Real Madrid Women 1–1 PSG: AI Football Prediction Software Review
WOMEN'S FOOTBALL | SCREENSHOT CASE STUDY | 22 SEPTEMBER 2026
How does AI football prediction software compare with a reported exact-score result? The new selection record supplied to AI Football Tips shows Real Madrid Women versus PSG as 1–1, with the 1–1 correct-score tip marked won at decimal odds of 7.96. The accompanying Correct Score Software screen lists 1–1 as its third displayed scenario at 10.56%.
QUICK ANSWER — Supplied result: 1–1. Displayed odds: 7.96. Correct Score Software: 1–1 at 10.56%, third behind 0–1 and 0–2. This reviews the supplied records; it does not claim the top-ranked score won.
Update note: this page originally contained an X2-and-goals preview. The new correct-score screenshot and result record were added later. The earlier forecast is retained separately below, rather than retrospectively changing it into a single 1–1 prediction.
Real Madrid Women vs PSG: the supplied 1–1 record
Open the winning-selection screenshot at full resolution. It shows the 1–1 tip, a 1–1 result, the W marker and odds of 7.96. The home-team name is shortened in that original record; the separate software screenshot identifies both teams in full.
Source status: the result and odds come from the supplied selection record. Real Madrid's official preview and UEFA's match page establish the fixture context: the Women's Champions League on 22 September at the Alfredo Di Stéfano. A readable official full-time report was not available in the sources retrieved for this update. We do not invent scorers, match events or independent confirmation of the supplied result.
What the correct-score prediction software actually displayed
Open the original Correct Score Software screenshot to zoom into the numbers. Its full 1906 × 1038 frame is preserved. The key values also appear as text below, so readers do not have to decipher the full spreadsheet on a phone.
Displayed rank | Score / estimate | Against the supplied 1–1 record |
Score 1 | 0–1 / 11.75% | Did not match |
Score 2 | 0–2 / 10.97% | Did not match |
Score 3 | 1–1 / 10.56% | Matched the reported score |
The distinction matters: 1–1 appeared in the three-score list, but was not the first-ranked scenario. The separate record shows 1–1 selected; neither new screenshot independently proves when that selection was made or supplies a complete history of selections, stakes and losses.
The side panels also display Real Madrid Women at 18% and PSG Women at 60%. We retain these as side-panel readings, without inventing a missing draw percentage or treating the neighbouring Yes/No and NB labels as documented probabilities.
Goals predictions: what matched and what missed
A 1–1 score contains two goals. Comparing that supplied result with every full-match goals line gives a more balanced picture than showing only successful signals.
Goal line | Over / Under | At a 1–1 score |
0.5 goals | 93.63% / 6.37% | Over occurred |
1.5 goals | 76.22% / 23.78% | Over occurred |
2.5 goals | 52.15% / 47.85% | Under occurred |
3.5 goals | 29.96% / 70.04% | Under occurred |
Over 1.5 and Under 3.5 aligned with the two-goal record. The small Over 2.5 lean did not: the total shown stayed below three goals. A 52.15% estimate still leaves 47.85% for Under 2.5; the less-favoured outcome remains possible.
There is no contradiction in listing 0–1 among the most likely individual scores while giving Over 1.5 a higher overall probability. A goals market groups many scorelines together; each correct-score percentage refers to one outcome. Related readings should not be counted as independent successful bets or independent proof of accuracy.
7.96 odds: a winning record is not proven value
The record displays 7.96 but does not identify a bookmaker, stake, purchase time or payout. We report the displayed odds without claiming they were available to every reader or calculating an actual customer profit.
For mathematical context, decimal odds of 7.96 correspond to a break-even probability of about 12.56% before costs, calculated as 1 ÷ 7.96. The screen's 1–1 estimate is 10.56%. Those figures alone do not establish a positive pricing edge. One winning outcome does not replace evaluation of a complete record.
Earlier published preview: separate from the new screen
The original article used a different software view. It displayed X2, meaning PSG or draw, and X2 & Over 1.5. Its individual full-match fields showed Over 1.5 at 75.1% and Over 2.5 at 50.6%. Those remain the original figures, distinct from the new Correct Score screen's 76.22% and 52.15%.
A 1–1 score meets X2 and Over 1.5, so the supplied result is consistent with that earlier combination. The earlier page used 1–1 only as an illustration, not as a recommended exact score. Its 1:2 header was treated as ambiguous and is not re-labelled as a successful forecast now.
How to use football prediction software for an honest review
Start with the fixture, the market label and all displayed alternatives. Keep a timestamped copy before the event, then compare it with a separate official result afterwards. Do not remove a higher-ranked score because a lower-ranked one happened to win.
Across a series of matches, record the selection rule, software version, available odds and every outcome, including losses. A screenshot helps explain an interface; it is not an independently audited success rate or proof of an income-producing system.
Read how to get correct-score football predictions and our worked guide to reading AI score probabilities for practical examples. The football-software data guide explains why visible outputs do not establish a particular model architecture or data feed.
Explore Correct Score Football Software
For this style of analysis, our Correct Score Football Software is the relevant store product. Its current product page lists three correct-score scenarios, goals analysis, 1X2 and both-teams-to-score outputs, and describes a Windows/Microsoft Excel digital product. This is our own product recommendation, not an independent software review.
Check current competition coverage, Excel requirements, access duration, price and delivery terms before purchase. Viewing screenshots on a phone does not mean the workbook runs on that phone. Product features and isolated winners do not guarantee accurate forecasts or financial returns.
Questions about the Real Madrid Women–PSG example
Did the software show the 1–1 correct score?
Yes. The new Correct Score screenshot lists 1–1 third at 10.56%, behind 0–1 and 0–2. The separate record shows 1–1 marked won at 7.96 odds. It was not the model's top-ranked score.
Was 1–1 the exact-score tip in the earlier article?
No. The earlier page discussed X2 and goals, using 1–1 as an explanatory example. The Correct Score screen and winning record were supplied later and are identified as an update.
Can this example establish the software's success rate?
No. That requires a defined market, fixed selection rule, dated sample and complete results including losses. A model percentage is not the same measurement as a verified historical hit rate.
Sources and review method
The two newly supplied screenshots are the sources for the correct-score percentages, 1–1 record and 7.96 odds. The earlier published screenshot supplies the archived X2-and-goals view. Club and UEFA sources verify fixture identity only, not the winning selection. We have not inferred software internals, fabricated a pre-match timestamp or reconstructed truncated image text.
Browse our AI football prediction articles for more original examples and reading guides.
Responsible prediction notice
18+ only. Football predictions are uncertain. This educational article does not promise winnings, accuracy or financial returns. Betting can cause financial harm. Do not chase losses or use money you cannot afford to lose.