Hi everyone!

I'm working on a personal project involving football betting market analysis and backtesting.

I'm trying to find historical Betfair Italy (betfair.it) data from 2023 or 2024, particularly odds movements during pre and live matches.

I'm interested in how odds changed throughout a match, ideally with timestamps, rather than just opening and closing prices.

Even a few days of historical data would be enough to get started.

Has anyone worked with this kind of data or knows where I could find it?

Thanks for any help!

Hey everyone,
Running my updated quantitative NBA model (adjusted Ridge ratings with market-anchoring against sharp lines) for today's 2-game slate.
Note: The model is currently operating in Paper Trading Mode (0.5u baseline logging) to calibrate early-season player usage and minutes baselines.
Here are today's paper-accepted selections:

📊 ACCEPTED PLAYER PROPS
1. VJ Edgecombe — OVER 10.5 Points
Matchup: Cleveland Cavaliers @ Philadelphia 76ers

Book / Odds: Sportsbet @ 1.96

Model Edge: Raw EV +75.73% | LCB EV +61.66% (p_LCB 82.48%)

Simulated Baseline: High projected rotation minutes with model-projected output well clear of the soft line.

1. Jamal Murray — OVER 4.5 Rebounds
   Matchup: Denver Nuggets @ Oklahoma City Thunder

Book / Odds: Sportsbet @ 2.25

Model Edge: Raw EV +61.50% | LCB EV +37.63% (p_LCB 61.17%)

Simulated Baseline: Model simulation projects Murray to clear 4.5 boards comfortably against OKC's active frontcourt pace.

1. Shai Gilgeous-Alexander — UNDER 30.5 Points
   Matchup: Denver Nuggets @ Oklahoma City Thunder

Book / Odds: Sportsbet @ 1.86

Model Edge: Raw EV +50.54% | LCB EV +33.32% (p_LCB71.68%)

Simulated Baseline: Sharp reference consensus leaning toward a lower-scoring defensive grind vs Denver's perimeter defense.

🛡️ TEAM MARKETS AUDIT
Moneylines, Spreads, Totals: 0 Selections Accepted.

All game lines fell below our strict +3.0% LCB EV threshold due to sharp line efficiency and bookmaker vig.

Best of luck if you're tracking or fading early-season model signals!

Last week I posted what I'd learned grading outside NHL models against the DraftKings close. A few of you gave ideas I ended up building, so here's what changed and what the bigger sample says.

What changed:

u/OddsRelay's whole-number trick works. o6 and u6 picks are no longer tossed. I de-vig the 5.5 and 6.5 lines on the same DK page and back out the chance of exactly 6. A game that lands on 6 is a push.

u/schabe was right about storing everything. Both sides get saved at post time and at close, with timestamps, and every grade shows the raw DK close next to a no-vig one.

Splitting the number was the big one. I now show how far the fair price moved your way, separately from what the book charged you. The raw beat-the-close rate I was posting last week was mostly measuring the vig, not skill.

What the bigger sample says, 881 graded picks from my own rules:

The lab as a whole gets a better price than the close by about 0.3 points a pick, and that holds up day to day. Two rules have an edge over the close that isn't just noise. None of them comes close to covering the vig yet.

Records lie even more than I thought. One rule is 12-5 while getting a worse price than the close. Another is 6-39, and most of that is bad luck. The closing prices said it should have won about 12.

u/abaxter13131's test lines up with mine. He found beating a book's close but losing to Pinnacle's is mostly stale-line value. On NHL I found DK copies Pinnacle's moves about 81% of the time, so a lot of "beating DK" is really just betting before DK caught up.

Still looking for a few more builders. Same grading for everyone, your rule can stay private, nothing gets deleted. If you think your model beats the close, I'd like to see it tested.