Projected points, recent match form and per-90 stats for every player at all 20 Premier League clubs. To score your own fifteen, use Rate My Team.
Every projection, every form line and the whole player pool. Pro extends the window to six gameweeks — the horizon a wildcard or a fixture swing is actually planned over.
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Every Fantasy Premier League decision comes down to the same question: which of these two players scores more points over the next few weeks? Form tables and total points answer that badly, because they describe what has already happened rather than what is coming. These tools are built around projected points instead, so you can compare a premium midfielder with a kind run of fixtures against a budget defender whose club has three away trips to the top six.
Almost all of it is free, and none of it needs an account. The explorer below, recent match form for every player, and projected points for the next three gameweeks are yours without paying anything. That is deliberate: the sites most managers use for this charge for numbers that are not especially expensive to produce. To have your own fifteen scored, use Rate My Team.
The team rater pulls in your latest fifteen and scores it. The verdict answers the three questions that actually decide a gameweek: who to captain, which of your starters is quietly costing you points, and what a single transfer would gain. Every suggested transfer is a legal one — inside your remaining budget and the three-per-club limit — and is ranked by how much it moves your projected total rather than by how good the incoming player looks in isolation.
Alongside the projection, every player carries their last six Premier League matches. Not points, which one lucky afternoon distorts for a month, but the underlying actions: shots, shots on target, expected goals, chances created, defensive actions and minutes, match by match. The form window follows the player rather than the calendar, so early in a season it reaches back into the last one instead of pretending two games is a sample.
Those matches are reported the way a betting market reports them, as how often a player cleared a line rather than only what they averaged. "Two or more shots in five of his last six" is a far more useful sentence than "averages 2.6 shots", because the average is the same for a player who is consistent and a player who had one enormous game and five quiet ones. The same numbers, across every major league and every market, are in the Player Props Tool.
Each player is reduced to a set of per-90 rates: expected goals, expected assists, defensive actions, saves, bonus points and cards. Those rates come from the season just gone, blended toward the current campaign as minutes accumulate.
Those rates are then adjusted for each upcoming fixture and converted into points with the official scoring rules, including the two-point defensive contribution threshold. The fixture adjustment comes from the betting market rather than the Premier League's own difficulty ratings, which are set in July and never move: bookmaker prices are stripped of their margin and solved for how many goals each side is expected to score. Games the market has not yet priced are corrected by how far our own estimate sat from the market on the games it has. Clean sheets are modelled from each club's expected goals conceded rather than assumed, and block-scored categories such as saves are counted in whole blocks the way the game actually pays them.
Summer signings and promoted-club regulars are the hardest players to price, because the FPL API holds no record of them. Most tools fall back on the player's price tag, which is why an entire promoted squad tends to project as an anonymous average of whoever costs the same. FPL's own expected points figure has the same problem before a ball is kicked: it compresses every player into a nought-to-four range, so Erling Haaland and a £4.0m goalkeeper are handed the same number.
We project those players from what they actually did in the league they arrived from. Output does not transfer one for one, so each league carries a multiplier measured from every player in our data who has made that exact move: a goal in the Championship is worth about 0.77 of a Premier League goal, one in the Eredivisie about 0.59, and one in La Liga about 0.91. Tested by holding each past season out in turn, this predicts a newcomer's goals and assists per 90 with roughly a third less error than assuming the average new arrival.
Anyone in that position carries a NEW tag in the tables above. Open their profile and it will tell you which league the projection is built on, how many minutes it rests on, and how far their numbers have been marked down. You can also tick New to the Premier League in the filters to see only those players. Their playing time is the one thing still worth your own judgement: the model assumes a Championship regular keeps starting, which holds until their new club signs over the top of them.
Fed back over the previous season, the model reproduces about 96% of the points those players really scored, with a median error near 10% per player. It deliberately leans on underlying numbers rather than raw output, so a striker who over-performed their expected goals will project slightly below what they managed last year.
Sort the entire player pool by projected points, points per million, expected goals per 90, defensive actions or ownership, and filter by position, club, price and availability. The fixture ticker shows the next six gameweeks coloured by difficulty, with blanks and double gameweeks handled properly. Click any player to see exactly where their projection comes from, component by component.
A differential is only useful when low ownership is attached to a good pick. The differentials view starts with available players expected to play meaningful minutes, limits the pool to players owned by under 10% of the game, then ranks them by projected points. That separates genuinely overlooked players from cheap reserves who are unpopular for a reason. The percentage is current ownership, not a trend: rising and falling labels will only be added once enough ownership history has been collected to support them.
Ownership is the clearest picture of what the field is doing, and the gap between a player's ownership and their underlying numbers is usually where a differential hides. These are the thirty most-owned players in the game, with the per-90 rates behind them. Every rate is adjusted for how many minutes it is based on, so a substitute with one tackle in one minute does not appear at the top of the defensive columns.
| Player | Club | Pos | Price | Owned | Points | Mins | xG/90 | xA/90 | DC/90 |
|---|---|---|---|---|---|---|---|---|---|
| João Pedro Junqueira de Jesus | CHE | FWD | £7.7m | 72.4% | 21 | 270 | 0.15 | 0.01 | 0.78 |
| Erling Haaland | MCI | FWD | £15.5m | 71.2% | 24 | 270 | 0.19 | 0.04 | 1.67 |
| Riccardo Calafiori | ARS | DEF | £5.7m | 47.7% | 22 | 236 | 0.04 | 0.05 | 1.04 |
| Bruno Borges Fernandes | MUN | MID | £12.0m | 46.2% | 27 | 270 | 0.17 | 0.06 | 1.78 |
| David Raya Martín | ARS | GKP | £6.0m | 38.9% | 15 | 270 | 0.00 | 0.00 | 0.00 |
| Dominik Szoboszlai | LIV | MID | £7.0m | 38.4% | 15 | 270 | 0.09 | 0.04 | 3.22 |
| Rayan Cherki | MCI | MID | £7.8m | 30.3% | 25 | 173 | 0.05 | 0.11 | 0.76 |
| Morgan Rogers | CHE | MID | £7.6m | 28.4% | 19 | 257 | 0.09 | 0.09 | 1.92 |
| Bryan Mbeumo | MUN | MID | £7.9m | 25.5% | 21 | 270 | 0.18 | 0.04 | 1.89 |
| Gabriel dos Santos Magalhães | ARS | DEF | £8.0m | 24.8% | 15 | 270 | 0.04 | 0.00 | 2.33 |
| Dominic Calvert-Lewin | LEE | FWD | £6.0m | 23.9% | 10 | 252 | 0.13 | 0.01 | 1.02 |
| Cole Palmer | CHE | MID | £9.6m | 22.2% | 21 | 262 | 0.08 | 0.03 | 2.24 |
| Bart Verbruggen | BHA | GKP | £4.5m | 22.2% | 9 | 270 | 0.00 | 0.02 | 0.00 |
| Alexander Isak | LIV | FWD | £9.1m | 20.6% | 23 | 243 | 0.18 | 0.00 | 0.57 |
| Joško Gvardiol | MCI | DEF | £5.6m | 19.9% | 22 | 254 | 0.02 | 0.01 | 1.93 |
| Maxim De Cuyper | BHA | DEF | £4.8m | 19.8% | 21 | 243 | 0.12 | 0.03 | 0.92 |
| Antonín Kinský | TOT | GKP | £4.5m | 18.7% | 9 | 270 | 0.00 | 0.00 | 0.00 |
| Marc Guéhi | MCI | DEF | £6.0m | 18.6% | 20 | 270 | 0.07 | 0.03 | 2.00 |
| Antoine Semenyo | MCI | MID | £8.4m | 18% | 13 | 270 | 0.01 | 0.07 | 1.33 |
| Martin Dubravka | TOT | GKP | £4.0m | 17.8% | 0 | 0 | 0.00 | 0.00 | 0.00 |
| Christos Tzolis | ARS | MID | £6.4m | 17.4% | 11 | 210 | 0.02 | 0.03 | 2.04 |
| Virgil van Dijk | LIV | DEF | £6.5m | 17.3% | 9 | 270 | 0.02 | 0.00 | 2.78 |
| Yoane Wissa | NEW | FWD | £6.2m | 17% | 13 | 261 | 0.11 | 0.00 | 1.91 |
| Pascal Groß | BHA | MID | £5.5m | 16.2% | 16 | 270 | 0.06 | 0.03 | 1.67 |
| Nico O'Reilly | MCI | DEF | £6.5m | 15.1% | 4 | 150 | 0.01 | 0.04 | 0.39 |
| Issa Diop | IPS | DEF | £4.0m | 14.8% | 7 | 270 | 0.00 | 0.00 | 3.11 |
| Cody Gakpo | LIV | MID | £7.2m | 14.5% | 28 | 250 | 0.03 | 0.09 | 2.85 |
| Mamadou Sangaré | BRE | MID | £5.7m | 14.1% | 18 | 210 | 0.03 | 0.03 | 3.84 |
| Luke Shaw | MUN | DEF | £4.4m | 14% | 7 | 252 | 0.00 | 0.04 | 2.27 |
| Martin Ødegaard | ARS | MID | £6.6m | 13.6% | 24 | 221 | 0.08 | 0.08 | 1.89 |
Defensive contributions, shortened to DefCon by most managers, are the defensive actions the game now pays points for. A defender earns two points in a match where they record ten or more clearances, blocks, interceptions and tackles combined. For midfielders and forwards the threshold is twelve, and recoveries count toward their total as well as the four actions defenders are measured on. The points are awarded once per match: hitting the threshold pays two, and going well beyond it pays exactly the same two.
That threshold is what makes the statistic awkward to shop for. What matters is not a player's average but how often they cross the line, so a midfielder who reliably posts thirteen or fourteen is worth far more than one who alternates between six and twenty for the same mean. The explorer above shows defensive actions per 90 for every player, adjusted for how many minutes sit behind the number, and the projection model converts each player's rate into the probability of clearing their own threshold rather than assuming the average player scores the average points.
Two separate tools sit on top of this data. The team builder is for drafting a fifteen from scratch: the £100.0m budget and three-per-club limit are enforced as you pick, the whole pool is filterable on any statistic, and auto-pick gives you a starting point to argue with. The team rater is for a squad that already exists — put in your FPL team ID and it scores what you own, names the captain and tells you which picks are holding you back.
The same player data drives the rest of OddAlerts. If you back your fantasy reads with real money, the Player Props Tool shows shot, goal and card markets across the major leagues, xG Stats covers underlying team performance, and Referee Stats matter more than most people think for card markets. Everything is also available through the OddAlerts Football Data API.
