Stop relying on gut feeling alone. In the Analytics section on 100s, you'll find in-depth match data, team form, head-to-head records, and a full picture of odds movement. Make decisions based on facts and improve your chances of winning.
What 100s Covers in Its Match Analysis
Results from the last 5–10 matches, win/loss streaks, and overall performance trends.
Detailed results and statistics from every past match between the two sides.
How odds have shifted from market open through to kick-off.
Pitch conditions, weather, home/away advantage, and team absences.
Individual player strike rates, averages, recent form, and venue-specific performance.
Identifying events where the true probability is higher than what the market odds suggest.
Match analysis powered by Poisson distribution, Elo ratings, and other mathematical models.
How a team responds under pressure, their morale, and experience in big-match situations.
Many bettors make decisions purely based on reputation — "It's a big club, they'll win." In practice, that thinking often turns out to be wrong. The analysis section on 100s helps you avoid exactly that mistake.
How a team has performed over their last five matches, their home record, and their history against the opponent — when you look at all of this together, the picture becomes clear. Before every match, 100s presents this data in a straightforward format so both new and experienced bettors can make confident decisions.
100s Uses a Separate Analysis Approach for Each Sport
Pitch report is the first thing 100s focuses on in cricket analysis. Spinners tend to dominate on pitches in Bangladesh, India, and Sri Lanka, giving spin-heavy sides a clear edge. On the other hand, pace-friendly surfaces in South Africa and Australia favour teams with strong fast bowling line-ups.
In T20 cricket, Powerplay and death over performance are critical factors. 100s' analysis shows that teams scoring 50+ runs in the Powerplay win 68% of their matches. Using specific metrics like these makes for far more informed betting decisions.
In Test cricket, five-day weather forecasts, pitch deterioration, and batting depth are all assessed. In ODIs, the focus shifts to run rate, net run rate, and middle-over performance.
| Cricket Metrics | Importance | Impact |
|---|---|---|
| Pitch Conditions | High | +23% |
| Team Form | High | +19% |
| Head-to-Head | Medium | +12% |
| Weather | Medium | +11% |
| Player Absence | High | +17% |
| Venue Record | Low | +8% |
100s uses the xG (Expected Goals) metric for football analysis. xG measures how many goals a team should have scored based on their chances — and often tells you more than the actual scoreline does.
For example, a team may have lost 3-0, but their xG was 2.3 against the opponent's 1.1. That means the result was harsher than the stats suggest, so writing them off as underdogs in the next match would be a mistake. 100s' analysis is built to uncover exactly this kind of hidden value.
Home advantage in football increases the probability of winning by an average of 12–15%. This edge is clearly visible in analysis across the Premier League, La Liga, and Bundesliga.
In tennis analysis, surface is a massive factor. The same player can perform very differently on clay, grass, and hard courts. On 100s, each player's record is broken down by surface.
First serve percentage, break point conversion rate, and tiebreaker record are the three most useful metrics in tennis betting. 100s analysis also factors in fatigue from long matches when a player moves into the next round.
Esports analysis is a relatively new field, but 100s is right there. Dedicated analytical frameworks are available for CS2, Dota 2, and League of Legends.
Roster changes, adaptability to new meta patches, and the gap between online and LAN performance are all critical factors in esports betting. This data is regularly updated on 100s.
Odds movements in the betting market are never random. When odds shorten, it means more money is backing that side — typically driven by sharp bettors or well-informed players. You can track these movements on 100s.
Example: Team A's odds were 2.40 in the morning but dropped to 1.75 just before kick-off. That move signals heavy money coming in on Team A. Knowing how to read this kind of shift is a key part of any solid betting strategy.
That said, odds movement doesn't always point to the correct outcome — it's one indicator among many. 100s Analysis lets you cross-reference this signal with other data for a more complete picture.
Odds Movement Example (BAN vs IND, T20)
Sample data. Actual odds may vary.
How Head-to-Head Records Are Presented on 100s
| Date | Matches | Format | Result | Margin |
|---|---|---|---|---|
| March 2026 | BAN vs IND | T20I | BAN Win | 7 Wickets |
| Dec. 2026 | BAN vs IND | ODI | IND Win | 45 Runs |
| Oct. 2026 | BAN vs IND | T20I | IND Win | 3 Wickets |
| August 2026 | BAN vs IND | Test | BAN Win | Innings & 48 |
| June 2026 | BAN vs IND | ODI | IND Win | 22 Runs |
Sample data. Live records are updated in real time on the 100s platform.
IND leads in the overall head-to-head record, but BAN has been in strong form at home recently. In T20s, the gap between the two sides is narrow. Pitch and weather could ultimately be the deciding factors here.
Many assume analysis is just about looking at past results. But 100s goes deeper, breaking things down across three layers: historical data, current conditions, and market signals.
The first layer is at least two years of match data. The second brings in the team's current state — who's injured, who's just returned, and how morale is holding up. The third layer covers betting market signals — which way odds are moving and where the money is flowing.
Combining all three layers of data gives you the complete picture. Relying on just one factor is as risky as using all three together is reliable. 100s users who have adopted this approach report a significant improvement in the quality of their betting decisions.
Numbers alone don't tell the full story — context matters too. A team may have lost five matches, but if all five were away games against the top five sides, writing them off based on results alone would be a mistake. 100s Analysis brings these nuances to the surface.
Match statistics, team data, and market information are gathered from multiple trusted sources.
All collected data is cross-checked to filter out errors and outdated information.
Statistical models process the data to determine the probability of each event.
Value bets are identified by comparing model probabilities against bookmaker odds.
Published on the 100s platform in clear language and visual format.
How to Find Value Bets Using 100s Analysis
A value bet is when a bookmaker's odds are higher than the actual probability of an outcome. For example: your analysis puts Team A's win probability at 60%, but the bookmaker is offering odds of 2.0 — which implies only 50%. That's a 10% edge in your favour.
A result above 0 indicates positive value. For example: (2.0 × 0.60) - 1 = 0.20, meaning 20% positive value — a bet that is profitable in the long run.
100s' analytics tool automatically compares market odds against model probabilities to highlight value bets. All you need to do is review the data and make the final call.
Frequently Asked Questions About 100s' Analytics Features
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