Tennis: Market Dynamics
Markets analysed
9
Avg lead changes
2.8
per market
Avg probability swing
50%
winner min to loser max
One-sided markets
33%
never changed leader
This category covers prediction markets related to tennis. The statistics below reflect the historical behaviour of resolved markets: how often the leading outcome changed, how wide the probability swings were, and whether reversals tended to happen early or late.
Lead Change Distribution
How many times did the market leader flip during the market's lifetime? Zero means one side dominated from open to close. Higher numbers mean contested, back-and-forth outcomes: the kind that create the most trading opportunity.
Number of lead changes per market
Probability Range by Market
Each bar is one resolved market. The coloured zone spans from the winner's lowest point (left edge) to the loser's peak (white marker) — this is where a reversal was possible. The dim green tail extends from the loser's peak to 100%, where the winner eventually resolved. A wide red zone means the market was nearly overturned.
When Did Reversals Happen?
Each dot is a market that had at least one lead change. The x-axis shows when the last reversal happened as a percentage of the market's total lifetime. Points in the shaded red zone (75-100%) reversed in the final quarter, the highest-risk window for certainty sellers.
Review the lead change histogram and probability range chart below to identify patterns specific to this category. Categories with high average lead changes and wide probability ranges offer more opportunities for active trading strategies.
Calibration Curve
When a Tennis market prices the favourite at 80%, does it actually win 80% of the time? Points below the dashed diagonal mean the market is overconfident. Each coloured line shows calibration at a different stage of the market's lifetime; systematic deviation is where the edge lives.
Upset Probability Matrix
If the favourite is at X% at this stage of the market, how often does the underdog still win? Red cells are where the market is systematically overconfident. The Late (80%) row is the most actionable: this is where traders decide whether to fade certainty or follow momentum.
| When evaluated | 50–60% | 60–70% | 70–80% | 80–90% | 90–100% |
|---|---|---|---|---|---|
| Early (10%) | 67% upset 3 markets | 0% upset 3 markets | 100% upset 2 markets | — | 0% upset 1 markets |
| Midpoint (50%) | 67% upset 3 markets | 0% upset 2 markets | 67% upset 3 markets | 0% upset 1 markets | — |
| Late (80%) | 100% upset 1 markets | 0% upset 2 markets | 40% upset 5 markets | — | 0% upset 1 markets |
Where Smart Money Enters
Every $10,000+ trade on a Tennis market plotted by two dimensions: what probability was the market at when the trade happened (x-axis), and how far through the market's lifetime it was placed (y-axis). Brighter cells mean more large-capital entries at that combination. A cluster at low probability early suggests informed contrarian positioning. A cluster at high probability late suggests momentum-following by large accounts.
Most Dramatic Resolved Markets
Ranked by probability swing (the gap between the winner's lowest point and the loser's highest point). These are the markets where the eventual winner was most seriously challenged.
| Market | Lead changes | Winner low | Loser peak | Swing |
|---|---|---|---|---|
| Roland Garros ATP: Alexander Bublik vs Jan-Lennard Struff | 1 | 22% | 79% | 57pp |
| Roland Garros ATP: Adolfo Vallejo vs Moise Kouame | 3 | 25% | 76% | 51pp |
| Roland Garros ATP (Doubles): Paul/Willis vs Chandrasekar/Yuzuki | 1 | 47% | 53% | 6pp |
| Roland Garros WTA: Completed Match: Iva Jovic vs Alexandra Eala | 10 | 49% | 52% | 3pp |
| Roland Garros WTA: Completed Match: Talia Gibson vs Yulia Putintseva | 6 | 49% | 52% | 3pp |
| Roland Garros ATP: Completed Match: Zachary Svajda vs Adam Walton | 4 | 50% | 51% | 1pp |
| Roland Garros ATP: Cristian Garin vs Learner Tien | 0 | 56% | 45% | -11pp |
| Roland Garros ATP: Ignacio Buse vs Andrey Rublev | 0 | 64% | 37% | -27pp |
| Roland Garros WTA: Aryna Sabalenka vs Daria Kasatkina | 0 | 90% | 11% | -79pp |
Act on these patterns in real time
Polyshadow signals fire when smart money bets match the patterns described above: late-money whale positions, new-account bets, and convergence across unconnected wallets.
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