KISS MM Podcast โ€” NSBA4 Mid-Season Stat Pack

Run-of-show + curated stats ยท through Week 5 ยท built 2026-07-21

How to use this

Ordered ~90-min rundown. Each stat has the number, a Say line you can read on air, and a confidence tag. You don't have to use everything โ€” the starred โญ items are the ones I'd build segments around.

SOLID safe to state as factCOLOR provisional / directional โ€” frame as funTINY n say the sample out loud

All buzz stats are Weeks 1โ€“5 (30 games). Combine ratings explain only ~6% of game-margin variance, so single-game and title probabilities are genuinely flat โ€” that's a feature of the league, and a running theme for the show. Playoff bracket assumed 1v4/2v3 within-conference (per David, not fully confirmed).

๐Ÿ“‚ Deep dives โ€” full tables & methodology

The run-of-show below is the on-air script. For the complete leaderboards, the math, and the receipts, each area has its own page:

0:00 โ€“ 3:00 ยท COLD OPEN

The hook

Open on the punchline: we ran the entire season through a sabermetrics grinder โ€” win shares, an Elo that ranks every player head-to-head, a prediction market, and 30,000 simulated seasons. Three teasers to promise:

3:00 โ€“ 18:00 ยท SEGMENT 1 ยท THE RACE & THE CHIP

Every team's chance to win it all

30,000 Monte-Carlo sims of the rest of the season + the single-elim playoff. SOLID (as a model; small-season caveat applies).

EastChip%WestChip%
sumin13.8%cryo13.9%
mingle/Yunyi12.2%James W13.6%
dan.k.memes8.3%ChessFun7.9%
xpoes4.1%czz7.7%
GidTheKid24.0%Connor Chang3.2%
Fez_Keyreb3.5%(Stitch)ยฒ3.1%
anurag2.9%jonathan1.8%
Sayโญ "Four teams โ€” cryo, sumin, James W, and mingle โ€” are packed between 12 and 14%. There is no favorite. If someone tells you they know who's winning this, they're lying โ€” even our model gives the top seed a 1-in-7 shot."

Why nobody breaks 15% โ€” the receipts

This isn't the model being wishy-washy. A title requires winning 3 straight single-elimination games, and each is ~50/50 even for the best team โ€” because skill/combine explains only ~6% of a game's margin. External proof: the prediction market went exactly 50% on 60 games. So a dominant team's ceiling is 0.5 ร— 0.5 ร— 0.5 โ‰ˆ 12.5%. Worked example, mingle/Yunyi:

Stagemingle's odds= what?
Make playoffs100%4-1, best in East (85.6% the #1 seed)
Reach the final25.2%win 2 games โ‰ˆ 0.5ยฒ
Win the chip12.2%win the 3rd โ‰ˆ 0.5ยณ
Say "mingle is the best regular-season team in the league and still only wins it 1 in 8 times โ€” not because they're overrated, but because three coin flips is three coin flips. That's the whole story of this playoff."

Talking points

Strength of schedule & luck

18:00 โ€“ 33:00 ยท SEGMENT 2 ยท THE MVP RACE

Win shares & the Buzzer Elo ladder

Win Probability Added (WPA) โ€” "win shares for science bowl"

For every buzz, how much it moved the team's chance of winning, summed over the season. SOLID (30/30 games reconcile).

#PlayerWins added
1Akhil B+1.93
2Vishnu M+1.92
3Suzuko O+1.34
4Kian D+1.28
5Harry G+1.27
Sayโญ "Akhil has personally added almost two full wins of win-probability โ€” more than anyone in the league. That's your MVP frontrunner."

โญ The Buzzer Elo ladder โ€” everyone ranked head-to-head

A Bradley-Terry/Elo rating built from who actually beats whom on tossups, on the floor together. Validated: on 183 head-to-head duels the higher-Elo player held the winning buzz record 96% of the time. SOLID (overall ladder; 44โ€“63 contests each)

#PlayerElo
1Akhil B1782
2Edward C1759
3Kian D1754
4Eric L1731
5Suzuko O1717
Say "This isn't points-per-game โ€” it's who wins the buzzer battle against real opponents. And it agrees with the eye test 96% of the time. Akhil tops this too โ€” WPA and Elo both say he's been the best player alive this season."

โญ Stats lie, Elo doesn't

33:00 โ€“ 48:00 ยท SEGMENT 3 ยท BREAKOUTS & DRAFT VALUE

The steal, the bust, the breakout

โญ Edward C โ€” the breakout of the season (one player, four stats)

Sayโญ "Every single one of our models independently flagged the same guy. Edward has arrived โ€” top-2 by Elo, biggest overperformer in the league, and a mid-round pick playing like a top-3 selection."

โญ Draft steals

PlayerDraftedPlaying like
Uddip K#61#19
Andrew Wen#48#16
Advai S#63 (last!)#33
Edward C#25#3
Say "The last pick of the entire draft โ€” Advai S at 63 โ€” is playing like a mid-second-rounder. Uddip K at 61 is playing like a top-20 pick. Somebody's scouting was asleep."

โญ Draft busts

PlayerDraftedPlaying like
Ryan KarimR1, #13#43
Ishaan KabraR1, #14#38
Edwin He#4#25 (โˆ’21)
Sanjay OrugantiR2, #20#46
Say "Two first-rounders are in the bust bin. Ryan Karim, the 13th pick, is playing like a 43rd โ€” he's also our coldest player and biggest faller, so the arrows are all pointing down." TINY n "Small season, ranks will move โ€” but right now, oof."

Fairness note: 9 drafted players have no game data (likely no-shows) and were excluded, not labeled busts. Captains weren't drafted and are out of this entirely.

Biggest riser

48:00 โ€“ 60:00 ยท SEGMENT 4 ยท BUZZ SCIENCE

Speed vs. knowledge

โญ The rebound rule (the "how do they know that" stat)

On every tossup this season where two people buzzed, the first buzzer was wrong all 179 times. A second buzz only happens because the first person negged and opened the door โ€” and the rebound is converted 76% of the time. SOLID

Sayโญ "Getting to the buzzer first isn't a skill โ€” it's a warning sign. 179 contested tossups this season, and the person who buzzed first was wrong every single time. The game is won on the rebound."

โญ Ice in the veins โ€” Lucas W

Lets the question read to 95% of the way through on his correct buzzes, and still converts 76% (19/25). Pure knowledge, zero panic. TINY n (25 buzzes; buzz-position is descriptive)

Say "Lucas W waits until basically the last word of the question and still beats you three times out of four. That's not speed โ€” that's just knowing it cold."

โญ The Vulture โ€” stealing other people's subjects

Say "Forty percent of Kian's points come on subjects that aren't even his. He's robbing other people's categories."

Discipline & the cost of a neg

60:00 โ€“ 70:00 ยท SEGMENT 5 ยท TEAM ROLES & TRUE HEAD-TO-HEAD

Who's the go-to guy โ€” and who really beats whom

Note: we can't do a real "rivalry" ledger from raw duels โ€” opponents only play once, so any two enemies share just ~4 subject tossups. What we CAN see cleanly is how teammates divide the subjects, and for true head-to-head we lean on the validated Buzzer Elo below.

Team subject specialists (the pecking order) SOLID

Say "Most teams are one person and a couple of role players. cryo is the exception โ€” suzuko is their biology, Edward is their math and physics, and neither steps on the other."

True head-to-head โ†’ use the Buzzer Elo SOLID

For "who actually beats whom," the Buzzer Elo (opponents only, validated 96%) is the honest tool: Akhil B tops it, and it can give an expected win-rate for any matchup. Raw one-off duels are too small to crown.

Per-subject Elo kings COLOR

Fun to name, but each is on ~10โ€“14 contests โ€” call them "current leaders," not settled crowns.

SubjectKingSubjectKing
BioEric LEarth/SpaceVaryan J
ChemKian DMathSohil R
CSOwen MPhysicsLucas W (Harry G close)
70:00 โ€“ 82:00 ยท SEGMENT 6 ยท THE BETTING POOL

What the market knew (and didn't)

Nobody else has this โ€” an internal prediction market on the league, with a full trade ledger.

82:00 โ€“ 90:00 ยท SEGMENT 7 ยท CHAOS CORNER

Throws, runs & the ban wars

Close

Wrap: the league is a coin flip by design, Akhil's the best player, Edward's the breakout, and the chip is anyone's. Predictions for the back half.


Confidence & method: Everything here was run through an edge-case audit โ€” small-sample leaders are tagged, one WPA identity bug was caught and fixed, and provisional per-subject ratings are labeled as such. Numbers are Weeks 1โ€“5; a short season means ranks will move. Chip odds assume a 1v4/2v3 within-conference single-elim bracket (per David, not fully confirmed) and full-strength rosters. Detailed per-stat confidence lives in outputs/podcast/AUDIT.md.