Recipe

Size a slate from a spreadsheet

Keep your slate in a spreadsheet, export it as CSV, and get a CSV of stakes back.

Needs KELLYIQ_API_KEY. One optimize per run, whatever the number of rows, up to your plan’s picks per slate (Free 3, Bettor 12, Sharp and Pro 50). The sample has 3 rows, so it runs on every plan.

The input

One row per bet. sport is a key from GET /v1/sports, such as baseball_mlb. confidence is one of STRONG_FADE, MODERATE_FADE, SLIGHT_FADE, MARKET, SMALL_EDGE, MODERATE_EDGE or STRONG_EDGE.

sport,team,opponent,odds,opponent_odds,confidence
baseball_mlb,Dodgers,Padres,-145,125,STRONG_EDGE
baseball_mlb,Cubs,Cardinals,120,-140,MODERATE_EDGE
baseball_mlb,Mets,Braves,135,-155,SLIGHT_FADE

The script

slate-from-csv

"""Size every bet in slate.csv and write the stakes to stakes.csv.

slate.csv columns: sport,team,opponent,odds,opponent_odds,confidence
"""
import csv
import os
import requests

API = os.environ.get("KELLYIQ_API_BASE", "https://api.kellyiq.com")
KEY = os.environ["KELLYIQ_API_KEY"]
BANKROLL = 1000

# utf-8-sig also reads the byte-order mark Excel puts at the start of "CSV UTF-8" files.
with open("slate.csv", newline="", encoding="utf-8-sig") as f:
    rows = list(csv.DictReader(f))

picks = [
    {
        "id": str(i),  # the row number, so results map back to rows
        "sport": r["sport"],
        "team": r["team"],
        "opponent": r["opponent"],
        "odds": int(r["odds"]),
        "opponentOdds": int(r["opponent_odds"]),
        "confidence": r["confidence"],
    }
    for i, r in enumerate(rows)
]

resp = requests.post(
    f"{API}/v1/optimize",
    headers={"Authorization": f"Bearer {KEY}"},
    json={"bankroll": BANKROLL, "picks": picks},
    timeout=60,
)
if not resp.ok:
    # A VALIDATION_ERROR lists every problem; picks[2].odds is the third data row.
    raise SystemExit(f"HTTP {resp.status_code}: {resp.text[:500]}")
result = resp.json()

stakes = {t["id"]: t["stake"] for t in result["allocation"]["stakes"]}

with open("stakes.csv", "w", newline="", encoding="utf-8") as f:
    out = csv.writer(f)
    out.writerow(["team", "odds", "stake", "note"])
    for p in result["picks"]:
        out.writerow([p["team"], p["odds"], stakes.get(p["id"], 0), p["reason"] or ""])

print(f"Wrote stakes.csv: {len(stakes)} of {len(picks)} bets, "
      f"${result['allocation']['totalStake']:.2f} in total (seed {result['seed']})")

How it works

Each pick’s id is its row number. The API echoes ids back unchanged, which is how stakes find their rows again.
Picks with no stake in the allocation get 0 and the reason in the note column. A fade usually comes back NO_EDGE.
If a row is wrong, the error names it by position: picks[2].odds is the third data row.
Saved from Excel as “CSV UTF-8”? Both scripts handle the marker Excel adds at the start of the file.
To rate bets with your own win probabilities instead (Bettor and up), send probability in place of confidence on every pick. See the reference.

Same answer twice →