46	96%	5/5	10/10	65%	40%	4.88	BOS at PIT
Drew Anderson	K U4.5	-135	3.37	86%	5/5	10/10	61%	34%	5.17	CWS at DET
Hunter Dobbins	K O3.5	-120	4.78	86%	5/5	9/9	58%	37%	5.45	STL at CHC
Michael Soroka	ER U2.5	-110	1.45	86%	4/5	9/10	65%	29%	4.99	ARI at ATL
Logan Henderson	BB U1.5	-140	0.89	79%	4/5	8/10	67%	25%	5.00	MIL at LAD

FPS = first-pitch strike rate over the last five. League average is about 61%.

Behind = share of pitches ending with the pitcher behind in the count over the last five. League average is about 34%.

PPO = pitches per out over the last five.

Six legs.

Six different games.

Three prop types.

Two of each.

Ticket A — One of each, +292

Model estimate: 80.1%
Implied estimate: 25.5%

Blade Tidwell U2.5 ER (-160)
Lake Bachar U1.5 walks (-260)
Drew Anderson U4.5 K (-135)

Ticket B — One of each, +500

Model estimate: 58.4%
Implied estimate: 16.7%

Michael Soroka U2.5 ER (-110)
Logan Henderson U1.5 walks (-140)
Hunter Dobbins O3.5 K (-120)

About those probability estimates

An 80% estimate on a three-leg ticket is not something I'm comfortable treating literally.

It comes from individual estimates of:

97%

96%

86%

Numbers that extreme can sometimes be driven by an expectation of limited workload rather than a dominant pitching performance.

So I'm treating these percentages the same way I've been treating the other very high estimates:

The direction is more useful than the exact percentage.

The magnitude is probably optimistic.

Blade Tidwell U2.5 ER

Highest probability on the board:

97%

Projection:

0.86 ER

Line:

U2.5

Lake Bachar U1.5 walks

Projection:

0.46 walks

Drew Anderson U4.5 K

Projection:

3.37 K

Line:

U4.5

Hunter Dobbins O3.5 K

Projection:

4.78 K

Michael Soroka U2.5 ER

Projection:

1.45 ER

Logan Henderson U1.5 walks

Projection:

0.89 walks

What I left out

Sean Burke U2.5 ER — 92%

Strong number, but Burke is the opposing starter to Drew Anderson.

I don't want two separate legs tied to the same game.

Edward Cabrera O1.5 ER — 87%

Same issue.

Cabrera is the opposing starter to Hunter Dobbins.

One position per game.

Blade Tidwell U1.5 walks — 93%

Second prop on a pitcher already being used.

One position per starter.

Cody Bradford U5.5 hits — 81%

There are only two prior starts in the data.

Both finished below this number, but two starts are not enough for me to put much weight on the trend.

I left this one out tonight because the sample is too small.

Game totals

Three games qualify tonight after two straight nights with none.

Matchup	Line	Pick	Odds	Derived	Difference
Rangers at Athletics	10.5	UNDER	-108	9.02	-1.48
Orioles at Rays	7.5	OVER	-110	8.33	+0.83
Royals at Angels	9.5	UNDER	-113	8.72	-0.78

I use a game total when my derived number differs from the listed line by at least:

0.75 runs

Rangers at Athletics U10.5

Derived:

9.02

Line:

10.5

Difference:

1.48 runs

That's one of the largest gaps I've seen since I started keeping these results.

The previous high was 1.68 runs on 8/13, and that game finished on the expected side.

Across fourteen games with usable numbers tonight:

Average residual: -0.207

Standard deviation: 0.519

Current game-total record:

6-4

Model improvements I'm working on

I'm also working on the next version of the hits, strikeout and outs projections.

The current models already use a wide mix of inputs.

That includes workload, command, recent performance, opponent tendencies, matchup history, pitch-level information and Statcast data — including expected slugging.

So this isn't about adding xSLG for the first time.

It is already part of the models.

What I'm trying to improve is how contact quality is estimated for the specific pitcher and lineup combination on that day.

I'm developing a separate modeled expected-slugging measure that can be used alongside the existing Statcast xSLG inputs.

The idea is to take information already being used — hitter quality, pitcher quality, handedness, pitch mix, pitch usage, contact tendencies and other matchup inputs — and generate a more matchup-specific expectation for the quality of contact that lineup should produce.

Then I can test whether that gives the models useful information beyond the existing Statcast expected-slugging data and the other inputs already included.

For hits allowed, the goal is a better estimate of whether expected contact should turn into baserunners rather than leaning too heavily on recent hit totals.

For strikeouts, it could help identify lineups that may handle a pitcher's specific arsenal better or worse than their overall strikeout numbers suggest.

For outs, it provides another way to estimate how much traffic and damage a starter may have to work through before pitch count becomes the limiting factor.

The important part is that this is an improvement to an already multi-feature model, not a replacement for what is there now.

Statcast expected slugging is already included.

I'm trying to determine whether a separately generated, matchup-specific expected-slugging signal improves the hits, strikeout and outs projections beyond what the current models already know.

I'm testing it first. If the numbers don't improve, it doesn't get added.

Notes

Six legs across a fifteen-game slate.

Each leg comes from a different game.

The two tickets each contain three different prop types. That's the main structural change from last night.

Nine days is still far too small a sample to draw firm conclusions.

Several other numbers looked interesting at first.

I narrowed it to six after reviewing the supporting data and the arguments against each one.

Six legs tonight.

Overall results

Date	Legs	Net
8/7	7-8	+6.18u
8/8	5-5	-7.10u
8/9	6-2	+8.58u
8/10	6-6	+2.72u
8/11	3-6	-1.83u
8/12	5-5	-4.33u
8/13	3-3	+0.88u
8/14	6-4	+3.85u
8/15	5-2	-0.02u
Total	46-41	+8.93u

46-41 on individual legs.

+8.93u overall.

Game totals: 6-4.

Nine days is still a very small sample.

Baseball has enormous night-to-night variance. The useful part is laying out the workload, recent results, command numbers and opponent history behind each leg, then coming back afterward and seeing what actually mattered.

Results tomorrow — wins and losses both.

reddit.com

u/nrichardson5 — 4 days ago

▲ 5 r/sportsbetting+1 crossposts

8/15 picks, parlays and writeup

41-39 on legs. +8.95u through eight days.

Today's card: 7 legs, 2 tickets, 0 game totals.

Fifteen-game slate.

Date	Legs	Net
8/7	7-8	+6.18u
8/8	5-5	-7.10u
8/9	6-2	+8.58u
8/10	6-6	+2.72u
8/11	3-6	-1.83u
8/12	5-5	-4.33u
8/13	3-3	+0.88u
8/14	6-4	+3.85u
Total	41-39	+8.95u

What last night changed

Three of my four losses yesterday had a legitimate warning attached beforehand, and I kept the leg anyway.

Kirby — Houston was the most patient lineup on the slate. Patient lineups create deeper counts and more opportunities for walks.

He walked 3.

Cole — the Yankees' relief staff was short, which gave him more room to work deeper into the game. More innings means more opportunities for a second walk.

He went six innings and walked 2.

Holmes — the matchup history didn't support the strikeout over.

He finished with 3 K.

So today I'm handling those situations differently.

If the opposing case is strong enough to write about, it's strong enough to leave the leg off.

Four others looked good at first, but I left them out after a second review.

The board

Pitcher	Pick	Number	Proj	Prob	L5	L10	Strike%	FPS	Behind	Previous
Brad Lord	Outs U11.5	+106	8.69	91%	5/5	10/10	64.7%	75%	24%	8 outs
Troy Melton	ER U1.5	+125	0.78	81%	4/5	8/10	66.2%	68%	28%	1 ER
Eduardo Rodriguez	ER U3.5	-160	2.35	80%	5/5	8/10	65.8%	66%	31%	0 ER
Jacob Misiorowski	BB U1.5	-111	0.94	78%	3/5	8/10	68.1%	75%	20%	—
Ryan Gusto	ER U2.5	-130	1.88	76%	4/5	8/10	62.4%	59%	32%	0 ER
Sean Manaea	Hits O4.5	-160	5.55	72%	4/5	8/10	65.9%	66%	32%	7 hits
Matthew Boyd	ER U2.5	-160	1.88	70%	3/5	7/10	67.4%	72%	28%	0 ER

Proj = my projection.

FPS = first-pitch strike rate over the last five. League average is about 61%.

Behind = share of pitches ending with the pitcher behind in the count over the last five. League average is about 34%.

Previous = result from the previous meeting with tonight's opponent.

Ticket A — Earned run unders, +547

Model estimate: 49.3%
Implied estimate: 15.5%

Eduardo Rodriguez U3.5 ER (-160)
Troy Melton U1.5 ER (+125)
Ryan Gusto U2.5 ER (-130)

Three different games.

All three have stayed below their number in 8 of their last 10.

All three also held tonight's opponent to one earned run or fewer in the previous meeting.

Ticket B — Workload and control, +536

Model estimate: 49.7%
Implied estimate: 15.7%

Brad Lord U11.5 outs (+106)
Jacob Misiorowski U1.5 walks (-111)
Matthew Boyd U2.5 ER (-160)

Three different games.

About those model estimates

A roughly 3x difference between my estimate and the implied number on both tickets is larger than I'm comfortable treating literally.

My individual-leg probabilities have been running high.

Last night's Michael King O3.5 K was assigned 80.1% and did finish above the line — but only barely, with exactly 4 K.

So for now:

I trust the direction more than I trust the size of the percentage.

The probability numbers should be treated as relative strength, not as proven calibration.

Brad Lord U11.5 outs

This is the strongest number on today's board at 91%, and the underlying numbers are unusual.

Over his recent starts:

First-pitch strikes: 75%

Behind in the count: 24%

Both are much better than league average.

And yet he still needs:

7.43 pitches per out

That's the highest rate on today's board by a wide margin.

So he's getting ahead of hitters but still struggling to finish plate appearances efficiently.

That's exactly the type of combination that can create short outings.

Twelve outs at 7.43 pitches per out would require roughly:

89 pitches

My projection:

8.69 outs

Troy Melton U1.5 ER

Number:

+125

Projection:

0.78 ER

Recent command:

68% first-pitch strikes

28% behind in the count

He's stayed below 1.5 earned runs in:

8 of his last 10

Previous meeting with Detroit:

1 earned run

Jacob Misiorowski U1.5 walks

Best control numbers on the board.

Over his recent starts:

75% first-pitch strikes

20% of pitches ending behind in the count

For comparison, league averages are roughly:

61% first-pitch strikes

34% behind

Projection:

0.94 walks

Line:

1.5

He's stayed below the number in:

8 of his last 10

Sean Manaea O4.5 hits — single

Projection:

5.55 hits

Previous meeting with Washington:

7 hits allowed

What I left off

Logan Webb U20.5 outs (+155)

Calculated probability:

72%

But the recent results don't support that number.

He's stayed below 20.5 in only:

1 of his last 5

and

5 of his last 10

That's four straight starts above the line.

When a 72% estimate is sitting next to a 1-of-5 recent result, I want more evidence before using it.

Left off.

Hayden Wesneski

Three different numbers initially qualified:

K U4.5 — 80%
BB O1.5 — 80%
Outs O15.5 — 73%

The problem is that he has only three appearances in the relevant history.

Three-for-three isn't enough for me to call something a trend.

The walks number also doesn't fit cleanly with his control numbers.

He's around:

65% first-pitch strikes

Yet the projection is calling for roughly two walks.

That disagreement is enough for me to stay away.

Ian Seymour U17.5 outs

Calculated probability:

71%

Randy Dobnak U2.5 ER

Calculated probability:

87%

Second-highest number on today's board.

But there's almost no useful opponent history behind it.

Only two career plate appearances against this lineup and a thin overall sample.

I'm not giving an 87% estimate much weight when the evidence underneath it is that limited.

Game totals

None tonight.

Second straight night with no totals.

I only take a game total when my derived number differs from the listed line by at least:

0.75 runs

Largest gap tonight:

+0.65

Rockies at Giants O7.5.

Across the twelve games with usable numbers:

Average residual: -0.179

Standard deviation: 0.372

My totals and the listed numbers are simply too close tonight.

Matchup	Derived	Line	Difference
Rockies at Giants	8.15	7.5	+0.65
Marlins at Reds	8.91	9.5	-0.59
Nationals at Mets	7.92	8.5	-0.58
Royals at Angels	7.97	8.5	-0.53
Brewers at Dodgers	7.04	7.5	-0.46
Rangers at Athletics	9.06	9.5	-0.44
Cardinals at Cubs	8.70	9.0	-0.30

Game totals are currently:

6-4

Part of keeping that segment selective means doing nothing on nights when the numbers don't separate enough.

Tonight is one of those nights.

Notes

Seven legs across a fifteen-game slate.

I kept the list shorter on purpose.

Eight days is still a very small sample, so there is not enough history to draw firm conclusions.

Several other numbers looked interesting, but I left them out after reviewing the full data.

Seven legs tonight.

The shorter list is intentional.

Overall results

Date	Legs	Net
8/7	7-8	+6.18u
8/8	5-5	-7.10u
8/9	6-2	+8.58u
8/10	6-6	+2.72u
8/11	3-6	-1.83u
8/12	5-5	-4.33u
8/13	3-3	+0.88u
8/14	6-4	+3.85u
Total	41-39	+8.95u

41-39 on individual legs.

+8.95u overall.

Game totals: 6-4.

Eight days is still a very small sample.

Baseball has enormous night-to-night variance. The goal isn't to pretend every outcome can be predicted.

The useful part is laying out the workload, recent results, command numbers and opponent history behind each leg, then coming back afterward and seeing what actually mattered.

Results tomorrow — wins and losses both.

reddit.com

u/nrichardson5 — 5 days ago

▲ 5 r/sportsbetting+1 crossposts

8/14 bets, parlays and writeup

35-35 on legs. +5.10u through seven days.

Today's card: 9 legs, 2 tickets, 0 game totals.

Fourteen-game slate.

Date	Legs	Net
8/7	7-8	+6.18u
8/8	5-5	-7.10u
8/9	6-2	+8.58u
8/10	6-6	+2.72u
8/11	3-6	-1.83u
8/12	5-5	-4.33u
8/13	3-3	+0.88u
Total	35-35	+5.10u

Seven days is still not a meaningful sample.

Most of the gain traces back to two tickets on two nights, plus last night's totals sweep.

Two things are new on the card

Every outs projection now shows its range

I measured the actual error across 3,568 starter starts this season — what the projection said compared with what actually happened.

The spread came out to:

3.2 outs

The projection was also running low by about:

0.75 outs

Both are corrected now, and the uncertainty around each outs projection is shown with the number.

That matters because of Ashcraft last night.

I called his U17.5 outs the strongest workload case on the board.

Once the historical error range is included, it was really about:

59%

He threw a complete game.

A 59% leg losing does not mean the model is broken.

It means it was a 59% outcome.

I described it with more certainty than the number justified, and showing the range should make that harder to do again.

Every pitcher now shows first-pitch strike rate and how often he gets behind

League averages are roughly:

61% first-pitch strikes

34% behind in the count

These numbers do not move the projection.

I checked them and they were worth roughly half a percentage point, which is not enough to justify changing the output.

They're here because they can explain results that the projection alone cannot.

Ashcraft is the perfect example.

Last night he threw first-pitch strikes to:

19 of 29 hitters

And 41% of plate appearances were finished by his second pitch.

That's a huge part of how an 85-pitch complete game happens.

We had that information available.

I just wasn't giving it enough attention.

The board

Pitcher	Pick	Price	Proj	Prob	L5	L10	Strike%	FPS	Behind	BvP
Michael King	K O3.5	-132	4.69	80.1%	4/5	9/10	63.9%	68%	34%	24% K, 50 PA
George Kirby	BB U1.5	-175	1.01	71.6%	3/5	7/10	66.6%	63%	34%	.264, 130 PA
Gavin Williams	ER O1.5	-110	2.06	70.5%	5/5	8/10	69.8%	64%	28%	.455, 24 PA
Gerrit Cole	BB U1.5	-250	1.21	68.0%	4/5	7/10	65.8%	62%	31%	.245, 135 PA
Yoshinobu Yamamoto	K U6.5	+120	5.60	67.9%	3/5	7/10	64.6%	63%	32%	12.5% K, 48 PA
Clay Holmes	K O3.5	-122	4.40	67.9%	3/5	7/10	65.3%	58%	30%	15.8% K, 38 PA
Robert Stock	Outs U14.5	+107	12.8	66.8%	1/2	1/2	64.7%	57%	45%	None
Jake Bennett	Hits U5.5	-130	5.01	65.7%	5/5	7/10	66.5%	63%	33%	None
Landen Roupp	Outs U17.5	+115	16.8	58.4%	2/5	5/10	61.0%	57%	41%	.000, 54.5% K, 11 PA

Proj = my projection
Prob = model probability
Strike% = overall strikes thrown, last five
FPS = first-pitch strike rate, last five
Behind = share of pitches ending behind in the count, last five
BvP = this lineup's career results against this pitcher

Michael King O3.5 K

Best-supported leg on the card.

He's cleared this number in:

9 of his last 10

His strikeout numbers are moving upward:

Last 5: 5.6

Last 10: 4.8

Season: 5.0

There is a real counterpoint, and it's the strongest one I have today.

Cleveland has stopped striking out.

Over its last five:

5.0 strikeouts per game

Season average:

8.2

Cleveland also has only a 9.2% whiff rate against King's pitch mix, the lowest of any lineup I looked at tonight.

I'm keeping the over because King's recent 5.6 strikeouts against a 3.5 line gives him a two-strikeout cushion.

Cleveland would have to hold him to almost half his recent rate.

But 80% is aggressive once Cleveland's recent contact is considered.

Gavin Williams O1.5 ER

He's allowed at least two earned runs in:

5 of 5

8 of 10

This is the one leg where command and outcome point in opposite directions.

Williams has some of the best command numbers on the board:

64% first-pitch strikes

Behind only 28% of the time

And I still have the earned-runs over.

The reason is San Diego's aggression.

They're putting the first pitch in play roughly:

17% of the time

Highest on tonight's slate.

Getting ahead of a lineup that swings early does not always lead to a quiet inning.

Sometimes it just means the contact comes sooner.

San Diego has 24 career plate appearances against Williams and is hitting:

.455

Williams throws the highest strike rate on the board at:

69.8%

He also averages only about:

0.8 BB per start

Excellent command.

This lineup has still squared him up.

Yoshinobu Yamamoto U6.5 K

His strikeout numbers have been drifting down:

Last 5: 5.4

Last 10: 5.8

Season: 6.05

Every window is below the 6.5 line, and the most recent sample is the lowest.

He's also the most efficient starter on the board at:

4.88 pitches per out

Efficient pitchers can move through at-bats before as many two-strike counts develop.

The counterpoint is Milwaukee.

They're striking out:

9.8 times per game over their last five

10.0 over their last ten

Season average:

8.3

They also have a 10.8% whiff rate against his pitch mix.

So Milwaukee is striking out well above its own baseline right now.

The previous matchup data pushes me back toward the under.

Milwaukee has 48 career plate appearances against Yamamoto and struck out only:

12.5%

Their previous meeting:

3 K

Against today's:

6.5 line

So Milwaukee's recent spike in strikeouts has not historically shown up against this pitcher.

Best-supported strikeout under on the card once that history is included.

Peter Lambert O4.5 K

Recent results and matchup history both point in the same direction.

Last 5: 6.0

Last 10: 5.8

Season: 5.55

All three sit above the line.

He's cleared it in:

4 of 5

7 of 10

Seattle has an 11.7% whiff rate against his pitch mix.

The previous matchup data agrees.

Across 39 plate appearances, Seattle has struck out:

30.8%

Their previous meeting:

6 K

Against a:

4.5 line

Recent results, whiff rate and matchup history all point the same way.

One of the cleaner legs on the card.

I left Lambert's earned-runs under off despite it producing the highest calculated number on the board.

Different stat category.

Different evidence.

Robert Stock U14.5 outs

Calculated probability:

66.8%

Strong workload argument.

Very thin sample.

Stock is running:

6.25 pitches per out

League is closer to:

5.6

He's also ending up behind in the count on:

45% of pitches

League average:

34%

A pitcher working from behind that often has to spend more pitches to collect outs.

At his current efficiency, 15 outs would cost roughly:

94 pitches

The problem is sample size.

He has only two appearances this season.

Recent record:

1 of 2

He also has no previous matchup history against Washington.

No plate appearances.

No previous meeting.

So this is not a trend.

It's two data points and an empty matchup sample.

The workload arithmetic is among the strongest on the board.

The evidence behind it is also among the thinnest.

Both things can be true.

Landen Roupp U17.5 outs

Similar idea to Stock, but with more history and less support.

Recent efficiency:

5.70 pitches per out

Behind in the count:

41%

Recent record below this number:

2 of 5

5 of 10

There are two significant counterpoints.

Colorado puts the first pitch in play roughly:

15% of the time

That's an aggressive lineup capable of creating quick outs.

The small matchup sample also points the wrong direction.

In 11 plate appearances against Roupp, Colorado is hitting:

.000

With a strikeout rate of:

54.5%

Eleven plate appearances is tiny.

I'm not treating it as decisive.

But a pitcher who has dominated a lineup is more likely to work deeper, which is the opposite of what this under needs.

The BB legs

Gerrit Cole U1.5 BB

Recent command numbers:

65.8% strikes

62% first-pitch strikes

Behind in the count: 31%

Season rate:

1.2 BB per start

George Kirby U1.5 BB

Kirby's command numbers:

66.6% strikes

63% first-pitch strikes

Season rate:

1.0 BB per start

Jake Bennett U5.5 hits

Recent record:

5 of 5

7 of 10

He's averaging:

4.74 pitches per out

Second-most efficient starter tonight.

First-pitch strike rate:

63%

Overall strike rate:

66.5%

This is more about efficient contact management than strikeouts.

There is no previous matchup history against Pittsburgh, so this one rests almost entirely on recent results and efficiency.

Clay Holmes O3.5 K

Recent record above the number:

3 of 5

7 of 10

First-pitch strike rate:

58%

That's slightly below league average.

But he's behind in the count only:

30%

So he's done a good job recovering after missing the first pitch.

The matchup history is the weak point.

St. Louis has 38 plate appearances against Holmes and struck out only:

15.8%

That's well below what I'd ideally want behind this line.

The previous meeting did produce:

5 K

Against a:

3.5 line

Tickets

Two tickets.

No repeated legs.

Every leg comes from a different game.

A. Workload unders — +345

Model estimate: 39.0%

Implied estimate: 22.5%

Robert Stock U14.5 outs (+107)
Landen Roupp U17.5 outs (+115)

Two legs instead of three.

I'd rather use a shorter ticket than force a third leg.

I'll also say clearly that this is the weakest-supported ticket on the card.

Stock has only two recent appearances.

Roupp has stayed below his number in only 2 of his last 5.

The workload arithmetic supports both.

The recent results are much less convincing.

B. Strikeouts and control — +286

Model estimate: 39.0%

Implied estimate: 25.9%

Michael King O3.5 K (-132)
George Kirby U1.5 BB (-175)
Gerrit Cole U1.5 BB (-250)

Singles

Yoshinobu Yamamoto U6.5 K
Peter Lambert O4.5 K
Clay Holmes O3.5 K
Jake Bennett U5.5 hits
Gavin Williams O1.5 ER

What I left off

Michael King U17.5 outs

This was originally included alongside his strikeout over.

I left the outs leg off the card.

The two positions pull against each other.

The outs under wants a shorter start.

The strikeout over benefits from more batters and more innings.

Gavin Williams is also the opposing starter in that same game.

Three different positions tied to one game creates too much shared risk.

Same issue I caught with Messick and Montero yesterday.

Robert Stock O3.5 K — 78.3%

Stock is already on Ticket A with U14.5 outs.

Same tension.

One position per start.

The earned-runs U2.5 cluster

Alcantara: 71.4%

Burns: 71.0%

Chandler: 70.9%

Alvarez: 70.6%

Lambert: 80.6%

Five pitchers.

Five different opponents.

Every projection landed between:

1.81 and 1.87

That level of uniformity looks like a default behavior rather than five genuinely independent matchup reads.

Lambert's was the highest number on the entire board.

I'm not making an exception just because the percentage is larger.

Seth Lugo O1.5 BB — 72%

First-pitch strike rate:

66%

The model also has him at:

2.18 BB

Those two inputs don't fit together cleanly enough for me.

Left off.

Sean Newcomb

Projected for:

4 outs

His uncertainty range is intentionally left blank.

The 3.2-out historical spread I calculated applies to starters.

It doesn't make sense for a reliever.

Game totals

None tonight. Nothing cleared the threshold.

I use a game total only when my derived number differs from the listed line by at least:

0.75 runs

Tonight the largest disagreement on the entire slate is:

+0.64

Yankees at Blue Jays O8.0.

Here's the full board:

Matchup	Derived	Line	Diff
Yankees at Blue Jays	8.64	8.0	+0.64
White Sox at Tigers	7.91	8.5	-0.59
Mariners at Astros	7.98	8.5	-0.52
Brewers at Dodgers	7.85	7.5	+0.35
Nationals at Mets	8.76	8.5	+0.26
Padres at Guardians	7.24	7.5	-0.26
Rockies at Giants	7.75	7.5	+0.26
Marlins at Reds	7.85	8.0	-0.15
Red Sox at Pirates	8.15	8.0	+0.15
Cardinals at Cubs	7.93	8.0	-0.07
Royals at Angels	8.55	8.5	+0.05

Across 11 games, the average difference is:

+0.010

Standard deviation:

0.357

An average that close to zero means there isn't a broad directional disagreement tonight.

My numbers and the listed totals are basically lined up.

Yesterday produced three totals, with the strongest difference at:

+1.68

Tonight the entire slate is inside two-thirds of a run.

That's exactly why the 0.75 threshold exists.

I'd rather have:

0 totals

than force three just to fill the section.

Totals are:

6-4 overall

Being selective is part of that.

Caveats

Nine legs on a fourteen-game slate.
Every leg comes from a different game.
Prices are aggregated and may differ from what you see.
Seven days is nowhere near enough data to establish a meaningful track record.
Ticket A is the weakest-supported part of today's card, and I'm saying that here rather than burying it.

A total of 54 lines cleared the initial edge filter.

I'm using nine.

Most of what got cut was left off because the calculated number looked strong while the evidence underneath it did not hold up, or because it created a second position tied to a start I was already using.

Overall results

Date	Legs	Net
8/7	7-8	+6.18u
8/8	5-5	-7.10u
8/9	6-2	+8.58u
8/10	6-6	+2.72u
8/11	3-6	-1.83u
8/12	5-5	-4.33u
8/13	3-3	+0.88u
Total	35-35	+5.10u

35-35 on individual legs.

+5.10u overall.

Game totals: 6-4.

Baseball has a huge amount of randomness.

A pitcher can execute exactly the plan you expected and still give up four singles.

Another can miss locations all night and somehow strike out ten.

The point isn't to pretend every bounce can be predicted.

It's to put the evidence behind each number in front of you — workload arithmetic, recent results, matchup history, pitch efficiency and now the uncertainty around each projection — so each leg can be judged on its own evidence rather than the running total.

Results tomorrow — wins and losses both.

reddit.com

u/nrichardson5 — 6 days ago

▲ 7 r/sportsbettingzone+2 crossposts

8/13 picks, parlays and writeup

32-32 on legs. +4.22u through six days.

Today's card: 6 legs, 2 tickets, 3 game totals.

Nine-game slate. Deliberately smaller than yesterday.

Date	Legs	Net
8/7	7-8	+6.18u
8/8	5-5	-7.10u
8/9	6-2	+8.58u
8/10	6-6	+2.72u
8/11	3-6	-1.83u
8/12	5-5	-4.33u
Total	32-32	+4.22u

Six days is not a meaningful sample yet. Nearly all of the gain still traces back to two tickets on two nights.

Why the card shrank

I've gone 1-5 on tickets over the last two nights while going 3-6 and 5-5 on the individual legs.

Tuesday also put 18 units at risk across legs, tickets and totals — the most I've had on one card.

Baseball has a huge amount of randomness.

A pitcher can execute the plan you projected and give up four singles. Another can miss his spots all night and still strike out ten.

My job here isn't to pretend I can predict every bounce. It's to put the actual evidence for each pick in front of you:

Workload arithmetic
Matchup history
Recent results
Hits allowed
Pitch efficiency
Bullpen situation

That way you can judge the number on the evidence instead of taking it on faith.

Stacking three legs into one ticket multiplies the variance.

That's the argument for a shorter card rather than a longer one.

Three-leg tickets need something around a 55% individual-leg hit rate to justify the payout structure I'm using.

Six days is nowhere near enough to know whether I'm there.

So today:

2 tickets. 6 legs.

I'm leaving good-looking options off rather than reaching to fill a third ticket.

One rule changed again

I also want to be clear about the BvP adjustment I made Monday.

I gave batter-vs-pitcher history more weight because it correctly flagged two losses from the previous card.

Then Tuesday I built my core ticket entirely from legs where BvP and previous matchup results both agreed.

It went:

0-for-3.

Castillo was the loudest example.

He had a 16.1% matchup strikeout rate across 56 plate appearances supporting his U5.5 K.

He finished with:

10 K.

So after one night each way, I'm not treating BvP as a hard veto anymore.

It's weighted context, not an automatic decision.

The board

Pitcher	Pick	Price	Proj	Book	L5	L10	Time
Keider Montero	Outs U16.5	+107	15.35	16.82	2/5	3/10	1:10
Davis Martin	K U4.5	+106	4.75	4.74	2/5	2/10	2:10
Max Scherzer	K U4.5	-145	3.94	4.18	1/5	1/9	3:07
Braxton Ashcraft	Outs U17.5	+115	16.05	18.09	1/5	4/10	1:10
Aaron Nola	Hits O5.5	+105	5.86	5.39	4/5	7/10	7:30
Jacob deGrom	Hits O4.5	+105	4.72	4.45	4/5	6/10	10:07

Proj = my projection.
Book = the sportsbook's implied number after removing vig.

Keider Montero U16.5 outs

Cleanest number on the board for me.

Montero needs 17 outs to beat the under.

At his recent 4.96 pitches per out, 17 outs would require roughly:

84 pitches

His average over the last five:

74 pitches

That's a meaningful workload jump just to reach the other side of the number.

Detroit's bullpen is rested, so an earlier hook is available if he starts laboring.

His one previous meeting with Cleveland ended at:

15 outs.

Max Scherzer U4.5 K

He's cleared this number in only:

1 of his last 9 starts

The bigger thing for me is pitch efficiency.

Over his last five, Scherzer is averaging roughly:

6.9 pitches per out

That's easily the highest number on this board.

If you're burning that many pitches to record outs, you're simply getting fewer batters and fewer opportunities to accumulate strikeouts.

The ugly part is the price:

-145

Davis Martin U4.5 K

This is basically the plus-money version of the Scherzer idea.

Martin has stayed below the number in:

3 of his last 5

and

8 of his last 10

Cincinnati has also struck out at only:

10% across 20 plate appearances

against him.

That's a small matchup sample, so I'm not treating it as decisive.

But it does point in the same direction as the recent results.

Tickets

Two tickets.

Six pitchers.

No leg repeated.

A. Unders — +621

Model estimate: 21.4%
Implied estimate: 14.0%

Keider Montero U16.5 outs (+107) — 1:10 ET
Davis Martin U4.5 K (+106) — 2:10 ET
Max Scherzer U4.5 K (-145) — 3:07 ET

All three are early games.

So this ticket will be decided before dinner.

B. Hits and workload — +804

Model estimate: 15.5%
Implied estimate: 9.5%

Braxton Ashcraft U17.5 outs (+115) — 1:10 ET
Aaron Nola O5.5 hits (+105) — 7:30 ET
Jacob deGrom O4.5 hits (+105) — 10:07 ET

The two hits legs are based on hits allowed, not workload.

That's the evidence I want for this type of line.

Aaron Nola O5.5 hits

Hits allowed in his last ten:

7, 3, 8, 7, 3, 6, 7, 5, 6, 6

He's cleared 5.5 in:

7 of 10

and

4 of 5

Season average:

5.75 hits allowed

That's already above the line.

He's also allowing a hit to roughly:

24.7% of the batters he faces

Jacob deGrom O4.5 hits

He's cleared this number in:

4 of his last 5

and

6 of his last 10

The trend has also moved upward:

Season: 4.73

Last 10: 5.2

Last 5: 5.8

His two previous meetings with the Angels resulted in:

6 hits and 5 hits.

Braxton Ashcraft U17.5 outs

This one is a workload argument.

Ashcraft needs 18 outs to beat the under.

At his recent 5.78 pitches per out, that would require about:

104 pitches

His average over the last five is:

83 pitches

That's roughly a 25% workload increase just to reach 18 outs — the biggest workload gap on my board.

He's reached 18 outs only once in his last five.

His previous meeting with Miami ended at:

15 outs.

There is one important counterpoint:

Pittsburgh's bullpen is short on available arms, which can buy a starter a longer leash.

I'm still keeping the under because 104 pitches is a difficult workload requirement regardless of who is available behind him.

What I left off

Max Fried U17.5 outs (+155)

This had the highest calculated edge on my board:

+15.4%

But there are two strong reasons against it.

His previous meeting with Seattle went:

21 outs

And the Yankees' bullpen is taxed with two arms unavailable.

That creates exactly the longer leash I'd rather not see when taking an outs under.

Highest calculated edge on the page.

Not on the card.

Logan Gilbert O17.5 outs

His previous meeting went:

16 outs

The Yankees have also hit:

.277 across 44 plate appearances

against him.

Left it alone.

Payton Tolle O5.5 K

Recent form is strong:

5 of 5

8 of 10

But Toronto has a 17% whiff rate across 29 plate appearances against him.

His two previous meetings produced:

4 K and 6 K

Not enough agreement for me to include it.

Cade Cavalli and Andrew Abbott

Both came back calibrator-saturated.

In other words, the calculated probability is sitting on a known model ceiling rather than giving me a useful read of the matchup.

Neither made the card.

Weather

Nothing decisive today.

Miami

Retractable roof.

Expected to be closed.

Toronto

Retractable roof.

Expected to be closed.

Seattle

The only notable wind reading is around:

12.5 mph gusts

That's where Fried and Gilbert are pitching.

I left both of those legs off anyway.

Game totals

Matchup	Line	Pick	Price	Time
Pirates at Marlins	8.0	OVER	-104	1:10
Reds at White Sox	8.5	OVER	+105	2:10
Brewers at Dodgers	8.5	OVER	+107	10:10

Three of the nine games cleared my threshold.

Strongest total: Pirates at Marlins O8.0

Model edge:

+1.68 runs

That's the largest totals edge the model has produced since I started tracking these.

Reds at White Sox is here for the third straight day

And I've been wrong on it twice.

Monday:

U7.5

Final:

Tuesday:

O9.0

Final:

Today:

O8.5

I'm including it because that's what the current inputs produce.

I'm not going to manually override the output because the previous two games went against me.

But the history deserves to be shown:

0-2 on this matchup this week.

Lifetime game-total record:

3-4

Caveats

Six legs and two tickets on a nine-game slate is the smallest card I've posted. That's intentional.
Every leg is from a different game.
Prices are cross-book aggregates and may be shorter at one individual sportsbook.
Six days is nowhere near enough data to establish a meaningful track record.

One leg that got left off because of the no-overlap structure was Parker Messick O5.5 K.

He cleared my edge filter at +7.0%, has reached the number in 4 of 5 and 6 of 10, and recorded 6 K in the previous meeting.

But he's the opposing starter to Montero.

I don't want two separate tickets depending on the same game developing into a low-scoring pitchers' duel.

So Messick stayed off.

Overall results

Date	Legs	Net
8/7	7-8	+6.18u
8/8	5-5	-7.10u
8/9	6-2	+8.58u
8/10	6-6	+2.72u
8/11	3-6	-1.83u
8/12	5-5	-4.33u
Total	32-32	+4.22u

32-32 on individual legs. +4.22u overall.

Nearly all of that gain traces back to two tickets on two nights.

Six days isn't a track record in a sport this noisy.

That's why I publish the reasoning behind every pick — so each one can be judged on its evidence rather than on the running total.

Results tomorrow — wins and losses both.

reddit.com

u/nrichardson5 — 7 days ago

▲ 10 r/sportsbetting

8/12 bets, parlays and writeup

27-27 on legs. +8.55u through five days.

Today's card: 9 pitcher props, 3 tickets, 1 single, 5 game totals.

Fifteen games. Pitcher props plus five game totals — the most totals I've had clear the bar since I started posting them.

One change after last night, and it cost me two legs I'd otherwise have included.

BvP is now a gate, not a footnote

I went 3-6 yesterday.

Both singles I lost had batter-vs-pitcher warnings attached that I noted beforehand but ultimately chose not to follow:

Sandoval O4.5 K — Toronto had a 14.8% whiff rate over 54 plate appearances against him. He struck out 4.
Harrison U4.5 hits — San Diego had hit .302 against him. He allowed 10.

Both flags were right.

So starting today, if a BvP reading backed by 50+ plate appearances points against a leg, I'm leaving it off the card.

Two legs got cut by that rule this morning. They're listed near the bottom.

The board

Proj = my projection.
Book = the sportsbook's implied number after removing vig.

Pitcher	Pick	Price	Proj	Book	L5	L10	Time
Luis Castillo	K U5.5	+106	4.49	5.75	0/5	0/10	7:40
Ranger Suarez	K O4.5	+128	4.77	4.41	3/5	8/10	7:07
David Peterson	K U4.5	-119	4.04	4.43	1/5	2/10	6:45
Will Warren	Outs U16.5	-115	15.10	16.66	1/5	3/10	7:05
Shane Baz	Hits O5.5	-102	6.01	5.71	4/5	7/10	1:40
Kyle Leahy	Outs O15.5	+160	15.66	14.44	3/5	5/10	2:15
Merrill Kelly	Outs U17.5	+110	16.01	18.19	0/5	3/10	3:40
Zebby Matthews	K U5.5	-128	5.35	5.29	1/5	2/10	1:40
Jack Perkins	K O3.5	-128	4.31	3.98	3/5	8/10	3:05

Luis Castillo U5.5 K

Best thing on the board for me today.

He has not reached six strikeouts in any of his last ten starts.

The book's implied number comes out to 5.75 against my projection of 4.49, the widest gap on the card.

The matchup agrees.

Cincinnati has struck out at just 16.1% across 56 plate appearances against him, and Castillo had only 3 K the last time he faced them.

Ranger Suarez O4.5 K

Pretty much the mirror image.

Toronto has a 32.7% whiff rate across 52 plate appearances against Suarez.

His two previous meetings produced:

10 K
6 K

He's also cleared 4.5 in 8 of his last 10.

The roof is closed in Toronto, so the 29% rain reading doesn't matter.

Will Warren U16.5 outs

This one is mostly arithmetic.

He needs 17 outs to beat the under.

At his recent 5.58 pitches per out, getting 17 outs would require roughly 95 pitches.

He's averaged only 69 pitches per start over his last five.

That's about a 37% workload increase just to reach the losing side of this number.

The Yankees' bullpen is also rested.

Tickets

Three tickets.

Nine pitchers.

No leg repeated.

A. Core — +764

Model probability: 23.6%
Implied probability: 11.9%

Luis Castillo U5.5 K (+106) — 7:40 ET
Ranger Suarez O4.5 K (+128) — 7:07 ET
David Peterson U4.5 K (-119) — 6:45 ET

All three have matchup history supporting the same side as the pick.

That was also true of all three legs in Ticket B last night, which finished 3-for-3.

Peterson's numbers are similar to Castillo's.

Washington has struck out at only 13.0% across 92 plate appearances against Peterson.

His two previous meetings finished with:

5 K and 3 K.

B. Volume and workload — +863

Model probability: 15.0%
Implied probability: 9.5%

Will Warren U16.5 outs (-115) — 7:05 ET
Shane Baz O5.5 hits (-102) — 1:40 ET
Kyle Leahy O15.5 outs (+160) — 2:15 ET

Baz has cleared his number in 4 of his last 5 and allowed 7 hits the last time he faced Minnesota.

Leahy is the plus-money leg.

Getting 16 outs should cost him roughly 86 pitches based on his recent efficiency.

His average is 84 pitches.

So unlike Warren, the workload needed to beat the number is completely normal for him.

C. Speculative — +566

Model probability: 22.6%
Implied probability: 14.4%

Merrill Kelly U17.5 outs (+110) — 3:40 ET
Zebby Matthews U5.5 K (-128) — 1:40 ET
Jack Perkins O3.5 K (-128) — 3:05 ET

Read the Kelly warning before using this ticket.

Kelly has not reached 17.5 outs in any of his last five starts.

Getting 18 outs would require roughly 101 pitches at his recent rate.

His average is 89.

But there's a major counterpoint:

He threw a complete game against Colorado earlier this season — 27 outs.

That's the only previous meeting available, and it directly contradicts the under.

One start isn't a pattern.

But it's a bad data point to ignore.

Matthews and Perkins both have fewer than 11 plate appearances of matchup history, so neither has enough BvP data to make a meaningful call.

Single

Framber Valdez O1.5 walks (-115) — 6:40 ET

Not in a ticket.

It's also the first walks prop I've posted.

My model has it at:

68% vs. roughly 53% implied

That's the widest probability gap of anything on the card.

Projection: 1.87 walks

Season average: 1.96

Last 10: 1.8

Last 5: 1.8

If you include hit batters, he's put 2.6 hitters on for free per start over his last five.

The caveat is important:

Every result I've published so far has been strikeouts, outs or hits allowed.

I don't have a track record for the walks model yet.

So I can't tell you that a 68% walks projection deserves the same confidence as a 68% strikeout projection.

Smaller stake than a ticket leg for me.

His U17.5 outs at +124 is arguably the cleaner option.

My projection is 15.87 outs, all three recent windows are below 17, and getting 18 outs should require roughly 94 pitches against an 83-pitch average.

I left it off because that would've brought the card to ten pitcher legs, and I'm already stretching further than I wanted.

What I passed on

Cal Quantrill U4.5 hits

This cleared my edge filter at +7.6%.

Dustin May U17.5 outs

Two previous meetings with San Diego:

18 outs
27 outs

Two starts isn't a huge sample, but both went against the under.

I left it alone.

Weather

Philadelphia

100.2°F and open air.

Hottest true outdoor conditions on the board.

That's worth keeping in mind behind Leahy's outs over.

Arizona

Chase Field is showing 98.8°F outside, but the roof will be closed.

So Kelly's game should play in neutral indoor conditions.

Toronto

Roof closed.

The rain reading on Suarez is irrelevant.

Game totals

Matchup	Line	Pick	Price	Time
Rays at Athletics	9.5	OVER	+109	3:05
Mariners at Yankees	8.5	OVER	-102	7:05
Mets at Braves	8.5	UNDER	+108	7:15
Reds at White Sox	9.0	OVER	-102	7:40
Rangers at Angels	9.5	OVER	+117	10:10

Five totals is a lot.

I had two yesterday and the threshold has not changed.

So don't read this as five equally strong picks.

Read it as a slate where the model has more totals clearing its threshold than usual.

Strongest total: Rays at Athletics O9.5

Model edge:

+1.22 runs

That matchup finished with 16 runs yesterday.

Worth pointing out the opposite situation too:

Yesterday I had the under in Reds/White Sox and it lost with 9 total runs against a 7.5 line.

Today the model wants the over on a higher number.

That's the model reacting to different starting pitchers.

Not me trying to chase yesterday's result.

Lifetime game-total record: 1-1.

Caveats

Nine ticket legs plus a single on a 15-game slate is still more than I'd like.
Ticket C is the most speculative of the three and the first one I'd leave out if you're trimming the card.
Prices are cross-book aggregates and will probably be shorter at one individual book, especially Leahy +160 and Suarez +128.
Five days is nowhere near enough data to prove anything.

Overall results

Date	Legs	Net
8/7	7-8	+6.18u
8/8	5-5	-7.10u
8/9	6-2	+8.58u
8/10	6-6	+2.72u
8/11	3-6	-1.83u
Total	27-27	+8.55u

27-27 on individual legs. +8.55u overall.

Essentially all of the profit has come from two tickets on two nights.

Dead even on individual legs is still the honest headline.

Results tomorrow — wins and losses both.

reddit.com

u/nrichardson5 — 8 days ago

▲ 4 r/sportsbetting+1 crossposts

8/11 picks, parlays and writeup

Fifteen-game slate. Pitcher props + game totals for the first time.

Fifteen games. Pitcher props across strikeouts, outs and hits allowed — plus game totals for the first time, which I've flagged properly further down.

Two changes today, both out of the 8/10 postmortem.

Head-to-head: a warning

Going back through Sunday's losses, the Bryce Elder miss was sitting there in plain sight. He had one prior start against the Mets this season and gave up ten hits in it. The line was 5.5, I took the under, and he gave up ten again.

We had that data the whole time and were simply overlooking it, so it's part of the process now.

But I nearly overcorrected. History only repeats against a club when it's an actual pattern — one bad night is an anecdote, and a starter who's throwing well against a lineup he's had trouble with before is still a good bet.

So a repeated result against that team can kill a leg. One or two starts is a note, and I check the batter-vs-pitcher history and current form before deciding.

Six legs had head-to-head running against them tonight. None of them is a trend — every one is a single start or a one-of-two split.

Three stay on the board with the warning attached:

Leg	Last time vs this club	Why it stays
Patrick Sandoval K OVER 4.5	3 K on 7/24	54 PA at .228 against him, cleared in 4 of 5
Ryan Weathers K UNDER 6.5	7 K on 3/30	Under in 8 of 10, and that H2H is 21 PA
Kyle Harrison hits UNDER 4.5	5 hits on 5/14	Under in 8 of 10, last five average 3.4

Three I am passing on — and once I looked properly, not one of them is really about head-to-head:

Nolan McLean outs OVER 17.5 — clearing it costs about 98 pitches at his recent rate and he's been averaging 96. It's a workload problem.
Paul Skenes hits OVER 4.5 — Miami strikes out at a 42% clip against him in 33 PA. Balls need to be in play to become hits.
Tomoyuki Sugano K OVER 2.5 — Arizona has struck out 7.7% of the time against him across 39 PA and hits .293. That's the reason, and the two thin starts just agree with it.

Command

I'm also tracking strike rate, free passes (walks + hit batsmen) and pitches per out for each starter.

It's context rather than a filter — command swings start to start far more than a season line suggests — but it explains a few of tonight's picks, so it shows up in the notes below.

Weather

Chase Field says 101.6 degrees and it means nothing. Retractable roof, it'll be closed, conditions inside are neutral. Same trap as Arizona on Sunday — if that number makes you think hitters' park, that's the mistake.

St. Louis at 99.4 open-air is the real hot spot (Sanchez/Pallante). Nothing of mine is in it.

San Francisco: 61 degrees, gusts to 22. Coldest and windiest game on the board, genuinely run-suppressing. That's behind my Hunter Brown under.

Rain tops out at 22%. Nothing close to a problem.

The board

Proj is my projection. Book is what the sportsbook's price implies once vig is stripped, so the gap is where we actually disagree.

Pitcher	Pick	Price	Proj	Book	L5	L10	Time
Brandon Young	K O 4.5	+128	4.53	4.38	4/5	8/10	7:40
Nolan McLean	K O 5.5	-150	5.69	6.13	5/5	9/10	7:15
Nick Martinez	Hits U 6.5	-150	5.93	6.23	1/5	1/10	9:40
Patrick Sandoval	Hits O 4.5	-147	5.68	5.01	5/5	5/5	7:07
Tanner Bibee	Hits U 5.5	+101	5.08	5.68	2/5	3/10	6:40
Ryan Johnson	Outs U 15.5	-132	14.53	14.70	0/5	1/10	9:38
Mitch Bratt	Outs U 15.5	+101	14.55	15.68	1/5	1/6	9:40
Hunter Brown	Hits U 4.5	+111	4.82	4.81	1/5	3/10	9:45
Dylan Cease	Hits U 4.5	-135	4.22	4.36	1/5	1/10	7:07

Nick Martinez has the best command on the board — 4.46 pitches per out, 69% strikes, 0.4 free passes a game over his last five. He is not walking his way into trouble, and he's cleared this hits number in one of his last ten.

Ryan Johnson is the opposite and that's the bet. 56% strikes, 3.4 free passes a game, and he has not once reached 15.5 outs in his last five. Angels' pen is rested, so the hook is available.

Dylan Cease vs Boston, hits allowed: 7, then 4, then 1. Trending the right way and the H2H agrees with the under.

Tickets

Three tickets, nine different pitchers, no leg appears twice. Payout is a realistic single book.

A. Core, +533

25.4% against a market 14.6%

Brandon Young OVER 4.5 K (+128), 7:40 ET
Nolan McLean OVER 5.5 K (-150), 7:15 ET
Nick Martinez UNDER 6.5 hits (-150), 9:40 ET

McLean is 5 for 5 and 9 for 10 on this number.

B. Model and history agree, +494

27.3% against a market 16.8%

Patrick Sandoval OVER 4.5 hits (-147), 7:07 ET
Tanner Bibee UNDER 5.5 hits (+101), 6:40 ET
Ryan Johnson UNDER 15.5 outs (-132), 9:38 ET

Every leg here has H2H behind it. Bibee's two prior meetings with Detroit: 4 hits and 2.

C. Plus money, +638

22.1% against a market 13.2%

Mitch Bratt UNDER 15.5 outs (+101), 9:40 ET
Hunter Brown UNDER 4.5 hits (+111), 9:45 ET
Dylan Cease UNDER 4.5 hits (-135), 7:07 ET

Bratt walks 3.4 a game and Arizona's pen is rested. Brown gets the cold and the wind.

All three tickets land within 0.02 of each other on expected value. That's the no-overlap build working — no single ticket carrying the page.

Singles

Patrick Sandoval OVER 4.5 K (+131), 7:07 ET is the largest single edge on my board and it is not in a ticket.

Toronto has hit .228 against him across 54 plate appearances and he's cleared this number in four of his last five.

Two things to know: he struck out only 3 against them on 7/24, and that same 54-PA sample has them whiffing at just 14.8%, which is soft for a strikeout over.

I like the price enough to play it anyway, at a smaller stake than a ticket leg.

Note he's already on ticket B for hits allowed, so playing both doubles you up on one start.

Ryan Weathers UNDER 6.5 K (-155) and Kyle Harrison UNDER 4.5 hits (-115) are the other two reinstated legs.

Both are 8-for-10 on the right side.

Both have a caution — Seattle has whiffed 33% against Weathers in a thin 21 PA, and San Diego hits .302 against Harrison.

Live plays, smaller stakes.

Game totals — first time posting these

New market, and I want to be upfront that this is day one.

I've been working on game totals privately for a while and have never posted them here, so there is no public record behind these two picks. Nothing below is backed by anything you can check. Treat it accordingly.

Matchup	Line	Pick	Price	Time
Rays at Athletics	10.5	OVER	+113	9:40
Reds at White Sox	7.5	UNDER	+104	7:40

Only two plays on a fifteen-game slate, and that's the point.

Totals have been by far the hardest market I've worked on — most of what I tried did nothing, and the version I'd have posted a week ago fired six picks a night and was living off one lucky Tuesday.

The bar is now high enough that most nights give me one or two games and some nights give me none.

I'd rather show you a thin board I believe in than a full one I don't.

Grading these publicly from tonight.

Caveats

Martinez under-hits is in the game I'm taking over. Not a contradiction — he can throw six good innings and the bullpens still produce eleven runs — but I'm pulling two directions in one park. If you dislike it, take the total and drop him; A still stands as a two-leg at +280.
Cease and Sandoval are in the same game going opposite ways. Deliberate. Across tickets that's anti-correlated, which lowers variance.
Prices are cross-book aggregates. A single book will be shorter, especially Young at +128.
On pitcher props I'm four days in at 24-21 on legs and up 10.38 units, most of it from two tickets. Four days is not a track record.
On game totals I'm 0-0. That record starts tonight and I'm not folding it into the props numbers.

Results tomorrow, wins and losses both.

reddit.com

u/nrichardson5 — 9 days ago

▲ 3 r/sportsbetting

8/9 picks, parlays and writeup

Sunday card across strikeouts, outs recorded and hits allowed. First pitch is 12:15 ET so this is an early one.

Two changes since yesterday, both from things that went wrong.

I stopped cutting pitchers on a fixed out count

My role filter used to throw out any starter whose season median was under 11 outs, on the theory that the model is blind to relievers the book has priced as starters. That's a real problem, but the filter was catching the opposite case too.

Two pitchers today, Ryan Gusto and Cristian Javier, both had season medians around 9 or 10. Both got cut. Their last two starts:

Gusto: 15 outs, then 18
Javier: 15 outs, then 18

They're being stretched out. The season median is describing a role neither of them has anymore, and the book already knows — it set both at 14.5 outs. The filter was cutting them for being exactly what the book says they are.

New version compares the last three starts against the actual line instead of a fixed number. It still cuts Brad Lord, whose last-3 median is 4 outs against an 8.5 line, which is the genuine version of the problem.

Expanding the field mostly showed me traps

Here's the part worth reading, because widening the net produced zero new bets and I think that's the useful result.

Once Gusto and Javier were visible, both showed big edges on unders. Gusto under 14.5 outs at +17% expected value, Javier under 14.5 at +12%. Both built on hitting the under in 8 of their last 10.

But those 8 unders are all from the short-role period. Both project over the line now. Betting those unders means using stale form against a pitcher who changed — which is precisely what I spent yesterday criticizing my own model for doing to Gavin Williams. Cut both.

Same reasoning killed Gusto's strikeout under, which had the added problem of a bottom-2 strikeout matchup.

I also passed on Randy Dobnak under 5.5 hits despite it grading as the single biggest edge on the board at +24.7%. His log is 6, 3, 4, 4, 4, 3, which is genuinely consistent. It's also only six starts, and I'm not putting a six-game sample above legs with ten.

So: the wider net surfaced four candidates, two of which looked like the best plays available, and all four got rejected on inspection. Previously they'd have been silently filtered and I'd never have seen them. I'd rather look and reject with a reason.

The card

L10 is how often he cleared that exact number in his last ten starts.

Pitcher	Pick	Price	Proj	L5	L10	Time
Brady Singer	K O 4.5	+105	4.58	4/5	9/10	12:15
Grayson Rodriguez	Outs U 17.5	+105	14.86	1/5	1/10	1:40
Joey Cantillo	Outs U 15.5	-143	14.86	0/5	2/10	2:10
Troy Melton	K O 4.5	-140	5.17	4/5	9/10	4:05
Troy Melton	Hits U 4.5	+120	5.14	1/5	2/10	4:05
Jared Jones	Hits U 4.5	-108	4.39	1/5	2/10	1:35
Matthew Boyd	K U 4.5	+124	4.62	1/5	3/10	2:10
Logan Webb	Hits U 5.5	+110	5.31	1/5	3/10	4:05

Brady Singer over 4.5 K is the best leg here. His log: 5, 5, 7, 6, 6, 5, 6, 6, 3, 6. Nine of ten over the number and the only miss was a 3. Cincinnati's pen is taxed at 155 pitches over two days, and the one thing yesterday's bullpen experiment did reliably predict was length — four of five taxed-pen starters went 6 innings or more. Longer start, more strikeout chances, and it's plus money.

Grayson Rodriguez under 17.5 outs is the biggest clean edge. One of ten, projects 14.86, and Baltimore's pen is fresh with nobody unavailable, so the quick hook is there if he wobbles. Fresh-pen outs unders went 2-0 for me yesterday.

Joey Cantillo under 15.5 outs has an odd pattern I like: 15, 24, 18, 15, 15, 15, 15, 11, 12, 15. He has finished on exactly 15 outs six times in ten starts. The line needs 16. He's 0 for his last 5.

Parlays

Realistic single-book payout first, my cross-book feed in parentheses.

A. Core three, +480 (feed +614)

25.6% against a market 13.8%

Brady Singer O4.5 K (+105), 12:15 ET
Grayson Rodriguez U17.5 outs (+105), 1:40 ET
Joey Cantillo U15.5 outs (-143), 2:10 ET

The one I'm playing.

B. Two-leg core, +247 (feed +320)

39.9% against a market 24.7%

Brady Singer O4.5 K (+105), 12:15 ET
Grayson Rodriguez U17.5 outs (+105), 1:40 ET

Best hit rate on the page.

C. Four legs, +851 (feed +1124)

17.0% against a market 7.9%

Brady Singer O4.5 K (+105), 12:15 ET
Grayson Rodriguez U17.5 outs (+105), 1:40 ET
Joey Cantillo U15.5 outs (-143), 2:10 ET
Troy Melton O4.5 K (-140), 4:05 ET

D. Melton same game, +247 (feed +277)

36.8% against a market 24.7%

Troy Melton O4.5 K (-140), 4:05 ET
Troy Melton U4.5 hits (+120), 4:05 ET

Correlated on purpose. A dominant start is few hits and a lot of strikeouts — one outcome described twice. Books price this as a same-game parlay so expect shorter than a straight multiply.

E. Nine of ten, +442 (feed +577)

25.2% against a market 14.8%

Brady Singer O4.5 K (+105), 12:15 ET
Jared Jones U4.5 hits (-108), 1:35 ET
Troy Melton O4.5 K (-140), 4:05 ET

Both strikeout legs are 9 for 10 against their number.

F. Short starts, +541 (feed +680)

22.2% against a market 12.4%

Grayson Rodriguez U17.5 outs (+105), 1:40 ET
Joey Cantillo U15.5 outs (-143), 2:10 ET
Matthew Boyd U4.5 K (+124), 2:10 ET

G. Plus money throughout, +1402 (feed +1971)

12.0% against a market 4.8%

Brady Singer O4.5 K (+105), 12:15 ET
Grayson Rodriguez U17.5 outs (+105), 1:40 ET
Matthew Boyd U4.5 K (+124), 2:10 ET
Troy Melton U4.5 hits (+120), 4:05 ET

All legs separate games except D, which is deliberate.

What I passed on and why

Connor Prielipp over 15.5 outs, +12.7%. There's a 38% chance of rain in Milwaukee and a delay-shortened start kills an outs over.
Grant Holmes under 4.5 K, +7.5%. The Yankees are 4th in strikeout rate and Atlanta's pen is taxed, so he's likely going longer against a lineup that whiffs. Two headwinds.

Where this fails

Three of my legs are unders resting on low hit rates, which is structurally the same shape as the Gusto trap I just threw out. The difference is that Rodriguez, Cantillo and Jones all have recent form matching their season form, with no role change underneath. If I'm wrong about that on one of them, it breaks the same way.
Melton's hits under projects 5.14 against a 4.5 line. The projection disagrees with the side; that leg is pure form. It's the weakest thing I'm listing.
I'm still betting hits allowed, which is my least reliable market.
Prices are a few hours old and lineups hadn't posted. Check your book, especially Singer, whose game starts soonest.

Two days in I'm 12-13 on legs and down 0.92 units. Results tonight, wins and losses both.

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u/nrichardson5 — 11 days ago

▲ 7 r/sportsbetting

8/8 picks, parlays, writeup

Full pitcher card tonight across strikeouts, outs recorded and hits allowed. My projections flagged a bunch of these, but I threw out six of them on bullpen and weather, so I want to show the reasoning rather than just dump numbers.

Bullpen state is doing most of the work here

A projection model looks at the pitcher. It doesn't look at whether his manager has anyone left to bring in.

When a bullpen is taxed, meaning arms unavailable and a heavy pitch count over the last two days, the starter gets a long leash. He wears it. That pushes outs up and hits up, and it quietly guts every under you might want on that pitcher. When the pen is fresh, the hook comes quick and the reverse applies.

That single check flipped or killed six legs my numbers liked.

Thrown out:

Chris Sale under 17.5 outs and under 7.5 K. Atlanta's pen has two arms unavailable and 205 pitches over two days. He is going deep whether it's going well or not. Both unders are fighting the manager.
Gage Jump under 5.5 hits. Boston pen taxed, two unavailable. Longer outing, more contact.
Seth Lugo under 6.5 hits. Kansas City pen taxed, 184 pitches. Same problem.
Sandy Alcantara under 5.5 hits. Miami pen taxed, 176 pitches. Same problem.
Aaron Nola over 4.5 K. My own numbers wanted the K over and the outs under on the same start, which is incoherent. There's a 36% chance of rain in Philadelphia. A rain-shortened start argues under, so I took the outs under and dropped the K.

Upgraded on the same logic:

Taj Bradley over 16.5 outs. Minnesota's pen is taxed with two unavailable. Long leash, and he's cleared this in 7 of 10.
Chris Sale over 4.5 hits. The exact same taxed pen that kills his unders makes this better. More innings, more contact, and he's over in 7 of 10.

That Sale pair is the clearest example of the whole idea. One bullpen fact kills two of his legs and improves a third.

The card

Proj is my projection, L10 is how often he cleared that exact number in his last ten.

Pitcher	Market	Pick	Price	Proj	L10	Read
Jake Bennett	K	U 4.5	+120	4.14	3/10	biggest edge on the board
Yoshinobu Yamamoto	Hits	U 5.5	-134	5.20	1/10	cleanest form here, fresh pen
Matthew Liberatore	Outs	U 17.5	+111	15.65	2/10	St. Louis pen fresh, quick hook
Taj Bradley	Outs	O 16.5	-101	16.75	7/10	taxed pen, long leash
Chris Sale	Hits	O 4.5	+120	4.78	7/10	taxed pen, wears it
Aaron Nola	Outs	U 17.5	+106	16.71	3/10	36% rain
Peter Lambert	Outs	O 16.5	-108	16.54	8/10	best form on the card
Peter Lambert	K	O 4.5	-120	5.25	8/10	same start, same direction
Kyle Bradish	K	U 5.5	-127	5.31	2/10	fresh pen, coherent
Andrew Alvarez	Outs	U 14.5	+106	15.16	2/10	weakest leg here, see below

The three I like most:

Jake Bennett under 4.5 K. He's cleared it three times in ten and not once in his last five, projects 4.14. The honest headwind is that Boston is 8th in the league in strikeout rate, and Oakland's pen is mildly taxed, so a longer start is the risk.

Yamamoto under 5.5 hits. One for ten. The Dodgers pen is fresh at 53 pitches over two days, so there's no reason he gets stretched. Phoenix is 111 degrees tonight, which argues for offense, and that's the one thing giving me pause.

Taj Bradley over 16.5 outs. Seven of ten, projects 16.75, and the bullpen behind him is short two arms. Everything points the same way.

Parlays

Realistic single-book payout first, my cross-book feed in parentheses. Trust the first one.

B. One leg per market, no bullpen conflict, 3 legs, +577 (feed +711)

22.0% against a market 11.7%

Jake Bennett U4.5 K (+120), 4:10 ET
Yoshinobu Yamamoto U5.5 hits (-134), 8:10 ET
Matthew Liberatore U17.5 outs (+111), 7:15 ET

Best probability-to-price on the page. This is the one I'm playing.

A. Pure bullpen read, 3 legs, +663 (feed +824)

17.0% against a market 10.2%

Taj Bradley O16.5 outs (-101)
Matthew Liberatore U17.5 outs (+111)
Chris Sale O4.5 hits (+120)

Every leg here is driven by pen state rather than by the projection. If you think the bullpen angle is the real edge, this is the cleaner expression of it.

C. Four legs, +1145 (feed +1513)

12.7% against a market 5.9%

B plus Taj Bradley O16.5 outs

D. Lambert same game, 2 legs, +205 (feed +253)

38.2% against a market 28.4%

Peter Lambert O16.5 outs and O4.5 K

Correlated on purpose. He's 8 of 10 on both numbers, and a deep start and a strikeout total are the same outcome described twice. Books price this as a same-game parlay so it'll come back shorter than a straight multiply.

E. Bennett, Bradley, Yamamoto, 3 legs, +541 (feed +665)

21.8% against a market 12.4%

One leg per market again, swapping Liberatore for Bradley if you'd rather have the taxed-pen leg than the fresh-pen one.

F. Short starts, 3 legs, +643 (feed +795)

17.8% against a market 10.6%

Aaron Nola U17.5 outs (+106) · Matthew Liberatore U17.5 outs (+111) · Andrew Alvarez U14.5 outs (+106)

G. Plus money throughout, 4 legs, +1494 (feed +2004)

9.3% against a market 4.5%

Bennett U4.5 K · Sale O4.5 hits · Liberatore U17.5 outs · Nola U17.5 outs

Every leg plus money and the longest shot here.

All legs are in separate games except D, which is deliberate. Sale is at 3:05 ET, so that's the clock on anything containing him.

Where I think this goes wrong

Alvarez under 14.5 outs projects 15.16, which is above the line. That leg rests entirely on him going under in 8 of his last 10, with nothing else supporting it. It's the weakest thing on my card and I'd drop it before anything else.
Two of my legs are hits allowed, which is my least reliable market. If tonight goes badly, Yamamoto and Sale are where I'd expect it.
Bennett's matchup argues against him. Boston strikes out less than most, and I'm betting the under anyway on form and price. That's a real conflict, not a detail.
My prices are a few hours old and lineups hadn't posted when I built this. Check your book, especially Bennett, where the whole case is about twelve points of edge that one line move erases.

Results tonight, wins and losses both.

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u/nrichardson5 — 12 days ago

▲ 0 r/test

Model parlays + explanation

Long-ish post. The parlays are at the bottom if you want to skip the methodology, but the methodology is the part that actually matters.

I run a projection model for pitcher strikeouts, outs recorded, and hits allowed. Today I pulled the full slate (15 games, 25 starters) and went looking for parlays. The first pass handed me a board with +99% edges on it. That's not a model finding value, that's a model being wrong. So here's what I had to fix first.

## Trap 1: the model doesn't know a guy got promoted

Projections are built off season and recent per-game averages from the game log. That means when a reliever makes his first real start, the model still thinks he's a reliever.

Daniel Lynch IV's last ten appearances, in innings: 1.0, 1.1, 1.0, 2.0, 1.0, 1.0, 1.0, 0.2, 1.0, 1.0.

The book has him at **8.5 outs**. My model projected **2.89** and spat out a 99.9% confidence on the under. That is not an edge. That is the model not knowing he's starting tonight.

Same story for George Klassen (2 games in the sample, both from *April*, model says 7 outs against a 14.5 line) and Carmen Mlodzinski (median 9 outs across ten appearances, priced at 12.5).

These three were the **top five "edges" on my raw board.** All garbage. I now gate on: at least 8 recent games, median outs of at least 11, and a last outing within 12 days. That killed 5 of 25 pitchers.

## Trap 2: aggregated lines aren't real lines

My prop feed stores "best of N books" pricing, meaning the best over price from one book and the best under price from another.

I checked the two-way overround on all 125 lines. **45% of them came out below 1.00.**

An overround below 1.00 is a risk-free arb. It cannot exist at a single book. What it means is that I was measuring my edge against a price nobody will actually give me. My first EV pass showed **+307% on a 4-leg parlay.** Cool. Also fake.

The fix is to devig each line properly, using `imp_over / (imp_over + imp_under)`, then add roughly 4% hold back in to model an actual single-book price.

## Trap 3: my probabilities aren't calibrated to these lines

After all that, the model was still spitting out 65-74% on legs the devigged market had at 42-48%. I don't believe I'm that much sharper than the market. So I shrink every model probability 50% toward the market number before sizing anything.

Everything below uses the shrunk number. The market column is what the devigged line implies.

## The honest headline: the strikeout market is the tightest one on this slate

I went in wanting K parlays. The K market is where the value *isn't* today.

Almost every strikeout leg with model edge has a matchup headwind:

* Wheeler projects 6.54 K, but Toronto is **30th of 30** in strikeouts, a K-factor of 0.858

* Gilbert faces the **29th**

* Sasaki faces the **28th**

And the guys whose K matchup *and* projection actually agree (Rasmussen, Leahy, Messick) are priced at roughly zero edge. The market has this market figured out.

The real edges today are in **hits allowed** and **outs recorded**.

## The board

|---|---|---|---|---|---|---|---|---|

| Keider Montero | Hits | U 4.5 | +125 | 3.80 | 1/5 | 3/10 | 41.7 | 54.8 |

| Shane Baz | Hits | O 5.5 | +102 | 6.20 | 5/5 | 8/10 | 47.6 | 60.8 |

| Nathan Eovaldi | Hits | O 5.5 | +125 | 6.07 | 4/5 | 7/10 | 41.9 | 53.8 |

| Roki Sasaki | Outs | O 15.5 | +102 | 15.94 | 4/5 | 7/10 | 48.5 | 56.6 |

| Shane Drohan | Hits | O 4.5 | +100 | 4.48 | 4/5 | 8/10 | 51.2 | 59.7 |

| Max Fried | Outs | U 17.5 | +102 | 15.16 | 1/5 | 4/10 | 49.6 | 57.2 |

| Zack Wheeler | K | O 6.5 | +120 | 6.54 | 3/5 | 6/10 | 43.2 | 50.2 |

| Tyler Phillips | K | U 4.5 | -152 | 4.05 | 1/5 | 2/10 | 57.6 | 64.3 |

L5 and L10 are how often he cleared that exact line in his last 5 and last 10.

## The parlays

Payouts are listed as **realistic single-book price, then what my aggregated feed claims.** Reality will be closer to the first number. Win percentage is mine against the market's.

### A. Model's best, 3 legs, 3 games, roughly +708 (feed says +818)

**18.9% against a market 9.6%**

* Keider Montero U4.5 hits (+125), 10:15 ET

* Shane Baz O5.5 hits (+102), 8:15 ET

* Roki Sasaki O15.5 outs (+102), 9:40 ET

Montero only projects 13.8 outs, so a short leash caps the hit total. Honest counterpoint: SF is 6th in the league in hits per game, so the matchup is a headwind. Baz is 5/5 in his last five and 8/10 in his last ten.

### B. Strikeout-anchored, 3 legs, 3 games, roughly +483 (feed says +598)

**18.0% against a market 13.7%**

* Zack Wheeler O6.5 K (+120), 6:40 ET

* Logan Gilbert O5.5 K (-120), 9:45 ET

* Roki Sasaki O4.5 K (-137), 9:40 ET

**This is the weakest parlay in the post and I'm including it anyway because it's the one everyone asks for.** All three project above their line on form, and Wheeler is at 8.4 K per game over his last five, but all three draw bottom-3 strikeout offenses. At a real price the edge is basically gone. Bet it because you like the arms, not because the model likes it.

### C. Short-start unders, 4 legs, 4 games, roughly +1227 (feed says +1558)

**10.7% against a market 5.5%**

* Max Fried U17.5 outs (+102), 7:05 ET

* Keider Montero U4.5 hits (+125), 10:15 ET

* Zack Wheeler U4.5 hits (+120), 6:40 ET

* Tyler Phillips U4.5 K (-152), 7:10 ET

Fried's last five outs totals: 18, 9, 15, 9, 16. That's a recent average of 13.4 against a season figure of 17.31. Something is up with his workload. Phillips has cleared 4.5 K twice in ten starts *despite* drawing high-K lineups.

### D. Contact-heavy hits overs, 4 legs, roughly +1362 (feed says +1800)

**11.0% against a market 4.9%, the highest EV in the post**

* Shane Baz O5.5 hits (+102)

* Nathan Eovaldi O5.5 hits (+125)

* Shane Drohan O4.5 hits (+100)

* Ryan Feltner O5.5 hits (+109)

**Heads up: Baz and Eovaldi are in the same game**, Baltimore at Texas, 8:15. This has to go in as an SGP and it will price shorter than +1362. The correlation works in your favor though, since both overs cash in the same kind of game.

Eovaldi's batter-vs-pitcher number is the loudest single stat I found today: **.514 across 38 plate appearances** against this Baltimore lineup. Counterpoint, and it's a real one: the O's are 26th in hits per game and their last five sits at 4.2.

### E. Workhorse outs, 3 legs, 3 games, roughly +711 (feed says +876)

**14.8% against a market 9.6%**

* Roki Sasaki O15.5 outs (+102)

* Logan Gilbert O18.5 outs (+130)

* Zebby Matthews O15.5 outs (+110)

Gilbert's last ten outs totals: 16, 18, 21, 19, 21, 22, 20, 18, 17, 21. That is an absurdly stable workload, and he went 20 outs against this same Tampa lineup earlier.

### F. K plus length on the same arms, an SGP, 4 legs, roughly +1054 (feed says +1373)

**10.0% against a market 6.4%**

* Roki Sasaki, O15.5 outs (+102) and O4.5 K (-137)

* Logan Gilbert, O18.5 outs (+130) and O5.5 K (-120)

Deliberately correlated. Deep starts and strikeouts move together, so the true hit rate is better than the 10.0% independent math suggests. Books know this too and will cut the payout accordingly.

### G. Highest hit rate, 3 legs, 3 games, roughly +518 (feed says +612)

**21.4% against a market 12.9%, the best win probability here**

* Tyler Phillips U4.5 K (-152)

* Jack Perkins U5.5 hits (-110)

* Keider Montero U4.5 hits (+125)

Caveat on Perkins: his season average is 2.78 hits but his recent is 4.8, and Boston's last five is 10.2 hits per game. My model's 75% under is anchored to stale form. This is the shakiest leg in an otherwise high-probability ticket.

## Caveats, because you should have them

* **No confirmed lineups yet.** Every lineup in my feed is carried over from the previous game. A scratch or a surprise lefty-heavy card moves the K and outs projections.

* **The payouts assume you get the aggregated prices.** At one book, expect 15 to 25% shorter than the numbers my feed claims. I listed both for that reason.

* **A 4-leg parlay at 11% is still an 89% loss rate.** The model thinking it's underpriced doesn't make it likely. Size accordingly.

* I'm posting the reasoning so you can disagree with the legs, not so you can tail blind. If you think I'm wrong about the Eovaldi spot, I'd genuinely like to hear it. The O's last-five hits trend is the thing nagging at me.

Will post results tomorrow, wins and losses both.

reddit.com

u/nrichardson5 — 13 days ago

▲ 1 r/sportsbetting+1 crossposts

Today's picks round robin

Sean Burke 6+ Ks

Summary: Best combination of form + workload. Boston’s recent dip in strikeouts is a minor negative, but Burke’s consistency outweighs it.

Pitcher Form

Season avg: 6.36 Ks
Recent avg: 9.0 Ks
Cleared 6+ in 9 of his last 10
Recent results: 7, 6, 8, 6, 8, 11, 9, 5, 10, 10

Boston Strikeout Trend

Season: 8.22 Ks/game
Last 10: 8.3
Last 5: 7.0

Workload

Outs line: 17.5
Projected outs: 18.08
Recent avg: 17.7 outs / 5.9 IP

BvP

35.7% K rate (14 PA — small but positive)

Takeaway: Burke’s form + workload + 9/10 clearance rate make this the strongest leg.

Paul Skenes 7+ Ks

Summary: Best opponent trend. Workload is the only concern.

Pitcher Form

Season avg: 6.78 Ks
Recent avg: 7.4 Ks
7+ in 8 of his last 10
Had 7 Ks vs Milwaukee previously

Milwaukee Strikeout Trend

Season: 8.17 Ks/game
Last 10: 7.7
Last 5: 9.6

Workload

Outs line: 17.5
Projected outs: 16.45
Recent avg: 16.4 outs / 5.47 IP

BvP

30.6% K rate
72 PA (best sample of the four)

Takeaway: Workload is light, but his K‑per‑out rate still projects ~7.5. Strong matchup + strong BvP.

Jake Irvin O3.5 Ks

Summary: Season-long matchup looks good, but Philly’s recent strikeout collapse is a major warning sign.

Pitcher Form

Season avg: 4.92 Ks
Recent avg: 4.0 Ks
Cleared 3.5 in 8 of his last 10

Philadelphia Strikeout Trend

Season: 8.76 Ks/game
Last 10: 6.8
Last 5: 5.6

Workload

Outs line: 14.5
Projected outs: 13.63
Recent avg: 14.3 outs / 4.77 IP

BvP

15.3% K rate
124 PA (meaningful + negative)

Takeaway: This play survives because the line is only 3.5. Metrics are mixed at best.

Tomoyuki Sugano O2.5 Ks

Summary: Weak matchup, but lowest threshold + strong workload projection.

Pitcher Form

Season avg: 3.05 Ks
Recent avg: 3.4 Ks
3+ in 7 of his last 10

Tampa Bay Strikeout Trend

Season: 7.23 Ks/game
Last 10: 7.4
Last 5: 7.2

Workload

Outs line: 15.5
Projected outs: 16.97
Recent avg: 16.7 outs / 5.57 IP

Colorado’s bullpen is classified as taxed, potentially extending his leash.

BvP

0% K rate
8 PA (too small to matter)

Takeaway: Low threshold + strong workload keep this playable despite matchup concerns

u/nrichardson5 — 15 days ago

▲ 6 r/u_nrichardson5+1 crossposts

Today's picks

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Results from yesterday 1/3 on parlays should have been 2/3 but ranger suarez pulled after 63 pitches

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