Tackles — the highest-volume outfield market on the board
A player makes more tackles in a match than shots. Across 266,866 player-matches the average is 1.46 tackles per 90 against 1.12 shots and 1.03 fouls committed, so the tackle lines turn on a steadier number than the shot markets — and a steadier number is easier to price.
How SharpXI models it
We build a recency-weighted tackles-per-90 rate for the player, shrink it toward a positional prior when the sample is thin, scale it by projected minutes, then apply an opponent factor: how many tackles sides tend to make against that opponent. A Negative Binomial distribution gives the probability of reaching each line, and that number is compared with the probability the price implies.
Go deeper: How a bet builder is priced
Where the value tends to sit
Tackles belong to the players doing the defensive work — full-backs and holding midfielders — rather than the forwards the market follows most closely. The line matters: a starter clears 1+ in roughly six matches in ten, while 2+ turns on minutes and on whether a side spends the afternoon chasing the ball.
Ligue 1 — how this market behaves
Across 1,136 graded Ligue 1 predictions from the 26/27 season, a player recorded 1+ tackle in 60.1% of appearances. SharpXI's model beat that base rate by 22.1% here, against UEFA Champions League 23.2%, Bundesliga 23.1%, UEFA Europa League 22.4%, Serie A 22.4%, Premier League 22.3%, La Liga 20.2%, UEFA Nations League 20.1%, Championship 19.4% and EFL Cup 18.6%
Ligue 1 leaders this season
In the 26/27 Ligue 1 season, Lamine Camara (AS Monaco) leads for tackles at 5.20 per 90, ahead of Cristian Cásseres Jr. (4.40) and Pierre Lees Melou (4.20). Rates are per 90 minutes, minimum 450 played, from completed matches.
Per-90 rates across the league (26/27 season, minimum 450 minutes) — the players whose underlying numbers drive this market.
| Player | Team | Per 90 | 1+ hit |
|---|---|---|---|
| Lamine Camara | AS Monaco | 5.20 | 100% |
| Cristian Cásseres Jr. | Toulouse | 4.40 | 100% |
| Pierre Lees Melou | Paris FC | 4.20 | 80% |
| Kévin Danois | Auxerre | 3.20 | 80% |
| Adrien Monfray | Troyes | 3.00 | 100% |
| Adama Camara | Paris FC | 2.80 | 80% |
| Zachary Athekame | Olympique Lyonnais | 2.50 | 100% |
| Anis Ouzenadji | Troyes | 2.40 | 100% |
| Branco Van den Boomen | Angers | 2.20 | 100% |
| Tiago Santos | Lille | 2.00 | 80% |
| Willian Pacho | Paris Saint-Germain | 2.00 | 80% |
| Matthieu Udol | RC Lens | 1.92 | 83% |
Frequently asked
What does 1+ tackles mean?
It is a bet that the player makes at least one tackle in the match. 2+ means at least two. SharpXI models the probability of each line separately.
Why does 3+ tackles show a hit rate but no value verdict?
Because the model does not beat the base rate at that line. Measured across seven leagues, 3+ tackles scored between 2.3% and 8.1% skill and calibrated poorly, so the line is shown with its record and nothing else — a hit rate we counted, rather than a verdict we would not trust. 3+ shots on target is handled the same way, for the same reason.
How does SharpXI decide a tackles price is value?
It compares its own modelled probability with the implied probability of the price as offered. When the model's number is higher, the leg is flagged as value, with a confidence rating from the sample size. ⚠ Tackles is quoted one side only, so the margin cannot be stripped out and the edge shown is before the margin, not after.
SharpXI is a statistical tool, not a betting operator, and no model guarantees a result. The honest scoreboard is closing-line value over a large sample. 18+ — please gamble responsibly.